Neurocognitive Recovery in Abstinent Patients with Alcohol Use Disorder: A Scoping Review for Associated Factors
Jeroen Staudt
Tim Kok
Hein A de Haan
Serge J W Walvoort
Jos I M Egger
SimpleOriginal

Summary

This 31 study review on abstinent AUD patients finds smoking and brain volume changes consistently linked to neurocognitive recovery. Alcohol quantity and education show no effect; other factors are understudied or show mixed results.

2023

Neurocognitive Recovery in Abstinent Patients with Alcohol Use Disorder: A Scoping Review for Associated Factors

Keywords abstinence; alcohol; contextual neuropsychology;; neurocognitive recovery; substance use disorder

Abstract

Objective: Studies have reported inconsistent results regarding the extent to which neurocognitive recovery occurs in abstinent patients with alcohol use disorder (AUD). In addition to abstinence, other factors may have influenced this process and contributed to the inconsistencies. This review examines the factors investigated in this regard and describes the possible influence of each factor based on the evidence collected.

Methodology: PubMed was systematically searched for articles published between January 2000 and July 2023. Longitudinal humane studies investigating neurocognitive recovery in abstinent adult AUD patients were included. Studies with a cross-sectional design were excluded, as were studies that did not classify AUD according to the DSM-IV or 5 criteria, only examined binge use, did not report neuropsychological outcomes or duration of abstinence, or where neurological disorders were present.

Results: Sixteen categories of factors were distinguished from 31 full-text articles. Consistent patterns were found, indicating an association between neurocognitive recovery and the "smoking" and 'brain volume" factors. Consistent patterns were also found indicating that there is no relationship with "quantities of alcohol used" and "education level." A similar consistent pattern was also found for "polysubstance use", "gender" and "verbal reading", but the number of studies is considered limited. The association with "age" is studied frequently but with inconsistent findings. The remaining eight factors were regarded as understudied.

Conclusion: The clearest patterns emerging from the evidence are a predominantly negative influence of smoking on neurocognitive recovery, associations between changes in brain area volume and neurocognitive recovery, and no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, nor with educational attainment. Future research on the understudied factors and factors with inconsistent evidence is needed, preferably through longitudinal designs with multiple assessment periods starting after at least two weeks of abstinence.

Introduction

Impaired neurocognitive function is common in treatment seeking patients with an alcohol use disorder (AUD). Alcohol intoxication is associated with loss of control and an increased probability of potentially harmful behaviors, complicating the maintenance of sobriety. Moreover, chronic and excessive alcohol consumption may result in long-lasting cognitive impairments. Since commonly used therapies such as cognitive behavioral therapy or motivational interviewing require intact cognitive function, cognitive impairments impede treatment success and are related to higher drop-out rates. Abstinence from alcohol can lead to (partial) recovery of neurocognitive function. However, studies have reported inconsistent results regarding the extent of neurocognitive recovery. This could be explained by two major problems.

First, most studies on neurocognitive recovery in abstinent AUD patients used a cross-sectional design. While these studies allow insight into neurocognitive recovery, they only provide a snapshot of functions over time and, as a result, are unable to reliably detect within-subject changes over a period of abstinence. Therefore, longitudinal studies are needed to improve our understanding of neurocognitive recovery. However, it is challenging to follow patients over time and collect the data needed to test these hypotheses because participants with AUD often show lower adherence and limited abstinence rates.

A second problem that may underlie these inconsistent findings is the lack of knowledge about factors other than abstinence that influence the course of neurocognitive recovery. Frequently mentioned are the number of previous medical detoxifications and biological factors such as liver complications and thiamine deficiencies, polydrug use, age, smoking, family history of alcohol dependence, and individual historical aspects of alcohol use (eg, total amount of alcohol consumed over a lifetime, recent alcohol consumption, and duration of AUD). While these factors are often discussed as potentially contributing to the variability seen in neurocognitive recovery, they have received insufficient attention in observational research. In addition, studies do not always provide suitable data or use validated methods to measure these factors. This was illustrated by two meta-analyses on the recovery of neurocognitive function in abstinent AUD patients. Insufficient detail of moderating factors or unreliable data limits the analysis of such variables leading to inconsistent findings where the latter author concluded that cognitive dysfunction abates after one year of sobriety, while the results from Crowe et al suggested pervasive cognitive impairments on several timeframes of abstinence duration, even after one year.

In summary, longitudinal research is necessary to increase our understanding of the recovery of neurocognitive function in abstinent AUD patients. Insight into the factors that influence this process can aid in realizing an effective longitudinal study design and in lowering the threshold for conducting this challenging longitudinal research.

In the present review, we aimed to answer the following questions: (a) Which factors are investigated in research on the recovery of neurocognitive function in abstinent AUD patients and (b) what is the influence of these factors on the recovery of neurocognitive function during abstinence from alcohol? In addition, the clinical value and applicability of the current knowledge of these factors will be discussed and considered in terms of their putative relevance for future research on the recovery of neurocognitive function in patients with abstinent AUD.

Method

This scoping review aims to answer the aforementioned questions using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Our primary outcome measure was the change in neurocognitive function, as measured with neuropsychological instruments.

Search Strategy

In order to identify articles, a literature search in PubMed was performed using the following search terms: ((Alcohol AND (recov* OR abstin*) AND (execut* OR memor* OR visu* OR attent* OR social OR longit* OR cogn* OR neuropsy* OR MRI OR DTI OR VBM OR MRS OR CT OR PET OR SPECT OR EEG OR ERP OR spectroscopy OR neuroimaging OR neurophysiology))) AND (cogn*[Title/Abstract] OR neuropsy*[Title/Abstract] OR memory[Title/Abstract] OR attention[Title/Abstract] OR execut*[Title/Abstract] OR visu*[Title/Abstract]), filters: Humans.

Article Selection

During the initial screening, articles were selected by two reviewers (JS and TK) based on their titles or abstracts. Only English-language manuscripts published in peer-reviewed journals were considered for inclusion, with the aim of including well-established methodologically sound studies. Humane, longitudinal studies investigating neuropsychological or neurocognitive function in adult abstinent patients (≥18 years) with alcohol dependency according to DSM-IV (TR) or alcohol use disorder according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders) criteria were included. The included reviews were systematically screened for relevant references to additional papers. Studies on abuse (DSM-IV), binge or heavy episodic drinking only, were excluded, as were cross-sectional studies, as this review aimed to clarify the factors associated with cognitive recovery over time in abstinent AUD patients. Finally, studies were excluded if a classification of alcohol use disorder for participants included in the study was missing, if there were no neuropsychological instruments used, when the duration of abstinence was not described, or when patients were diagnosed with an alcohol-related neurological disease (eg, Korsakoff, Marchiafava-Bignami, Alcohol Dementia, epilepsy, dementia).

The search encompassed articles published between January 2000 and July 2023, following the suggestion by Fernández-Serrano et al to include studies that were published after the surge of contemporary neuroscientific models of addiction and similar to other reviews on the effects of alcohol on neuropsychological function in AUD patients.

The full article was retrieved and discussed by the two reviewers when there was uncertainty regarding the inclusion of a study. A consensus was reached for all discussed articles. The remaining articles were full-text articles and read to be used for data extraction.

Data Extraction

For each study, all relevant data from the results and discussion sections were selected using a coding form (available via the corresponding author) with fields containing information about the author, year of publication, study design, number of participants/controls, neuropsychological measure(s), and (non-)significant predictors of neuropsychological outcomes.

In order to quantify the design quality, validity, and utility for patient care, the level of evidence (1 (very strong) to 5 (weak)) of each included article was rated by two independent reviewers (JS and TK) using the Oxford Classification for Evidence-Based Medicine (OCEBM Levels of Evidence Working Group) (Howick et al, 2011). Evidence strength was rated per study following the recommendations of the OCEBM. The studies included for the purpose of this review were considered as prognostic.

The effects on neuropsychological outcome measures were placed under the most appropriate neuropsychological domain after a consensus meeting with both the reviewers. The classification of neuropsychological domains was largely adopted from the study by Fernández-Serrano et al Regarding this classification, it is important to point out the overlap between various neuropsychological domains and the fact that neurocognitive tasks used are not specific indicators of one neuropsychological function.

All predictors from the full-text articles included for this review were sorted into categories using a coding form. During the collection process, reviewers (JS and TK) identified 16 categories. The extracted variables were placed by the reviewer under the most appropriate category at their own discretion. In case of doubt, the other reviewer was consulted, and consensus was reached. The categories were regrouped into five domains, again with the agreement of both the reviewers. The following five domains were distinguished: drinking-related factors, demographic factors, psychiatric factors, premorbid neurocognitive function, and medical factors.

The effects and associations found for a specific factor and their direction, are narratively synthesized and discussed. Findings are considered significant at alpha level ≤.05.

Results

During the screening, 2179 articles, including 15 reviews, were retrieved based on the search criteria (Figure 1). A total of 58 articles remained for inclusion and inspected by two reviewers. Within this stage, the primary aim was to include studies that explicitly considered the association between abstinence duration, recovery of neurocognitive function, and other relevant factors. During this final process, we excluded several studies (no longitudinal analyses (10), no alcohol disorder according to DSM-IV or DSM-5 criteria (4), narrative review (3), study protocol (2), only a cognitive screening instrument used (5), no abstinence duration reported (2), and age <18 years (1)), resulting in 31 articles for which data could be extracted and used for the purpose of this review.

Figure 1.

Fig 1

Prisma flow diagram detailing the screening process.

Summary of Factors

Regarding the 31 studies included for analysis, most (25/31) started cognitive assessments within two weeks after admission, using neuropsychological tasks covering domains of executive function (21/31), memory and learning (22/31), attention (9/31), processing speed (13/31), spatial processing (8/31), intelligence (11/31), and social cognition (2/31). Abstinence from alcohol was verified by means of biomarkers (and in some studies also self-report) (13/31 studies), by means of self-report only (5/31 studies), or abstinence control measures were not mentioned (13/31 studies).

Table 1 summarizes the results per factor based on the number of studies that found an association or effect with neurocognitive recovery and the number that did not. Found associations and effects for each factor pointed in one direction. Per study, the rated OCEBM level is marked in superscript. Studies in this review have been rated from 2 to 4.

Table 1. Neurocognitive Recovery in Abstinent AUD Patients: Factors and Evidence

Table 1

Drinking Related Factors

Smoking

Eight studies examined the association between tobacco smoking and neurocognitive recovery in abstinent AUD patients. Six studies found significant effects of chronic smoking on neurocognitive recovery, with abstinence duration from alcohol varying from five weeks to 9 months. Smoking adversely affects neurocognitive recovery during short- and long-term abstinence, in terms of processing speed, learning and memory, spatial processing, executive function and fine motor skills.

Additionally, greater current smoking severity was related to less neurocognitive improvement and former smoking status (never smoking or former smoker) modulated neurocognition, with never-smoking AUD patients showing the greatest recovery. Active smokers showed less recovery than former- or never-smoking AUD patients. Former smoking AUD patients showed less neurocognitive recovery than never smoking AUD patients. In addition, Yeh et al found lower performance on domains of learning and memory in smoking AUD patients compared to never smoking AUD patients after 7 months of abstinence. Moreover, the results indicated that smoking status interacted with both abstinence duration and age, with older age leading to poorer neurocognitive performance.

Two studies did not find an association between chronic smoking and recovery of neurocognitive function. In a study on the effect of brain-derived neurotrophic factor (BDNF) genotype within subgroups of AUD patients classified by smoking status, Hoefer et al found changes in learning and memory to correlate with hippocampal volume depending on BDNF genotype. They concluded that BDNF genotype, but not smoking status or measures of drinking severity, regulates functionally relevant hippocampal volume recovery in abstinent AUD patients. In another study, smoking status was not associated with neurocognitive recovery on domains of executive function, memory and speed.

In summary, the results show a mostly consistent pattern of a negative association between tobacco use and recovery on several neurocognitive domains during varying periods of abstinence.

Quantities of Alcohol Used

Thirteen studies analyzed the association between quantified alcohol use and recovery of neurocognitive function. Variables included among other things “number of average drinks per month at 1, 3 and 8 years of drinking”, “lifetime years of drinking”, “lifetime drinks per month”, “months of heavy drinking”, “age of onset of heavy drinking”, ‘lifetime drinks’ and ‘1 year average drinks’, “alcohol dose” or “duration of dependence”, “lifetime alcohol use”. Eleven studies did not find an association between variables quantifying alcohol use and recovery on domains of executive function, learning and memory, attention, processing speed and recovery of social cognitive function. The abstinence duration periods ranged from 1 day up to 48 months, with most studies using abstinence periods within one year (8/11 studies). Other studies have investigated neurocognitive recovery during abstinence periods up to 48 months.

Two studies found an association between quantified alcohol use (length of alcohol use and abuse, duration of dependency and non-dependency, average intake per day, last intake) and recovery on domains of learning and memory, intelligence, spatial processing, and executive function, using abstinence periods of three and six months.

In summary, the evidence shows a largely consistent pattern in which no association between quantities of previous alcohol use and recovery on several neurocognitive domains during varying periods of abstinence could be found.

Polysubstance Use

Four studies examined the association between polysubstance use and recovery of neurocognitive function. One study investigating neurocognitive recovery in patients with polysubstance use disorder (including AUD) showed significant improvements on domains of general intelligence, executive function, working memory, and global cognition after four months of abstinence. No significant improvements were observed on domains of visuospatial skills and processing speed. No longitudinal comparison with AUD-only patients was made. Three studies did not find an association between single or polysubstance use next to alcohol use and recovery on domains of executive function, learning and memory, and processing speed, with abstinence duration periods ranging from one month to eight months.

In summary, the number of studies is limited but shows a pattern in which no association could be found between polysubstance use and recovery on several neurocognitive domains, during varying periods of abstinence.

Number of Previous Detoxifications

Three studies analyzed the association between the number of previous detoxifications and the recovery of neurocognitive function. In a study of patients with AUD, a distinction was made between groups with few medical detoxifications (≤1) and many medical detoxifications (≥2). The former group performed better on tasks of executive function, as well as learning and memory after three to six months of abstinence. No differences were found in the first three months of abstinence. One study did not find the number of inpatient detoxifications to be a predictor in similar domains after 24 months of abstinence. Another study did not find a significant correlation between the number of previous detoxifications and recovery of social cognitive function after eight weeks of abstinence. In summary, evidence for an association between previous detoxification and recovery of neurocognitive function is considered limited and inconsistent.

Positive Family History

Five studies examined the association between a positive family history (PFH) and recovery of neurocognitive function. Three studies found a negative association between PFH status and recovery on domains of executive function after six to seven weeks of abstinence or 15 months of abstinence. Two studies did not find an association between PFH and social cognitive function after two months of abstinence. In summary, the evidence is considered limited and suggests a negative association between PFH and executive function and no association between PFH and social cognitive function.

Demographic Factors

Age

Four out of ten studies found a negative association between increasing age and recovery of executive function, learning and memory, and speed after 6 to 15 months of abstinence. Six studies did not find an association between age and recovery of executive function, learning and memory, attention, speed, and social cognitive function after an abstinence duration varying from three weeks to nine months of abstinence. In summary, a larger number of studies have shown inconsistent results regarding the association between age and recovery of neurocognitive function.

Gender

Three studies examined the association between gender and neurocognitive recovery and did not find any effects on domains of executive function after 15 months of abstinence, nor on attention after one and a half months of abstinence, or social cognitive function after eight weeks of abstinence. Evidence is considered limited, but consistently shows no association between gender and recovery of neurocognitive function.

Education

Five of the six studies did not find an association between educational level and neurocognitive recovery. After controlling for education level in their analyses, no association was found with the performance on domains of executive function, learning and memory, attention, processing speed and visuospatial processing, between subgroups, after abstinence duration periods of 1.5 months till 15 months. One study found that higher education predicted a better recovery of verbal abilities after an abstinence period of 1.5 months. Taken together, the evidence largely shows a consistent pattern showing that educational attainment is not associated with the recovery of neurocognitive function.

Psychiatric Factors

Depression

Seven studies examined the association between depressive symptoms and recovery of neurocognitive function, of which three studies did not find an association between depressive symptoms and recovery on domains of executive function, learning and memory, or processing speed after abstinence periods varying from eight weeks to 48 months of abstinence. Two studies did not find an association between depressive symptoms and social cognitive function after two months of abstinence.

Two studies found a negative association between depressive symptoms and recovery of executive function at five weeks of abstinence and after 15 months of abstinence. All studies examined depressive symptoms but did not classify depression using the DSM criteria.

One study analyzed the association between AUD and Bipolar Disorder (BD) and found that patients with co-occurring BD and AUD may suffer from more severe cognitive dysfunction and less favorable recovery of cognitive deficits than patients without AUD over the course of remission from a mood episode.

In summary, evidence of an association between depressive symptoms and recovery of neurocognitive function is considered insufficient. The results show an inconsistent pattern of an association between depressive symptoms and recovery of executive function, limited evidence of an association with recovery on domains of learning and memory and processing speed, and limited evidence showing no association between depressive symptoms and social cognitive function.

Antisocial Personality Disorder

Two studies examined the association between antisocial personality disorder (ASPD) and neurocognitive recovery. One study did not clearly state whether ASPD coincided with a lack of abstinence, and in the other, ASPD was only associated with executive function at baseline and not with changes in neurocognitive function. The evidence found is considered to be limited.

Premorbid Neurocognitive Function

Verbal Reading Task

Four out of five studies found no association between performance on a verbal reading task and the recovery of executive function, learning and memory, processing speed, and spatial processing after six till 48 months of abstinence. In addition, Rosenbloom et al argued that overall test results showed higher scores on most tests by patients completing their trajectory compared to patients who dropped out of the study in a later phase, suggesting the possibility that improvements in sobriety were due to higher initial function.

In one study, the results of a verbal reading task explained part of the found improvement in executive function, processing speed, and spatial processing after an abstinence period of five weeks.

In summary, a mostly consistent pattern of limited studies shows no association between performance on a verbal reading task and the recovery of neurocognitive function, after six to 48 months of abstinence. One study found an association after five weeks of abstinence, indicating a possible relationship with short-term abstinence.

Neurocognitive Performance at Baseline

One study showed that executive function at baseline predicted executive function after an abstinence duration of 15 months.

Medical

Blood Values

Three studies examined the association between blood values and recovery of neurocognitive function. Two studies, using assessments at admission and at one and a half month after admission, found improvement in domains of learning and memory, and attention to be associated with NAA (N-acetylaspartate) values.

A third study found that baseline medical test results (only specified as “abnormal results from blood and urine tests used to detect signs of liver, blood, kidney, and connective tissue disease”) directly predicted less recovery on measures of executive function after 15 months of abstinence.

In summary, evidence of an association between blood values and recovery of neurocognitive function is considered limited.

Medical Conditions

Three studies examined the association between medical conditions and recovery of neurocognitive function, two of which found no association between hypertension and hepatitis C (measured at baseline) in domains of executive function, learning and memory, processing speed, attention, and visuospatial processing after abstinence periods of 4 and 8 months.

Bates et al did find fewer medical conditions at baseline (not specified and measured with the Life Experiences and Social Resources Inventory) to contribute to the recovery of verbal ability assessed after 1.5 months of abstinence.

In summary, the evidence for an association between medical conditions and recovery of neurocognitive function is considered inconsistent, and the number of studies is limited.

Brain Volumes

Five of the six studies found an association between brain volumes and recovery of (visuospatial) memory, visuospatial learning, and processing speed using abstinence periods varying from one week of abstinence to eight months of abstinence.

In non-smoking AUD patients, increasing hippocampal volumes correlated with visuospatial memory improvements after one month of abstinence. A moderate-to-strong correlation was found between hippocampal volume change and improvements in the domain of learning and memory after one month of abstinence, depending on the brain-derived neurotrophic factor (BDNF) genotype (Val homozygotes only, not in MET carriers). Between one month and seven months, however, hippocampal volume changes did not correlate significantly with changes in neurocognitive function.

Increasing volumes in all gray matter and white matter regions (with the exception of the thalamus) were associated with improved processing speed over nearly eight months of abstinence, in non-smoking AUD patients, only. Yeh et al found significant correlations between total brain volume changes and recovery of visuospatial learning between one week and one month of abstinence from alcohol for smoking AUD but not for non-smoking AUD. However, the greater rate of brain volume increase in the first period of abstinence (one week to one month) in smoking AUD patients was inversely related to the improvement of visuospatial memory during the second period of abstinence (one month to seven months). Despite numerically faster brain volume gains and a trend toward faster ventricular shrinkage in smoking AUD patients, the recovery of visuospatial learning and memory of smoking AUD patients was below that of non-smoking AUD patients in the second period.

Changes in lateral ventricular volume were negatively correlated with overall memory performance after abstinence periods varying from three weeks to two years. Changes in the fourth ventricle were not associated with changes in memory performance after one month of abstinence.

In summary, most studies have shown a consistent pattern of association between changes in brain volume during abstinence and recovery of neurocognitive function. This process can be influenced by smoking.

Perfusion

One study found no correlation between changes in frontal and parietal gray matter perfusion and changes in neurocognitive performance in executive function, learning and memory, processing speed, spatial processing, and intelligence after one month of abstinence.

Discussion

This scoping review describes the scientific evidence for factors associated with the recovery of neurocognitive function in abstinent AUD patients (see Table 2 for a comprehensive overview of the strength of evidence found per factor). In this section, we discuss the most consistent patterns found, relate them to evidence in the relevant literature, and identify research gaps.

Table 2. Overview of the Strength of Evidence per Factor

Table 2

First, the accumulated evidence suggests a largely consistent pattern of a negative association between smoking and neurocognitive recovery in the domains of processing speed, learning and memory, spatial processing, executive function, and fine motor skills, up to nine months of abstinence from alcohol. The interaction of nicotine and alcohol on neurocognitive function is of interest because it is highly prevalent in AUD patients, creating synergy and multiplying health risks. Future studies of neurocognitive recovery in AUD patients should incorporate smoking status and differentiate between active smoking, former smoking, and never smoking status.

Second, increasing brain volumes during abstinence from alcohol within one year is associated with improvements in (visuospatial) memory and learning, and speed. Some evidence has also been found suggesting an association between decreasing lateral ventricular volume and memory improvement. Due to the process of sustained abstinence, ventricular volumes decrease and brain structures such as the temporal, insular, anterior cingulate cortices, amygdala, thalamus, hippocampus, brainstem, and cerebellar cortex increase. Identifying the reversibility of the structural and functional changes caused by alcohol use is important. The results of this review further support the association between the recovery of neurocognitive function with changes in brain volumes. In addition, findings from the included studies suggest that other factors may influence this relationship, such as smoking status or BDNF genotype.

Two other well-studied factors, amounts of alcohol used and education level, show consistent evidence that they are predominantly not associated with the recovery of neurocognitive function. First, factors reflecting alcohol quantities were not, or sparsely, associated with neurocognitive recovery in various domains (executive function, learning and memory, attention and processing speed, and social cognition) after varying abstinence periods of up to 4 years. This finding has been noted before, and is somewhat counterintuitive. Excessive alcohol use is related to structural and functional abnormalities in the brain, which, in turn, are associated with neuropsychological impairments. There may be a methodological problem underlying this finding. Former alcohol use was retrospectively assessed in these studies by relying on self-report measures and the ability to adequately retrieve information from the past. AUD, however, is associated with episodic memory deficits, varying from learning impairments to spatiotemporal coding deficiencies (ie, binding spatial and temporal information), and deficiencies in autonoetic awareness (ie, recalling situations from the past by introspectively reliving these situations). These memory impairments may compromise the validity of the results obtained using the self-report measures. In addition, it can be considered that other factors associated with excessive alcohol use may cause severe neurocognitive impairments, such as thiamine deficiency.

Second, accumulated evidence suggests that educational attainment is not associated with the recovery of neurocognitive function in multiple domains. This finding seems to contradict the robust association between education level and cognitive performance. Indeed, the level of education is believed to influence the recovery of neurocognitive function and to reflect cognitive reserve. However, these results were derived from cross-sectional studies, which showed a correlation at one point in time. Recovery of function, as reflected by changes in cognitive function with multiple assessments, was not measured. In line with our findings, other studies on cognitive reserve have shown no substantial relationship between educational attainment and changes in cognitive performance or cognitive reserve.

The evidence for an association between the factors “polysubstance use”, “premorbid neurocognitive function” or “gender” with the recovery of neurocognitive function is considered insufficient. In most cases, the patterns consistently show no evidence of an association. Firstly, polysubstance use has been studied to a limited extent. Only four studies were included, of which two studies had lower levels of evidence ratings (small sample sizes: and no control group). Moreover, two studies that did not find an effect did not include smoking status in their analyses. This excludes that part of the effects can be ascribed to smoking status, given the evidence for the influence of smoking status on neurocognitive recovery in AUD patients. The field of research on polysubstance use has long been overlooked, and the use of other substances was largely seen as a nuisance before 2010. Given the few longitudinal studies available, the assumed impact of smoking status, and specific neurobiological alterations coinciding with polysubstance use, more studies are needed.

Second, premorbid neurocognitive function, assessed by means of a verbal reading task, could not be associated with the recovery of neurocognitive function. Regarding the results, the following considerations are made to enhance future research. Investigations of alcohol-related neurocognitive impairments often use a verbal reading task to establish premorbid intelligence, such as the NART (National Adult Reading Task). Previous research on the use of the NART provided evidence for justified use in estimating premorbid intelligence in patients with frontal lobe damage, Korsakoff syndrome, and mild or moderate stages of Alzheimer’s disease. Indeed, studies indicate that reading tests index prior intellectual ability and provide the most reliable and precise estimates of the WAIS-IV full scale IQ. However, in our review, most studies used these measures to investigate the effect of premorbid intelligence on performance or recovery on other neurocognitive instruments. To our knowledge, studies on the relationship between verbal reading tasks and neurocognitive measures other than intelligence tasks are scarce, with one study indicating a moderate correlation between performance on the NART and performance on measures of memory. Therefore, it seems appropriate to be careful when using a verbal reading task to predict specific neurocognitive function or recovery of neurocognitive function. In addition, tests assessing premorbid intelligence are likely to provide the most reliable premorbid estimates of full-scale intelligence in the mean range while overestimating intelligence in those with very low scores and underestimating those with very high scores. Finally, it is considered that a lower verbal ability can precede heavy alcohol use or can be the result of both lower premorbid intelligence and more intellectual decline.

A third factor, gender, shows no association with the recovery of neurocognitive function but has been studied to a limited extent. The strength and generalizability of the evidence is limited for several reasons. Most studies included in this review consisted largely of men, which may have biased the results. Research within AUD populations largely consists of men, which complicates research on gender effects. Furthermore, the included studies had a small sample size or focused on only one domain of recovery (social cognitive function). Literature on the effect of gender differences on cognitive function states that men and women are generally evenly capable of cognitive capacities. It remains unclear whether this also applies to the recovery of neurocognitive function in AUD patients, since only a few studies have been performed on this matter, to our knowledge. Neurobiological studies suggest gender-specific neural recovery effects and greater neurotoxic effects of alcohol in binge drinking women than in men. Findings from a recent study showed a significant association between no recovery of cognitive function and the female gender in recovering AUD patients.

One factor that has been analyzed in multiple studies on the recovery of neurocognitive function is age. However, the results showed an inconsistent pattern of studies that found a negative association and studies that found no association. These findings may partially cohere with the relatively low and equally distributed age of patients included in the studies (between 40 and 50 years, with, roughly estimated, most patients predominantly aged between 30 and 60 years). Moreover, the interaction of age with alcohol is complex, since the recovery of neurocognitive function can be modulated by age at exposure, aging following alcohol toxicity or thiamine deficiency, and aging during chronic alcohol use.

Finally, the findings of this review indicate that most of these factors are understudied. In this regard, studies on the influence of polysubstance use, the number of previous detoxifications, positive family history, sex, depression, ASPD, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion on recovery of neurocognitive function during abstinence are limited and in need of further research. In addition, it is noted that alcohol use disorder is highly comorbid with other psychiatric disorders, such as depression or personality disorder, as was also found within some of the studies included. This, so-called “dual disorder”, is associated with poorer prognosis (eg, greater psychopathological severity, higher frequency of psychiatric admissions) and may be accompanied by other, distinct, neuropsychological characteristics.

Recommendations for Future (Longitudinal) Research

Based on the findings of this review, a number of recommendations can be made that may lower the threshold for clinically relevant scientific research and further aid in modelling the recovery of neuropsychological function with sustained abstinence.

  • The recovery of neurocognitive function was negatively associated with smoking. Smoking status (never smoking, former smoking, and smoking) is associated with differential effects on the recovery of neurocognitive function and should be incorporated in future research.

  • There is sufficient evidence for the lack of an association between “quantities used” (by means of self-report) and recovery of neurocognitive function during abstinence. It should be noted that episodic memory deficits might obscure the self-reported findings of AUD patients regarding alcohol use in the past. It is therefore recommended to consider carefully the use of self-report tools to measure prior alcohol consumption, and their purpose in neurocognitive recovery research.

  • Most studies (25/31) included in this review started the first assessments within two weeks of abstinence. Given the possible negative effects of withdrawal on neurocognitive function, it is recommended that neurocognitive function be assessed after at least two weeks of abstinence.92 Another study recommends assessment after six weeks of abstinence.

  • Findings from this review indicate that most factors are understudied, while scarce evidence is indicative of follow-up research. In this regard, associations of neurocognitive recovery with age, gender, polysubstance use, the number of previous detoxifications, blood values, medical conditions, depression and ASPD (also studied as dual disorders) should be studied in well-controlled cross-sectional, or preferably longitudinal, designs that account for abstinence duration.

  • Social cognition, or the recovery of social cognitive function, is an understudied neurocognitive domain that requires further research.

Limitations

This review is not without limitations, four of which we will mention here. First, methodological issues must be considered when interpreting our findings. Determining the predictive value of a factor, or its association, is always done in the context of other factors, and is valid, within the model used. Therefore, not finding an association or an effect means that there is no effect within the model handled. Studies within this review show considerable differences in the number of variables included in their analyses. In this regard, we notice that well-controlled, cross-sectional studies, including multiple relevant variables associated with neurocognitive functioning in abstinent AUD, also contribute to our understanding of neurocognitive recovery but have not been included in this review. Second, we did not pool data to meta-analyze the effects of individual factors since not all data were available from the included studies. Third, the instruments used to measure neurocognitive function in these studies are diverse and differ in terms of validity and reliability. In addition, there is diversity in the extent to which studies take into account possible learning effects associated with the instruments used, ranging from merely stating a limitation of the study to using parallel forms or calculating a reliable change index. Finally, there is a risk of publication bias by including only published studies in this review. We consider the risk, however, to be limited, as the factors studied were often not the primary focus of the included study, resulting, for example, in multiple null findings (eg, multiple studies showing no association between quantities of alcohol used with neurocognitive recovery).

Conclusion

Notwithstanding the aforementioned limitations, to our knowledge, this is the first review to systematically map the factors that may influence the recovery of neurocognitive function in abstinent AUD patients. The clearest patterns emerging from the evidence collected are a predominantly negative influence of smoking on the recovery of neurocognitive function, and associations between changes in volumes of various brain areas (hippocampal, ventricular, and total brain volume), and recovery of neurocognitive function. There is sufficient evidence for the lack of an association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, or between neurocognitive recovery and educational attainment.

Future research on several factors is indicated because these have been sparsely investigated using a longitudinal design (polysubstance use, the number of previous detoxifications, positive family history, gender, depression, ASPD, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion) and/or show conflicting findings (age). Longitudinal designs should preferably be used, with multiple assessment periods, starting at least after two weeks of abstinence, given the possibility of withdrawal symptoms interfering with neurocognitive performance.

Findings from these studies may help resolve the conflicting results found so far on the recovery of neurocognitive function and may expand our understanding of this process and the extent to which it occurs in the context of AUD. Ultimately, this will aid in creating a clinical profile that can be used to identify patients at risk of slower or limited recovery and to improve personalized care.

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Abstract

Objective: Studies have reported inconsistent results regarding the extent to which neurocognitive recovery occurs in abstinent patients with alcohol use disorder (AUD). In addition to abstinence, other factors may have influenced this process and contributed to the inconsistencies. This review examines the factors investigated in this regard and describes the possible influence of each factor based on the evidence collected.

Methodology: PubMed was systematically searched for articles published between January 2000 and July 2023. Longitudinal humane studies investigating neurocognitive recovery in abstinent adult AUD patients were included. Studies with a cross-sectional design were excluded, as were studies that did not classify AUD according to the DSM-IV or 5 criteria, only examined binge use, did not report neuropsychological outcomes or duration of abstinence, or where neurological disorders were present.

Results: Sixteen categories of factors were distinguished from 31 full-text articles. Consistent patterns were found, indicating an association between neurocognitive recovery and the "smoking" and 'brain volume" factors. Consistent patterns were also found indicating that there is no relationship with "quantities of alcohol used" and "education level." A similar consistent pattern was also found for "polysubstance use", "gender" and "verbal reading", but the number of studies is considered limited. The association with "age" is studied frequently but with inconsistent findings. The remaining eight factors were regarded as understudied.

Conclusion: The clearest patterns emerging from the evidence are a predominantly negative influence of smoking on neurocognitive recovery, associations between changes in brain area volume and neurocognitive recovery, and no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, nor with educational attainment. Future research on the understudied factors and factors with inconsistent evidence is needed, preferably through longitudinal designs with multiple assessment periods starting after at least two weeks of abstinence.

Introduction

Impaired neurocognitive function is commonly observed in individuals seeking treatment for alcohol use disorder (AUD). Alcohol intoxication is associated with a loss of control and an increased likelihood of engaging in potentially harmful behaviors, which complicates efforts to maintain sobriety. Furthermore, chronic and excessive alcohol consumption can lead to long-lasting cognitive impairments. Common therapies, such as cognitive behavioral therapy or motivational interviewing, require intact cognitive function. Therefore, cognitive impairments can hinder treatment success and are linked to higher dropout rates.

Abstinence from alcohol may lead to partial or full recovery of neurocognitive function. However, studies have yielded inconsistent results regarding the extent of this recovery. This inconsistency may be attributed to two main issues in research design.

Firstly, most studies on neurocognitive recovery in abstinent AUD patients have used a cross-sectional design. While these studies offer insights into neurocognitive recovery, they only provide a single snapshot of function over time. Consequently, they cannot reliably detect changes within an individual over a period of abstinence. Longitudinal studies are therefore necessary to better understand neurocognitive recovery. However, following patients over time and collecting the necessary data to test these hypotheses is challenging, as individuals with AUD often exhibit lower adherence to study protocols and limited rates of sustained abstinence.

A second issue contributing to inconsistent findings is the limited understanding of factors, other than abstinence, that influence the course of neurocognitive recovery. Commonly mentioned factors include the number of previous medical detoxifications, biological elements such as liver complications and thiamine deficiencies, polydrug use, age, smoking, a family history of alcohol dependence, and individual alcohol use history (e.g., total lifetime alcohol consumed, recent consumption, and AUD duration). Although these factors are often discussed as potential contributors to variability in neurocognitive recovery, they have not received sufficient attention in observational research. Additionally, studies do not always provide suitable data or use validated methods to measure these factors. This limitation has been highlighted by meta-analyses on neurocognitive recovery in abstinent AUD patients, where insufficient detail on moderating factors or unreliable data has restricted analysis, leading to conflicting conclusions among researchers.

In summary, longitudinal research is essential to enhance the understanding of neurocognitive function recovery in abstinent AUD patients. Gaining insight into the factors that influence this process can help in designing effective longitudinal studies and in reducing the obstacles associated with conducting such challenging research. This review aimed to identify which factors are investigated in research on neurocognitive recovery in abstinent AUD patients and to determine the influence of these factors on recovery during alcohol abstinence. Additionally, the clinical value and applicability of current knowledge about these factors are discussed, considering their potential relevance for future research on neurocognitive recovery in patients with abstinent AUD.

Method

This scoping review aimed to answer the stated questions using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The primary outcome measure was changes in neurocognitive function, as assessed by neuropsychological instruments.

Search Strategy

To identify relevant articles, a literature search was conducted in PubMed using specific search terms related to alcohol, recovery, abstinence, and various neurocognitive and neuroimaging terms. Filters were applied to include only human studies.

Article Selection

During the initial screening, two reviewers selected articles based on their titles or abstracts. Only English-language manuscripts published in peer-reviewed journals were considered to ensure methodologically sound studies were included. The review focused on human, longitudinal studies investigating neuropsychological or neurocognitive function in adult abstinent patients (18 years or older) diagnosed with alcohol dependency (DSM-IV) or alcohol use disorder (DSM-5). Included reviews were systematically screened for additional relevant papers. Studies on alcohol abuse (DSM-IV) or only binge/heavy episodic drinking were excluded, as were cross-sectional studies, since this review aimed to clarify factors associated with cognitive recovery over time in abstinent AUD patients. Studies were also excluded if a classification for AUD was missing, if neuropsychological instruments were not used, if the duration of abstinence was not described, or if patients had an alcohol-related neurological disease (e.g., Korsakoff syndrome). The search included articles published between January 2000 and July 2023, following recommendations to include studies published after the emergence of contemporary neuroscientific models of addiction. If there was uncertainty about a study's inclusion, the full article was retrieved and discussed by the two reviewers until a consensus was reached. The remaining full-text articles were then used for data extraction.

Data Extraction

For each included study, relevant data from the results and discussion sections were selected using a coding form. This form captured information such as author, publication year, study design, number of participants/controls, neuropsychological measures, and significant or non-significant predictors of neuropsychological outcomes. The level of evidence for each article, ranging from 1 (very strong) to 5 (weak), was rated by two independent reviewers using the Oxford Classification for Evidence-Based Medicine (OCEBM) to quantify design quality, validity, and utility for patient care. Studies included in this review were considered prognostic. The effects on neuropsychological outcome measures were categorized under the most appropriate neuropsychological domain after a consensus meeting between both reviewers. This classification of domains largely followed previous research, acknowledging the overlap between various neuropsychological domains and that neurocognitive tasks often reflect multiple functions. All predictors from the included full-text articles were sorted into 16 categories by the reviewers. These categories were then regrouped into five broader domains: drinking-related factors, demographic factors, psychiatric factors, premorbid neurocognitive function, and medical factors, again with agreement from both reviewers. Findings regarding effects and associations were described narratively, with significance typically set at an alpha level of ≤.05.

Results

During the screening process, 2179 articles, including 15 reviews, were identified based on the search criteria. Fifty-eight articles remained for detailed inspection by two reviewers. The primary goal at this stage was to include studies that explicitly considered the association between abstinence duration, neurocognitive recovery, and other relevant factors. During the final selection, several studies were excluded due to reasons such as lack of longitudinal analysis (10), no alcohol disorder diagnosis according to DSM-IV or DSM-5 criteria (4), being a narrative review (3), a study protocol (2), using only a cognitive screening instrument (5), no reported abstinence duration (2), or participants being under 18 years old (1). This resulted in 31 articles from which data could be extracted for this review.

Summary of Factors

Among the 31 included studies, most (25/31) initiated cognitive assessments within two weeks of admission. These assessments utilized neuropsychological tasks covering domains such as executive function (21/31), memory and learning (22/31), attention (9/31), processing speed (13/31), spatial processing (8/31), intelligence (11/31), and social cognition (2/31). Abstinence from alcohol was verified through biomarkers (and self-report in some studies) in 13 studies, by self-report only in 5 studies, or abstinence control measures were not mentioned in 13 studies. The studies reviewed were rated with OCEBM levels from 2 to 4, indicating varying strengths of evidence.

Drinking Related Factors

Smoking: Eight studies investigated the link between tobacco smoking and neurocognitive recovery in abstinent AUD patients. Six studies found significant negative effects of chronic smoking on recovery, across abstinence durations ranging from five weeks to nine months. Smoking was shown to adversely affect processing speed, learning and memory, spatial processing, executive function, and fine motor skills during both short- and long-term abstinence. Greater smoking severity correlated with less neurocognitive improvement, and never-smoking AUD patients generally showed the greatest recovery. Active smokers showed less recovery than former or never-smoking AUD patients, with former smokers showing less recovery than never-smokers. One study also noted that smoking status interacted with abstinence duration and age, with older age leading to poorer performance. Two studies did not find an association between chronic smoking and neurocognitive recovery. One suggested that brain-derived neurotrophic factor (BDNF) genotype, rather than smoking status, regulated hippocampal volume recovery. The other found no association with executive function, memory, or speed. In summary, most evidence consistently indicates a negative association between tobacco use and recovery across several neurocognitive domains.

Quantities of Alcohol Used: Thirteen studies analyzed the association between quantified alcohol use and neurocognitive recovery, using variables such as "number of average drinks per month," "lifetime years of drinking," and "duration of dependence." Eleven of these studies found no association between these quantified alcohol use variables and recovery in domains like executive function, learning and memory, attention, processing speed, and social cognitive function. Abstinence durations in these studies ranged from one day to 48 months, with most studies focusing on periods within one year. Two studies did find an association between quantified alcohol use (e.g., length of use, average intake per day) and recovery in learning and memory, intelligence, spatial processing, and executive function, with abstinence periods of three and six months. Overall, the evidence largely shows no association between prior alcohol consumption quantities and recovery in various neurocognitive domains during abstinence.

Polysubstance Use: Four studies examined the association between polysubstance use and neurocognitive recovery. One study, involving patients with polysubstance use disorder (including AUD), showed significant improvements in general intelligence, executive function, working memory, and global cognition after four months of abstinence, though no longitudinal comparison with AUD-only patients was made. Three other studies found no association between single or polysubstance use alongside alcohol use and recovery in executive function, learning and memory, and processing speed, with abstinence durations from one to eight months. In summary, the limited number of studies generally indicates no association between polysubstance use and recovery across several neurocognitive domains during varying periods of abstinence.

Number of Previous Detoxifications: Three studies analyzed the association between previous detoxifications and neurocognitive recovery. One study found that patients with fewer medical detoxifications (≤1) performed better on executive function and learning and memory tasks after three to six months of abstinence, with no differences observed in the first three months. Another study found no predictive value for the number of inpatient detoxifications in similar domains after 24 months of abstinence. A third study found no significant correlation between previous detoxifications and social cognitive function recovery after eight weeks of abstinence. In summary, evidence for an association between previous detoxification and neurocognitive recovery is limited and inconsistent.

Positive Family History: Five studies examined the association between a positive family history (PFH) and neurocognitive recovery. Three studies reported a negative association between PFH status and executive function recovery after six to seven weeks or 15 months of abstinence. Two studies found no association between PFH and social cognitive function after two months of abstinence. In summary, the evidence is limited and suggests a negative association between PFH and executive function but no association with social cognitive function.

Demographic Factors

Age: Four out of ten studies found a negative association between increasing age and recovery of executive function, learning and memory, and processing speed after 6 to 15 months of abstinence. Six studies found no association between age and recovery of executive function, learning and memory, attention, processing speed, and social cognitive function, with abstinence durations ranging from three weeks to nine months. In summary, a larger number of studies have shown inconsistent results regarding the association between age and neurocognitive recovery.

Gender: Three studies examined the association between gender and neurocognitive recovery. They found no effects on executive function after 15 months of abstinence, attention after one and a half months, or social cognitive function after eight weeks. Evidence is considered limited but consistently shows no association between gender and neurocognitive recovery.

Education: Five of six studies found no association between educational level and neurocognitive recovery. After controlling for education, no association was found with performance in executive function, learning and memory, attention, processing speed, and visuospatial processing across subgroups, after abstinence durations ranging from 1.5 to 15 months. One study found that higher education predicted better recovery of verbal abilities after 1.5 months of abstinence. Overall, the evidence largely shows that educational attainment is not associated with neurocognitive recovery.

Psychiatric Factors

Depression: Seven studies examined the association between depressive symptoms and neurocognitive recovery. Three studies found no association between depressive symptoms and recovery in executive function, learning and memory, or processing speed, across abstinence periods from eight weeks to 48 months. Two studies found no association between depressive symptoms and social cognitive function after two months of abstinence. Two studies found a negative association between depressive symptoms and executive function recovery at five weeks and after 15 months of abstinence. All studies examined depressive symptoms but did not classify depression using DSM criteria. One study analyzing AUD and Bipolar Disorder (BD) found that patients with co-occurring BD and AUD might experience more severe cognitive dysfunction and less favorable recovery of cognitive deficits than patients without AUD during remission from a mood episode. In summary, evidence for an association between depressive symptoms and neurocognitive recovery is insufficient, showing inconsistent patterns for executive function and limited or no association for other domains.

Antisocial Personality Disorder: Two studies examined the association between antisocial personality disorder (ASPD) and neurocognitive recovery. One study did not clearly state if ASPD coincided with a lack of abstinence, and in the other, ASPD was only linked to executive function at baseline, not to changes in neurocognitive function. The evidence found is considered limited.

Premorbid Neurocognitive Function

Verbal Reading Task: Four out of five studies found no association between performance on a verbal reading task and recovery of executive function, learning and memory, processing speed, and spatial processing after six to 48 months of abstinence. One study suggested that improvements in sobriety might be due to higher initial function, as patients who completed the study performed better. One study found that verbal reading task results explained some improvement in executive function, processing speed, and spatial processing after five weeks of abstinence. In summary, limited studies mostly show no association between verbal reading task performance and neurocognitive recovery after six to 48 months of abstinence, with one study indicating a possible relationship with short-term abstinence.

Neurocognitive Performance at Baseline: One study showed that executive function at baseline predicted executive function after 15 months of abstinence.

Medical

Blood Values: Three studies examined the association between blood values and neurocognitive recovery. Two studies, with assessments at admission and 1.5 months later, found improvement in learning and memory and attention domains to be associated with N-acetylaspartate (NAA) values. A third study found that abnormal baseline medical test results (indicating liver, blood, kidney, and connective tissue disease) directly predicted less recovery in executive function after 15 months of abstinence. In summary, evidence for an association between blood values and neurocognitive recovery is considered limited.

Medical Conditions: Three studies examined the association between medical conditions and neurocognitive recovery. Two found no association between hypertension and hepatitis C (measured at baseline) with executive function, learning and memory, processing speed, attention, and visuospatial processing after 4 and 8 months of abstinence. One study found that fewer baseline medical conditions contributed to verbal ability recovery after 1.5 months of abstinence. In summary, evidence for an association between medical conditions and neurocognitive recovery is inconsistent and limited.

Brain Volumes: Five of six studies found an association between brain volumes and recovery of visuospatial memory, visuospatial learning, and processing speed, with abstinence periods ranging from one week to eight months. In non-smoking AUD patients, increasing hippocampal volumes correlated with visuospatial memory improvements after one month of abstinence. A moderate-to-strong correlation was found between hippocampal volume change and improvements in learning and memory after one month, depending on BDNF genotype. However, between one and seven months, hippocampal volume changes did not significantly correlate with neurocognitive function changes. Increasing volumes in gray and white matter regions (except the thalamus) were associated with improved processing speed over nearly eight months of abstinence in non-smoking AUD patients only. One study found significant correlations between total brain volume changes and recovery of visuospatial learning between one week and one month of abstinence for smoking AUD patients, but not for non-smoking AUD patients. However, a greater rate of brain volume increase in the first period of abstinence in smoking AUD patients was inversely related to visuospatial memory improvement in the second period. Despite numerically faster brain volume gains and a trend toward faster ventricular shrinkage in smoking AUD patients, visuospatial learning and memory recovery in smoking AUD patients was lower than in non-smoking AUD patients in the second period. Changes in lateral ventricular volume negatively correlated with overall memory performance after abstinence periods from three weeks to two years. Changes in the fourth ventricle were not associated with memory performance after one month of abstinence. In summary, most studies show a consistent pattern of association between brain volume changes during abstinence and neurocognitive recovery, a process that can be influenced by smoking.

Perfusion: One study found no correlation between changes in frontal and parietal gray matter perfusion and changes in neurocognitive performance in executive function, learning and memory, processing speed, spatial processing, and intelligence after one month of abstinence.

Discussion

This scoping review describes the scientific evidence for factors associated with the recovery of neurocognitive function in abstinent AUD patients. This section discusses the most consistent patterns found, relates them to relevant literature, and identifies research gaps.

Firstly, accumulated evidence suggests a largely consistent negative association between smoking and neurocognitive recovery in domains such as processing speed, learning and memory, spatial processing, executive function, and fine motor skills, up to nine months of alcohol abstinence. The interaction of nicotine and alcohol on neurocognitive function is significant due to its high prevalence in AUD patients, creating synergistic effects and increasing health risks. Future studies on neurocognitive recovery in AUD patients should include smoking status and differentiate between active smoking, former smoking, and never smoking.

Secondly, increasing brain volumes during alcohol abstinence within one year are associated with improvements in visuospatial memory, learning, and processing speed. Some evidence also suggests an association between decreasing lateral ventricular volume and memory improvement. Sustained abstinence leads to decreased ventricular volumes and increased volumes in brain structures like the temporal, insular, anterior cingulate cortices, amygdala, thalamus, hippocampus, brainstem, and cerebellar cortex. Identifying the reversibility of structural and functional changes caused by alcohol use is important. The results of this review further support the association between neurocognitive function recovery and changes in brain volumes. Furthermore, findings from included studies suggest that other factors, such as smoking status or BDNF genotype, may influence this relationship.

Two other well-studied factors, amounts of alcohol used and education level, consistently show they are largely not associated with neurocognitive recovery. Firstly, factors reflecting alcohol quantities were not, or rarely, associated with neurocognitive recovery in various domains (executive function, learning and memory, attention and processing speed, and social cognition) after abstinence periods up to four years. This finding is somewhat counterintuitive, as excessive alcohol use is linked to structural and functional brain abnormalities, which are, in turn, associated with neuropsychological impairments. A methodological problem might underlie this finding: retrospective assessment of past alcohol use often relies on self-report measures, and AUD is associated with episodic memory deficits, which may compromise the validity of self-reported data. Additionally, other factors associated with excessive alcohol use, such as thiamine deficiency, might cause severe neurocognitive impairments.

Secondly, accumulated evidence suggests that educational attainment is not associated with neurocognitive recovery in multiple domains. This finding appears to contradict the robust association between education level and cognitive performance. Education level is generally believed to influence neurocognitive function recovery and to reflect cognitive reserve. However, these contrasting results were derived from cross-sectional studies, which showed a correlation at a single point in time. Recovery of function, as reflected by changes in cognitive function with multiple assessments, was not measured. Consistent with the review's findings, other studies on cognitive reserve have shown no substantial relationship between educational attainment and changes in cognitive performance or cognitive reserve.

Evidence for an association between polysubstance use, premorbid neurocognitive function, or gender with neurocognitive recovery is considered insufficient. In most cases, patterns consistently show no evidence of an association. Firstly, polysubstance use has been studied to a limited extent. Only four studies were included, two of which had lower levels of evidence ratings (small sample sizes, no control group). Moreover, two studies that found no effect did not include smoking status in their analyses. This omission is significant given the evidence for smoking's influence on neurocognitive recovery in AUD patients. The research field on polysubstance use has long been overlooked, with other substance use largely viewed as a confounding factor before 2010. Given the scarcity of longitudinal studies, the assumed impact of smoking status, and specific neurobiological alterations associated with polysubstance use, more studies are needed.

Secondly, premorbid neurocognitive function, assessed by a verbal reading task, could not be associated with neurocognitive recovery. To enhance future research, caution is advised when using verbal reading tasks to predict specific neurocognitive function or recovery of neurocognitive function. While such tests estimate premorbid intelligence, their relationship with non-intelligence neurocognitive measures is scarce. Additionally, these tests may over- or underestimate intelligence at the extremes of the spectrum. Finally, a lower verbal ability could precede heavy alcohol use or result from both lower premorbid intelligence and intellectual decline.

A third factor, gender, shows no association with neurocognitive recovery but has been studied to a limited extent. The strength and generalizability of the evidence are limited because most included studies primarily consisted of men, potentially biasing results. Research within AUD populations largely involves men, complicating the study of gender effects. Furthermore, included studies often had small sample sizes or focused on only one domain of recovery (e.g., social cognitive function). While general literature suggests men and women have similar cognitive capacities, it remains unclear whether this applies to neurocognitive recovery in AUD patients due to limited research. Neurobiological studies suggest gender-specific neural recovery effects and greater neurotoxic effects of alcohol in binge-drinking women compared to men. Recent research showed a significant association between no cognitive function recovery and female gender in recovering AUD patients.

Age has been analyzed in multiple studies on neurocognitive recovery; however, the results show an inconsistent pattern, with some studies finding a negative association and others finding none. These findings may partially cohere with the relatively low and evenly distributed age of patients in the studies (mostly between 30 and 60 years). The interaction of age with alcohol is complex, as neurocognitive recovery can be modulated by age at exposure, aging following alcohol toxicity or thiamine deficiency, and aging during chronic alcohol use.

Finally, the findings of this review indicate that most of these factors are understudied. Studies on the influence of polysubstance use, the number of previous detoxifications, positive family history, sex, depression, ASPD, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion on neurocognitive function recovery during abstinence are limited and require further research. It is also noted that AUD frequently co-occurs with other psychiatric disorders, such as depression or personality disorder, as observed in some included studies. This "dual disorder" is associated with a poorer prognosis and may be accompanied by distinct neuropsychological characteristics.

Recommendations for Future (Longitudinal) Research

Based on the findings of this review, several recommendations can be made to facilitate clinically relevant scientific research and further aid in modeling neurocognitive function recovery with sustained abstinence:

  • Neurocognitive function recovery was negatively associated with smoking. Smoking status (never smoking, former smoking, and current smoking) is linked to differential effects on neurocognitive recovery and should be included in future research.

  • There is sufficient evidence for the lack of an association between self-reported "quantities used" and neurocognitive function recovery during abstinence. Episodic memory deficits in AUD patients might obscure self-reported findings regarding past alcohol use. Therefore, careful consideration of self-report tools for measuring prior alcohol consumption and their purpose in neurocognitive recovery research is recommended.

  • Most studies (25/31) in this review started initial assessments within two weeks of abstinence. Given the possible negative effects of withdrawal on neurocognitive function, it is recommended that neurocognitive function be assessed after at least two weeks, or preferably six weeks, of abstinence.

  • Findings from this review indicate that most factors are understudied, with scarce evidence suggesting the need for follow-up research. Associations of neurocognitive recovery with age, gender, polysubstance use, the number of previous detoxifications, blood values, medical conditions, depression, and ASPD (also studied as dual disorders) should be investigated in well-controlled cross-sectional, or preferably longitudinal, designs that account for abstinence duration.

  • Social cognition, or the recovery of social cognitive function, is an understudied neurocognitive domain that requires further research.

Limitations

This review has several limitations. Firstly, methodological issues must be considered when interpreting the findings. The predictive value or association of a factor is determined within the context of a specific model. Therefore, not finding an association or effect means there is no effect within the model used. Studies in this review show considerable differences in the number of variables included in their analyses. While well-controlled, cross-sectional studies that include multiple relevant variables associated with neurocognitive functioning in abstinent AUD patients also contribute to the understanding of neurocognitive recovery, they were not included in this review. Secondly, data were not pooled for meta-analysis due to the unavailability of all necessary data from the included studies. Thirdly, the instruments used to measure neurocognitive function across these studies are diverse and vary in validity and reliability. Additionally, there is diversity in how studies account for potential learning effects associated with the instruments, ranging from merely stating a limitation to using parallel forms or calculating a reliable change index. Finally, there is a risk of publication bias by including only published studies. However, this risk is considered limited, as the factors studied were often not the primary focus of the included studies, resulting in multiple null findings (e.g., studies showing no association between quantities of alcohol used and neurocognitive recovery).

Conclusion

Despite the aforementioned limitations, this is, to the best of knowledge, the first review to systematically map factors that may influence neurocognitive function recovery in abstinent AUD patients. The clearest patterns from the evidence collected indicate a predominantly negative influence of smoking on neurocognitive function recovery, and associations between changes in volumes of various brain areas (hippocampal, ventricular, and total brain volume) and neurocognitive function recovery. There is sufficient evidence suggesting no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, or between neurocognitive recovery and educational attainment.

Future research on several factors is indicated because they have been sparsely investigated using a longitudinal design (polysubstance use, the number of previous detoxifications, positive family history, gender, depression, ASPD, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion) and/or show conflicting findings (age). Longitudinal designs are preferred, with multiple assessment periods, beginning at least two weeks after abstinence to account for potential interference from withdrawal symptoms on neurocognitive performance. Findings from such studies may help resolve the conflicting results on neurocognitive function recovery and expand the understanding of this process and its extent in the context of AUD. Ultimately, this will aid in creating a clinical profile to identify patients at risk of slower or limited recovery and to improve personalized care.

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Abstract

Objective: Studies have reported inconsistent results regarding the extent to which neurocognitive recovery occurs in abstinent patients with alcohol use disorder (AUD). In addition to abstinence, other factors may have influenced this process and contributed to the inconsistencies. This review examines the factors investigated in this regard and describes the possible influence of each factor based on the evidence collected.

Methodology: PubMed was systematically searched for articles published between January 2000 and July 2023. Longitudinal humane studies investigating neurocognitive recovery in abstinent adult AUD patients were included. Studies with a cross-sectional design were excluded, as were studies that did not classify AUD according to the DSM-IV or 5 criteria, only examined binge use, did not report neuropsychological outcomes or duration of abstinence, or where neurological disorders were present.

Results: Sixteen categories of factors were distinguished from 31 full-text articles. Consistent patterns were found, indicating an association between neurocognitive recovery and the "smoking" and 'brain volume" factors. Consistent patterns were also found indicating that there is no relationship with "quantities of alcohol used" and "education level." A similar consistent pattern was also found for "polysubstance use", "gender" and "verbal reading", but the number of studies is considered limited. The association with "age" is studied frequently but with inconsistent findings. The remaining eight factors were regarded as understudied.

Conclusion: The clearest patterns emerging from the evidence are a predominantly negative influence of smoking on neurocognitive recovery, associations between changes in brain area volume and neurocognitive recovery, and no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, nor with educational attainment. Future research on the understudied factors and factors with inconsistent evidence is needed, preferably through longitudinal designs with multiple assessment periods starting after at least two weeks of abstinence.

Introduction

Many individuals seeking treatment for an alcohol use disorder (AUD) commonly experience impaired neurocognitive function. Alcohol intoxication often leads to a loss of control and increases the likelihood of harmful behaviors, making it difficult to maintain sobriety. Furthermore, consistently heavy alcohol consumption can result in long-lasting cognitive deficits. Standard therapies, such as cognitive behavioral therapy or motivational interviewing, depend on the individual's cognitive abilities. Therefore, cognitive impairments can hinder treatment success and contribute to higher dropout rates.

Stopping alcohol use can lead to some recovery of neurocognitive function. However, research findings on how much neurocognitive recovery occurs have been inconsistent. This inconsistency may be due to two main issues in past studies.

First, most studies on neurocognitive recovery in individuals with AUD who have stopped drinking have used a cross-sectional design. While these studies offer some insight into cognitive recovery, they only capture a single point in time. This makes it difficult to reliably detect changes in an individual's cognitive function over a period of abstinence. For this reason, longitudinal studies, which follow individuals over time, are necessary to better understand neurocognitive recovery. However, following individuals with AUD over time and collecting the necessary data for such studies is challenging, as these participants often have lower adherence and struggle to maintain sobriety.

A second issue contributing to these inconsistent findings is a lack of understanding about factors, other than abstinence, that influence the course of neurocognitive recovery. Commonly mentioned factors include the number of previous medical detoxifications, biological elements like liver complications and thiamine deficiencies, polysubstance use, age, smoking, a family history of alcohol dependence, and personal history of alcohol use (e.g., total lifetime alcohol consumed, recent consumption, and duration of AUD). While these factors are often discussed as potential contributors to the variability in neurocognitive recovery, they have not received enough attention in observational research. Additionally, studies do not always provide suitable data or use validated methods to measure these factors.

This problem was highlighted by two separate meta-analyses on neurocognitive recovery in abstinent AUD patients. Insufficient detail about influencing factors or unreliable data limited the analysis of these variables, leading to conflicting conclusions. One author concluded that cognitive dysfunction improves after one year of sobriety, while other findings suggested persistent cognitive impairments across various periods of abstinence, even after one year. Longitudinal research is therefore essential to enhance understanding of neurocognitive recovery in individuals with AUD who are abstinent. Understanding the factors that influence this process can help in designing effective longitudinal studies and making this challenging research more feasible.

This review aimed to address two primary questions: (a) Which factors are investigated in research on neurocognitive recovery in abstinent AUD patients, and (b) what is the influence of these factors on neurocognitive recovery during alcohol abstinence? Additionally, the clinical relevance and practical application of current knowledge about these factors are discussed, considering their potential importance for future research on neurocognitive recovery in abstinent AUD patients.

Method

This scoping review sought to answer the questions outlined previously, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The primary outcome measure for this review was the change in neurocognitive function, assessed using neuropsychological instruments.

To identify relevant articles, a literature search was conducted in PubMed using specific search terms related to alcohol, recovery, abstinence, and various cognitive and neuroimaging functions. The search was limited to human studies. During the initial screening, two reviewers selected articles based on their titles or abstracts. Only English-language manuscripts published in peer-reviewed journals were included to ensure methodological soundness. The review included longitudinal studies investigating neuropsychological or neurocognitive function in adult abstinent patients (18 years or older) diagnosed with alcohol dependency according to DSM-IV (TR) or alcohol use disorder according to DSM-5 criteria. Relevant references from included reviews were also screened for additional papers. Studies focusing only on alcohol abuse (DSM-IV), binge drinking, or heavy episodic drinking were excluded, as were cross-sectional studies, because this review specifically aimed to understand factors associated with cognitive recovery over time in abstinent AUD patients. Studies were also excluded if participants' AUD classification was missing, if no neuropsychological instruments were used, if the duration of abstinence was not described, or if patients had an alcohol-related neurological disease such as Korsakoff syndrome. The search included articles published between January 2000 and July 2023, consistent with the inclusion of studies after the emergence of contemporary neuroscientific addiction models. Any uncertainties regarding article inclusion were resolved through discussion and consensus between the two reviewers. The remaining articles were then used for data extraction.

For each selected study, relevant data from the results and discussion sections were extracted using a standardized coding form. This form captured information such as author, publication year, study design, number of participants and controls, neuropsychological measures used, and significant or non-significant predictors of neuropsychological outcomes. The quality, validity, and clinical utility of each included article were rated by two independent reviewers using the Oxford Classification for Evidence-Based Medicine (OCEBM Levels of Evidence Working Group) on a scale from 1 (very strong) to 5 (weak). The studies were considered prognostic for the purpose of this review. The effects on neuropsychological outcome measures were categorized under the most appropriate neuropsychological domain after a consensus meeting with both reviewers, largely following an established classification system. It is important to acknowledge that there can be overlap between various neurocognitive domains, and specific tasks may not exclusively measure a single function. All predictors identified from the full-text articles were sorted into 16 categories using a coding form. Reviewers independently placed extracted variables into the most suitable category, resolving any doubts through consultation and consensus. These 16 categories were then regrouped into five broader domains: drinking-related factors, demographic factors, psychiatric factors, premorbid neurocognitive function, and medical factors, again with agreement from both reviewers. The observed effects and associations for each factor, along with their direction, were then summarized and discussed narratively. Findings were considered statistically significant if the alpha level was less than or equal to 0.05.

Results

The initial search yielded 2179 articles, including 15 reviews. After screening, 58 articles remained for closer inspection. The main goal at this stage was to include studies that explicitly explored the link between abstinence duration, neurocognitive recovery, and other relevant factors. During this final selection process, several studies were excluded for various reasons, such as lacking longitudinal analysis or proper AUD classification, not using neuropsychological instruments, or not reporting abstinence duration. Ultimately, 31 articles were included for data extraction and analysis.

Most of the 31 included studies (25 out of 31) began cognitive assessments within two weeks of admission. These assessments used neuropsychological tasks covering domains such as executive function, memory and learning, attention, processing speed, spatial processing, intelligence, and social cognition. Abstinence from alcohol was confirmed through biomarkers (in 13 studies, sometimes combined with self-report), by self-report only (in 5 studies), or the verification method was not specified (in 13 studies). The quality ratings for studies in this review ranged from 2 to 4.

Regarding drinking-related factors, the evidence on smoking showed a largely consistent negative association with neurocognitive recovery. Six of eight studies found that chronic smoking negatively affected neurocognitive recovery across various domains (processing speed, learning and memory, spatial processing, executive function, and fine motor skills) over abstinence periods ranging from five weeks to nine months. Greater current smoking severity was linked to less cognitive improvement, and never-smoking AUD patients showed the best recovery. Older age also interacted with smoking status, leading to poorer performance. Two studies, however, found no association between smoking and neurocognitive recovery. The evidence regarding quantities of alcohol used showed a mostly consistent pattern of no association between past alcohol consumption levels (e.g., average drinks per month, lifetime years of drinking, duration of dependence) and recovery across several neurocognitive domains. Eleven of thirteen studies reported no such link, even with abstinence durations up to 48 months. Only two studies found an association between quantified alcohol use and recovery in certain domains. For polysubstance use, the number of studies was limited, but they generally showed no association between single or polysubstance use (beyond alcohol) and recovery in executive function, learning and memory, and processing speed, over abstinence periods of one to eight months. One study on polysubstance use disorder patients (including AUD) noted cognitive improvements, but without a direct comparison to AUD-only patients. The evidence for an association between the number of previous detoxifications and neurocognitive recovery was limited and inconsistent. One study found that fewer medical detoxifications were linked to better performance in executive function, learning, and memory after three to six months of abstinence, while two other studies found no such association. For positive family history of alcohol dependence, limited evidence suggested a negative association with recovery of executive function in three of five studies, but no association with social cognitive function in two studies.

In terms of demographic factors, the association between age and neurocognitive recovery was inconsistent. Four of ten studies found that increasing age was negatively associated with recovery of executive function, learning and memory, and speed after six to fifteen months of abstinence. However, six studies found no such association. Gender showed no association with neurocognitive recovery in the three studies that examined it, suggesting no effects on executive function, attention, or social cognitive function. The evidence for this factor is limited but consistent. Education level largely showed no association with neurocognitive recovery. Five of six studies found no link between educational attainment and performance or recovery in various neurocognitive domains. One study, however, found that higher education predicted better verbal ability recovery.

Regarding psychiatric factors, the evidence on depression and neurocognitive recovery was insufficient and inconsistent. Three studies found no association between depressive symptoms and recovery of executive function, learning and memory, or processing speed, while two others found no association with social cognitive function. However, two studies reported a negative association between depressive symptoms and executive function recovery. One study found that co-occurring bipolar disorder and AUD might lead to more severe cognitive dysfunction and less favorable recovery. For antisocial personality disorder (ASPD), the evidence was limited; one study found an association with executive function at baseline but not with changes in neurocognitive function.

For premorbid neurocognitive function, assessed by a verbal reading task, four of five studies found no association with the recovery of executive function, learning and memory, processing speed, and spatial processing after six to 48 months of abstinence. One study did find an association between verbal reading task results and improvement in executive function, processing speed, and spatial processing after five weeks of abstinence. Neurocognitive performance at baseline was examined in one study, which found that executive function at baseline predicted executive function after 15 months of abstinence.

Under medical factors, the evidence for an association between blood values and neurocognitive recovery was limited. Two studies found improvements in learning, memory, and attention to be linked to specific blood values (N-acetylaspartate values), while a third study found abnormal baseline medical test results predicted less recovery in executive function. The evidence for an association between medical conditions and neurocognitive recovery was inconsistent and limited. Two of three studies found no association between hypertension and hepatitis C with neurocognitive recovery, while one study found that fewer medical conditions at baseline contributed to verbal ability recovery. Most studies (five of six) found a consistent pattern of association between brain volumes and recovery of memory, learning, and processing speed during abstinence periods. For instance, increasing hippocampal volumes correlated with visuospatial memory improvements in non-smoking AUD patients, and increasing volumes in other brain regions were linked to improved processing speed. Smoking status was found to influence this relationship. Finally, one study found no correlation between perfusion changes in frontal and parietal gray matter and changes in neurocognitive performance across various domains after one month of abstinence.

Discussion

This review describes the scientific evidence regarding factors associated with neurocognitive recovery in abstinent AUD patients. This section will discuss the most consistent patterns identified, relate them to existing literature, and highlight research gaps.

First, accumulated evidence indicates a largely consistent negative association between smoking and neurocognitive recovery in domains like processing speed, learning and memory, spatial processing, executive function, and fine motor skills, for up to nine months of alcohol abstinence. The interplay between nicotine and alcohol on neurocognitive function is significant due to its high prevalence among AUD patients, leading to synergistic effects and increased health risks. Future studies on neurocognitive recovery in AUD patients should account for smoking status, differentiating between active smokers, former smokers, and individuals who have never smoked.

Second, increasing brain volumes during alcohol abstinence within one year are associated with improvements in memory, learning, and processing speed. Some evidence also suggests an association between decreasing lateral ventricular volume and memory improvement. During sustained abstinence, ventricular volumes tend to decrease, while structures such as the temporal, insular, anterior cingulate cortices, amygdala, thalamus, hippocampus, brainstem, and cerebellar cortex show volume increases. Understanding the reversibility of structural and functional changes caused by alcohol use is crucial. This review's findings further support the link between neurocognitive recovery and changes in brain volumes. Additionally, the included studies suggest that other factors, such as smoking status or specific genetic factors, may influence this relationship.

Two other well-studied factors, the amount of alcohol used and education level, consistently show little or no association with neurocognitive recovery. First, factors quantifying past alcohol consumption were not, or only rarely, associated with neurocognitive recovery in various domains after abstinence periods of up to four years. This finding, while somewhat unexpected given alcohol's known impact on brain structure and function, may stem from methodological issues. Retrospective self-report measures of past alcohol use, commonly used in these studies, can be compromised by episodic memory deficits common in AUD, which affect the ability to accurately recall past information. It is also possible that other factors linked to heavy alcohol use, such as thiamine deficiency, are the primary drivers of severe neurocognitive impairments.

Second, substantial evidence suggests that educational attainment is not associated with neurocognitive recovery across multiple domains. This finding appears to contradict the strong established link between education level and cognitive performance, as education is often believed to reflect cognitive reserve and influence recovery. However, such associations are primarily from cross-sectional studies, which capture a single point in time rather than changes in cognitive function over multiple assessments, as observed in recovery. Consistent with these findings, other studies on cognitive reserve have also reported no significant relationship between educational attainment and changes in cognitive performance or cognitive reserve.

Evidence regarding the association of "polysubstance use," "premorbid neurocognitive function," or "gender" with neurocognitive recovery is considered insufficient. In most cases, the patterns consistently show no evidence of an association. Polysubstance use has been studied to a limited extent; only four studies were included, with two having lower evidence ratings due to small sample sizes and lack of control groups. Furthermore, two studies that found no effect did not include smoking status in their analyses, which could obscure the influence of smoking on neurocognitive recovery. Given the limited longitudinal studies, the assumed impact of smoking, and specific neurobiological changes associated with polysubstance use, more research is needed in this area, which has historically been overlooked.

Premorbid neurocognitive function, as assessed by verbal reading tasks, could not be definitively linked to neurocognitive recovery. While verbal reading tasks are often used to estimate premorbid intelligence, their ability to predict specific neurocognitive function or recovery of neurocognitive function is less clear, with limited research on this relationship outside of intelligence itself. Factors such as lower verbal ability potentially preceding heavy alcohol use or being a result of both lower premorbid intelligence and more intellectual decline also need consideration.

Gender, a third factor, showed no association with neurocognitive recovery in the limited studies available. The strength and generalizability of this evidence are limited because most included studies primarily consisted of men, which may bias results. While general literature suggests men and women have similar overall cognitive capacities, it remains uncertain whether this applies to neurocognitive recovery in AUD patients due to insufficient research. Neurobiological studies suggest gender-specific neural recovery and greater neurotoxic effects of alcohol in women who binge drink compared to men. More studies are needed to clarify this.

Age has been analyzed in multiple studies on neurocognitive recovery, but results are inconsistent, with some finding a negative association and others no association. This inconsistency might relate to the relatively narrow and evenly distributed age range of patients (mostly 30 to 60 years old) in these studies. The interaction of age with alcohol is complex, as recovery can be influenced by age at exposure, aging following alcohol toxicity or thiamine deficiency, and aging during chronic alcohol use.

Finally, this review indicates that most of these factors remain understudied. Research on the influence of polysubstance use, the number of previous detoxifications, positive family history, gender, depression, antisocial personality disorder, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion on neurocognitive recovery during abstinence is limited and requires further investigation. It is also important to note that AUD frequently co-occurs with other psychiatric disorders like depression or personality disorder. This "dual disorder" is associated with poorer prognosis and may involve distinct neuropsychological characteristics.

Recommendations for Future Research

Based on the findings of this review, several recommendations can be made to facilitate clinically relevant scientific research and improve the understanding of neurocognitive recovery during sustained abstinence:

  • Neurocognitive recovery was negatively associated with smoking. Future research should include smoking status (never smoking, former smoking, and active smoking) as it is linked to different effects on neurocognitive recovery.

  • There is sufficient evidence that the self-reported "quantities used" of alcohol are not associated with neurocognitive recovery during abstinence. Because episodic memory deficits might affect the accuracy of self-reported past alcohol use in AUD patients, researchers should carefully consider the use and purpose of such self-report tools in neurocognitive recovery research.

  • Most studies in this review started initial cognitive assessments within two weeks of abstinence. Given the potential negative effects of withdrawal on neurocognitive function, it is recommended that neurocognitive function be assessed after at least two weeks of abstinence, with some studies suggesting after six weeks.

  • Findings from this review indicate that most factors are understudied, yet limited evidence suggests the need for follow-up research. Therefore, associations of neurocognitive recovery with age, gender, polysubstance use, the number of previous detoxifications, blood values, medical conditions, depression, and antisocial personality disorder (including as dual disorders) should be investigated in well-controlled cross-sectional, or preferably longitudinal, studies that account for abstinence duration.

  • Social cognition, or the recovery of social cognitive function, is an understudied neurocognitive domain that requires further research.

Limitations

This review has several limitations. First, methodological issues must be considered when interpreting the findings. Determining a factor's predictive value or association always occurs within the context of the model used. Therefore, not finding an association or effect means there was no effect within that specific model. Studies in this review varied considerably in the number of variables included in their analyses. While well-controlled, cross-sectional studies that include multiple relevant variables associated with neurocognitive functioning in abstinent AUD also contribute to understanding neurocognitive recovery, they were not included in this review. Second, data from the included studies were not pooled for meta-analysis due to the unavailability of all necessary data. Third, the instruments used to measure neurocognitive function across studies were diverse and varied in validity and reliability. Additionally, studies differed in how they addressed potential learning effects associated with these instruments, ranging from simply acknowledging the limitation to using parallel forms or calculating reliable change indices. Finally, there is a risk of publication bias by including only published studies. However, this risk is considered limited because the factors studied were often not the primary focus of the included research, leading to multiple null findings (e.g., several studies showing no association between alcohol quantities used and neurocognitive recovery).

Conclusion

Despite the limitations mentioned, this is the first review, to current knowledge, to systematically map the factors that may influence neurocognitive recovery in abstinent AUD patients. The clearest patterns from the collected evidence indicate a predominantly negative influence of smoking on neurocognitive recovery and associations between changes in the volumes of various brain areas (hippocampal, ventricular, and total brain volume) and neurocognitive recovery. There is sufficient evidence to suggest no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, or between neurocognitive recovery and educational attainment.

Future research is indicated for several factors that have been sparsely investigated using a longitudinal design (polysubstance use, number of previous detoxifications, positive family history, gender, depression, antisocial personality disorder, verbal reading, blood values, baseline neurocognitive function, medical conditions, and perfusion) or show conflicting findings (age). Longitudinal designs are preferred, with multiple assessment periods, beginning at least two weeks into abstinence to avoid interference from potential withdrawal symptoms.

Findings from these future studies may help resolve existing conflicting results on neurocognitive recovery and expand understanding of this process and its extent in the context of AUD. Ultimately, this knowledge can help create a clinical profile to identify patients at risk of slower or limited recovery and improve personalized care.

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Abstract

Objective: Studies have reported inconsistent results regarding the extent to which neurocognitive recovery occurs in abstinent patients with alcohol use disorder (AUD). In addition to abstinence, other factors may have influenced this process and contributed to the inconsistencies. This review examines the factors investigated in this regard and describes the possible influence of each factor based on the evidence collected.

Methodology: PubMed was systematically searched for articles published between January 2000 and July 2023. Longitudinal humane studies investigating neurocognitive recovery in abstinent adult AUD patients were included. Studies with a cross-sectional design were excluded, as were studies that did not classify AUD according to the DSM-IV or 5 criteria, only examined binge use, did not report neuropsychological outcomes or duration of abstinence, or where neurological disorders were present.

Results: Sixteen categories of factors were distinguished from 31 full-text articles. Consistent patterns were found, indicating an association between neurocognitive recovery and the "smoking" and 'brain volume" factors. Consistent patterns were also found indicating that there is no relationship with "quantities of alcohol used" and "education level." A similar consistent pattern was also found for "polysubstance use", "gender" and "verbal reading", but the number of studies is considered limited. The association with "age" is studied frequently but with inconsistent findings. The remaining eight factors were regarded as understudied.

Conclusion: The clearest patterns emerging from the evidence are a predominantly negative influence of smoking on neurocognitive recovery, associations between changes in brain area volume and neurocognitive recovery, and no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, nor with educational attainment. Future research on the understudied factors and factors with inconsistent evidence is needed, preferably through longitudinal designs with multiple assessment periods starting after at least two weeks of abstinence.

Introduction

Problems with brain function are common in adults seeking treatment for alcohol use disorder (AUD). When a person is intoxicated by alcohol, they can lose control and engage in harmful behaviors, which makes it harder to stay sober. Long-term, heavy alcohol use can also lead to lasting brain function problems. Since common treatments like cognitive behavioral therapy and motivational interviewing rely on clear thinking, these brain impairments can hinder treatment success and cause more people to drop out.

Stopping alcohol use can lead to some recovery of brain function. However, studies have shown mixed results on how much recovery occurs. This might be due to two main reasons. First, most studies looked at brain function at only one point in time, which makes it hard to see changes over a period of sobriety. Longitudinal studies, which follow people over time, are needed to better understand this recovery. However, it is challenging to conduct these studies because people with AUD often have difficulty staying sober or continuing in the study.

A second issue is that not enough is known about other factors, besides simply stopping alcohol, that influence brain recovery. These factors often include the number of past medical detoxifications, biological issues like liver problems or vitamin deficiencies, use of other drugs, age, smoking, family history of alcohol dependence, and details about past alcohol use. Although these factors are often discussed, they have not been studied enough in research, or the data collected has not been suitable. This review aimed to identify which factors are studied in research on brain function recovery in adults with AUD who are sober, and how these factors influence that recovery. The clinical importance of this knowledge for future research will also be discussed.

Methodology

This review followed specific guidelines to answer the stated questions. The main outcome measured was any change in brain function, assessed using specialized psychological tests.

Search Strategy

Articles were found through a literature search using terms related to alcohol, recovery, abstinence, and various brain functions, focusing on human studies.

Article Selection

Two reviewers initially screened articles by title or abstract. Only English-language articles from peer-reviewed journals were included to ensure quality. Studies had to be longitudinal, meaning they followed participants over time, and focus on adult patients (age 18 or older) with alcohol dependence or AUD who were abstinent. Reviews were also checked for additional relevant papers. Studies on alcohol abuse only, or those that did not involve follow-up over time, were excluded. Also excluded were studies missing a clear diagnosis of alcohol use disorder, not using specific brain function tests, not describing the length of abstinence, or including patients with severe alcohol-related brain diseases like Korsakoff syndrome. The search included articles published between January 2000 and July 2023. When there was doubt about including a study, both reviewers discussed it until they reached an agreement.

Data Extraction

Relevant information was taken from each included study using a special form. This included details like the author, publication year, study design, number of participants, and whether any factors predicted changes in brain function. The quality of each study was also rated using a standard system, from very strong (1) to weak (5). Studies in this review were rated from 2 to 4. The effects found on brain function were grouped into appropriate categories, such as executive function or memory, after discussion between the reviewers. All factors examined in the studies were organized into 16 categories, which were then grouped into five main areas: drinking-related factors, demographic factors, psychiatric factors, premorbid brain function, and medical factors. The findings for each factor, including their direction (positive or negative effect), were described. Findings were considered significant if their likelihood of occurring by chance was 5% or less.

Results

Out of 2179 articles initially found, 31 were selected for this review. Most of these studies (25 out of 31) began testing brain function within two weeks after participants were admitted, covering areas such as executive function, memory, attention, processing speed, and intelligence. Abstinence from alcohol was confirmed using biological tests (13 studies), self-report only (5 studies), or the method of verification was not stated (13 studies).

Summary of Factors

Most studies indicated an association or effect between certain factors and brain function recovery.

Drinking Related Factors

Smoking. Eight studies looked at smoking and brain recovery. Six found that chronic smoking negatively affected recovery, influencing processing speed, learning, memory, spatial processing, executive function, and fine motor skills. Higher smoking severity led to less improvement. People who never smoked or had quit smoking showed better recovery than active smokers. Two studies found no such association. Overall, there is a consistent pattern suggesting smoking negatively impacts brain recovery during abstinence.

Quantities of Alcohol Used. Thirteen studies examined the amount of alcohol previously consumed (e.g., lifetime use, duration of dependence). Eleven of these studies found no link between these measures and recovery in various brain functions, even after up to 48 months of abstinence. Two studies did find an association, specifically with learning, memory, and executive function, after three to six months of abstinence. In general, evidence largely shows no connection between past alcohol quantities and brain function recovery.

Polysubstance Use. Four studies explored the link between using multiple substances and brain recovery. One study showed improvements in general intelligence and executive function after four months of abstinence in people with polysubstance use disorder (including AUD). However, no direct comparison was made with AUD-only patients. Three studies found no association between using other substances (besides alcohol) and recovery in executive function, learning, memory, or processing speed. The number of studies on this topic is limited, but they generally suggest no association.

Number of Previous Detoxifications. Three studies looked at how the number of past detoxifications affected brain recovery. One study found that people with fewer detoxifications performed better on executive function and memory tasks after three to six months of abstinence. Two other studies found no such link. The evidence on this factor is limited and inconsistent.

Positive Family History. Five studies examined if a family history of alcohol problems affected brain recovery. Three studies found a negative association with executive function after six weeks to 15 months of abstinence. Two studies found no link with social cognitive function. Overall, the evidence is limited but suggests a negative link with executive function.

Demographic Factors

Age. Four out of ten studies found that increasing age was linked to less recovery in executive function, learning, memory, and processing speed. Six studies found no association between age and recovery in these or other brain functions. Results are inconsistent regarding the link between age and brain recovery.

Gender. Three studies examined gender and brain recovery and found no effects on executive function, attention, or social cognitive function. Evidence is limited but consistently shows no association between gender and brain recovery.

Education. Five of six studies found no link between education level and brain recovery in various functions. One study found that higher education predicted better recovery of verbal abilities. Generally, evidence shows education level is not associated with brain function recovery in this context.

Psychiatric Factors

Depression. Seven studies looked at depressive symptoms and brain recovery. Three found no association with executive function, learning, or processing speed. Two found no association with social cognitive function. Two studies found a negative association with executive function. One study found that people with both AUD and Bipolar Disorder might have more severe problems and less recovery. Overall, evidence on depression and brain recovery is insufficient and inconsistent.

Antisocial Personality Disorder. Two studies examined this disorder and brain recovery. One did not clearly state if the disorder was linked to lack of abstinence, and the other only found it linked to executive function at the start of the study, not to changes over time. Evidence is limited.

Premorbid Neurocognitive Function

Verbal Reading Task. Four out of five studies found no link between performance on a verbal reading task (often used to estimate prior intelligence) and recovery of executive function, learning, memory, processing speed, or spatial processing. One study did find a link, but only after five weeks of abstinence. Most studies show no association, indicating a possible short-term relationship.

Neurocognitive Performance at Baseline. One study found that a person's executive function at the start of the study predicted their executive function after 15 months of abstinence.

Medical

Blood Values. Three studies looked at blood values and brain recovery. Two found that certain blood values were linked to improvements in learning, memory, and attention. A third study found that abnormal baseline medical test results were linked to less recovery in executive function. Evidence is limited.

Medical Conditions. Three studies examined medical conditions. Two found no link between conditions like high blood pressure or Hepatitis C and recovery in various brain functions. One study found that fewer medical conditions at the start were linked to better recovery of verbal ability. Evidence is inconsistent and limited.

Brain Volumes. Five of six studies found an association between changes in brain volumes and recovery of memory, learning, and processing speed. For example, increased hippocampal volume was linked to memory improvements. Changes in brain volume can be influenced by factors like smoking. Most studies consistently show an association between changes in brain volume during abstinence and recovery of brain function.

Perfusion. One study found no link between changes in blood flow to the brain and changes in executive function, learning, memory, or processing speed.

Discussion

This review identifies factors linked to brain function recovery in adults with alcohol use disorder who are sober.

The clearest finding is that smoking has a largely consistent negative impact on brain function recovery, affecting areas like processing speed, learning, and executive function. This is important because many people with AUD also smoke, and the combination can worsen health risks. Future studies should consider smoking status. Second, an increase in brain volumes during abstinence is linked to improvements in memory, learning, and processing speed. This suggests that the brain can recover structural changes caused by alcohol, and this process can be influenced by factors like smoking.

Interestingly, two factors often thought to be important—the amount of alcohol previously consumed and education level—consistently showed little to no association with brain recovery in this review. The lack of association with past alcohol use might be due to problems with people accurately remembering and reporting their past consumption, especially given that AUD can affect memory. Similarly, while education is generally linked to cognitive performance, these findings from longitudinal studies suggest it might not predict recovery of function over time, which differs from what cross-sectional studies show.

Many other factors, such as the use of multiple substances, past brain function levels, and gender, have not been studied enough. For example, polysubstance use has been largely overlooked, and more research is needed, especially considering the known impact of smoking. Similarly, although gender differences in brain function are recognized, the limited studies in this review did not show a clear impact on recovery, perhaps because most study participants were men. Age also showed inconsistent results, possibly because most patients in the studies were middle-aged, and the interaction between age and alcohol is complex. Many factors, including past detoxifications, family history, depression, other personality disorders, blood values, and medical conditions, need more research because existing studies are limited or show conflicting results.

Recommendations for Future Research

Based on these findings, several recommendations can help future research on brain recovery in AUD patients. Since smoking negatively affects recovery, future studies should always account for smoking status. Self-reported past alcohol use might not be reliable for predicting recovery due to memory problems in AUD patients, so researchers should be cautious when using such data. Initial brain function assessments should ideally occur at least two weeks after abstinence begins, to avoid the confounding effects of withdrawal symptoms. Many factors, including age, gender, polysubstance use, past detoxifications, medical conditions, depression, and antisocial personality disorder, need more well-controlled longitudinal studies that consider the length of abstinence. Additionally, the recovery of social cognitive function, a key brain domain, needs more dedicated research.

Limitations

This review has limitations. The way a factor predicts recovery depends on the study model, so a lack of association does not mean there is no effect outside that specific model. This review did not combine data for a meta-analysis because not all necessary data were available from the included studies. The tools used to measure brain function varied across studies, and not all studies fully accounted for learning effects that might occur with repeated testing. Finally, there is a risk of publication bias, where studies with significant findings are more likely to be published. However, this risk is considered limited here, as many included studies reported no association for the factors examined.

Conclusion

This review systematically explored factors that might influence brain function recovery in adults with alcohol use disorder who are abstinent. The clearest findings show a negative impact of smoking on recovery and a positive association between increasing brain volumes and recovery. There is sufficient evidence that the self-reported amount of alcohol previously consumed and education level are not linked to brain function recovery. Many factors, including polysubstance use, the number of previous detoxifications, family history, gender, depression, antisocial personality disorder, verbal reading ability, blood values, baseline brain function, medical conditions, and brain perfusion, require more research, especially using longitudinal studies with multiple assessments. These studies should preferably start at least two weeks into abstinence to avoid interference from withdrawal symptoms. Understanding these factors can help resolve conflicting research findings, provide a clearer picture of brain recovery in AUD, and ultimately lead to better, more personalized care for patients at risk of slower or limited recovery.

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Abstract

Objective: Studies have reported inconsistent results regarding the extent to which neurocognitive recovery occurs in abstinent patients with alcohol use disorder (AUD). In addition to abstinence, other factors may have influenced this process and contributed to the inconsistencies. This review examines the factors investigated in this regard and describes the possible influence of each factor based on the evidence collected.

Methodology: PubMed was systematically searched for articles published between January 2000 and July 2023. Longitudinal humane studies investigating neurocognitive recovery in abstinent adult AUD patients were included. Studies with a cross-sectional design were excluded, as were studies that did not classify AUD according to the DSM-IV or 5 criteria, only examined binge use, did not report neuropsychological outcomes or duration of abstinence, or where neurological disorders were present.

Results: Sixteen categories of factors were distinguished from 31 full-text articles. Consistent patterns were found, indicating an association between neurocognitive recovery and the "smoking" and 'brain volume" factors. Consistent patterns were also found indicating that there is no relationship with "quantities of alcohol used" and "education level." A similar consistent pattern was also found for "polysubstance use", "gender" and "verbal reading", but the number of studies is considered limited. The association with "age" is studied frequently but with inconsistent findings. The remaining eight factors were regarded as understudied.

Conclusion: The clearest patterns emerging from the evidence are a predominantly negative influence of smoking on neurocognitive recovery, associations between changes in brain area volume and neurocognitive recovery, and no association between neurocognitive recovery and the amount of alcohol consumed, as measured by self-report, nor with educational attainment. Future research on the understudied factors and factors with inconsistent evidence is needed, preferably through longitudinal designs with multiple assessment periods starting after at least two weeks of abstinence.

Introduction

Problems with brain function are common in adults who seek help for alcohol use disorder (AUD). When people are drunk, they often lose control. This can lead to bad choices and make it hard to stay sober. Drinking too much alcohol for a long time can also cause lasting brain damage. Treatments like talk therapy need people to think clearly. Brain problems make these treatments harder and can cause people to quit. Stopping alcohol can help the brain heal, at least partly. But studies do not always agree on how much the brain can heal. Two main problems might explain this.

First, most studies about brain healing in people who stopped drinking looked at things at only one point in time. These studies show some things about brain healing, but they are like a single photo. They do not show how a person's brain changes over time while they stay sober. So, studies that follow people over time are needed to better understand how the brain heals. But it is hard to follow people over time and gather information. People with AUD often do not stick with studies or stay sober for long periods.

Second, it is not clear what other things, besides stopping alcohol, affect brain healing. People often talk about how many times someone went through detox, health problems like liver issues or lack of vitamins, using other drugs, age, smoking, family history of alcohol problems, and how much and how long someone drank. Even though these things are often talked about as affecting brain healing, studies have not looked at them enough. Also, studies do not always collect the right information or use good ways to measure these things.

Two big reviews of many studies on brain healing in people who stopped drinking showed this. When there is not enough detail or the information is not good, it is hard to study these factors. This leads to different findings. One review said brain problems get better after one year of being sober, but another said brain problems can last even after a year.

In short, studies that follow people over time are needed to better understand how the brain heals in people who stopped drinking. Knowing what affects this healing can help create better studies and make it easier to do this hard research. This review wanted to find out: (a) What things have been studied about brain healing in people who stopped drinking alcohol? and (b) How do these things affect brain healing when someone stops drinking? It also looks at how useful this information is now and for future studies on brain healing in people who have stopped drinking.

Method

This review aimed to answer these questions by following certain rules for how to do a study like this. The main thing looked at was how brain function changed, as measured by special brain tests.

Search Strategy

To find articles, a search was done in a medical database (PubMed). Special words like "alcohol," "recovery," "brain," and "memory" were used to find the right studies. Only studies about humans were included.

Article Selection

At first, two people (JS and TK) looked at the titles and short summaries of articles to choose them. Only English articles from good scientific journals were chosen. The goal was to pick studies that used strong methods. Studies that followed adults (18 or older) who had stopped drinking and had an alcohol problem (as defined by health guides) were included. These studies looked at how their brains worked. Other studies that were already reviews were checked for more useful papers.

Studies that only looked at heavy drinking or problem drinking (not full alcohol use disorder) were left out. Studies that only looked at one point in time were also left out. This review wanted to understand how brain healing changes over time in people who stopped drinking. Lastly, some studies were not included if they did not clearly say if participants had an alcohol use disorder, if they did not use brain tests, if they did not say how long people had stopped drinking, or if people had other brain diseases caused by alcohol.

The search covered articles published from January 2000 to July 2023. This time frame was chosen because it includes newer ideas about how alcohol affects the brain. If there was a question about whether to include a study, the two reviewers read the full article and talked about it. They agreed on all articles. The rest of the articles were read fully to get information from them.

Data Extraction

Important facts were taken from each study's results. This included who wrote it, when it was published, and how the study was set up. It also noted how many people were in it, what brain tests were used, and what factors were linked to brain test results.

To rate how good each study was, two reviewers (JS and TK) gave it a score from 1 (very strong) to 5 (weak). The brain test results were put into suitable brain function groups after the reviewers agreed.

All factors found in the articles were put into groups. The reviewers (JS and TK) first found 16 categories, then regrouped them into five bigger areas: things about drinking, a person's background, mental health, how the brain worked before, and health problems. What was found about each factor was then described.

Results

From the search, 2179 articles were found, including 15 reviews. In the end, 58 articles were chosen and checked by two reviewers. The main goal at this stage was to pick studies that clearly looked at the link between how long someone stopped drinking, how their brain healed, and other factors. Some studies were not included for different reasons, such as not following people over time, not being about actual alcohol disorder, or not saying how long people stopped drinking. This left 31 articles that could be used for this review.

Summary of Factors

Out of the 31 studies, most (25) started brain tests within two weeks of people entering treatment. These tests looked at things like thinking skills, memory, attention, how fast people process information, understanding space, intelligence, and social skills. Stopping alcohol was checked in different ways: by blood tests (13 studies), by asking people (5 studies), or it was not mentioned (13 studies).

The results for each factor were reviewed. Any links found for each factor pointed in the same direction.

Drinking Related Factors

Smoking

Eight studies looked at how smoking tobacco was linked to brain healing in people who stopped drinking alcohol. Six of these studies found that long-term smoking clearly hurt brain healing, both short-term and long-term. This included how fast people think, learning, memory, understanding space, thinking skills, and small muscle movements. People who smoked more now showed less brain improvement. Those who never smoked showed the most healing, while those who used to smoke showed less healing than those who never smoked. One study also found that smoking seemed to work with how long someone stopped drinking and their age; older age led to worse brain function.

However, two studies did not find a link between long-term smoking and brain healing. One of these studies suggested that a certain gene, not smoking, affected how a part of the brain healed. Another study found no link between smoking and healing in thinking skills, memory, and how fast someone thinks.

In short, most studies agree that smoking tobacco is bad for brain healing in many areas, for different lengths of time after stopping alcohol.

Quantities of Alcohol Used

Thirteen studies looked at how much alcohol someone drank in the past and how it was linked to brain healing. They looked at things like how many drinks per month, years of drinking, how much was drunk over a lifetime, and how long someone had an alcohol problem. Eleven of these studies did not find a link between how much alcohol was used and healing in thinking skills, learning, memory, attention, how fast people think, or social skills. People had stopped drinking for as little as 1 day up to 48 months. Most studies looked at people sober for less than one year.

Two studies did find a link. They showed that how much and how long someone drank was linked to healing in learning, memory, intelligence, understanding space, and thinking skills after 3 to 6 months of being sober.

In short, most studies agree that how much alcohol someone drank in the past is not linked to how well their brain heals in many areas, after different lengths of time being sober.

Polysubstance Use

Four studies looked at how using many substances (like alcohol plus other drugs) was linked to brain healing. One study looked at people who used many substances, including alcohol. It found their overall intelligence, thinking skills, working memory, and general brain function improved after four months of not using substances. But no clear improvements were seen in understanding space or how fast they processed information. This study did not compare these people to those who only had an alcohol problem.

Three other studies found no link between using other substances (besides alcohol) and healing in thinking skills, learning, memory, or how fast people think. This was true for people sober for 1 to 8 months.

In short, there are only a few studies. They mostly show no link between using many substances and brain healing in different areas, after varying times of being sober.

Number of Previous Detoxifications

Three studies looked at how many times someone went through detox and how it was linked to their brain healing. One study divided people with AUD into groups: those who had few detoxes (1 or less) and those who had many (2 or more). The group with few detoxes did better on thinking skills, learning, and memory after 3 to 6 months of being sober. No differences were seen in the first three months.

Another study found that the number of detoxes was not a predictor for similar brain skills after 24 months of being sober. A third study found no clear link between the number of detoxes and healing of social skills after eight weeks of being sober.

In short, the proof for a link between past detoxes and brain healing is limited and not clear.

Positive Family History

Five studies looked at how having a family history of alcohol problems was linked to brain healing. Three studies found that a family history of alcohol problems was bad for healing in thinking skills after 6 to 7 weeks or 15 months of being sober. Two studies found no link between a family history of alcohol problems and healing of social skills after two months of being sober.

In short, the proof is limited. It seems a family history of alcohol problems is bad for thinking skills but has no link to social skills.

Demographic Factors

Age

Four out of ten studies found that getting older was linked to worse healing in thinking skills, learning, memory, and how fast people think, after 6 to 15 months of being sober. Six studies found no link between age and healing in thinking skills, learning, memory, attention, how fast people think, or social skills. This was true for people sober from 3 weeks to 9 months.

In short, many studies show mixed results about the link between age and brain healing.

Gender

Three studies looked at the link between gender and brain healing. They found no effects on thinking skills after 15 months of sobriety, no effects on attention after 1.5 months, or on social skills after 8 weeks. The proof is limited, but it always shows no link between gender and brain healing.

Education

Five out of six studies found no link between how much schooling someone had and their brain healing. These studies found no link to thinking skills, learning, memory, attention, how fast people think, or understanding space, for people sober from 1.5 to 15 months.

One study did find that more schooling meant better healing of speaking skills after 1.5 months of being sober. Overall, the proof mostly agrees that schooling is not linked to brain healing.

Psychiatric Factors

Depression

Seven studies looked at how feelings of sadness (depression) were linked to brain healing. Three studies found no link between these feelings and healing in thinking skills, learning, memory, or how fast people think, for people sober from 8 weeks to 48 months. Two studies found no link between sad feelings and healing of social skills after two months of being sober.

But two studies did find a bad link: sad feelings were tied to worse healing of thinking skills after 5 weeks and 15 months of sobriety. All studies looked at feelings of sadness but did not say if people had a medical diagnosis of depression.

One study looked at people with both AUD and Bipolar Disorder. It found that these people might have worse brain problems and less healing than those without AUD, even when their mood swings got better.

In short, there is not enough proof for a clear link between sad feelings and brain healing. The results are mixed. There are unclear links between sad feelings and healing in thinking skills. There's little proof of a link to learning, memory, and how fast people think. And little proof of no link to social skills.

Antisocial Personality Disorder

Two studies looked at how a certain personality disorder (ASPD) was linked to brain healing. One study did not clearly say if ASPD meant people weren't sober. In the other study, ASPD was only linked to thinking skills at the start, not to how brain function changed over time. The proof found is limited.

Premorbid Neurocognitive Function

Verbal Reading Task

Four out of five studies found no link between how well someone read words and how their brain healed. This included thinking skills, learning, memory, how fast they thought, and understanding space, for people sober from 6 to 48 months. One study said that people who finished the study often did better on tests, suggesting that their brain might have worked better from the start, which helped them improve.

However, one study found that reading task results did explain some of the improvements in thinking skills, how fast people thought, and understanding space after 5 weeks of being sober.

In short, most of the few studies show no link between reading tasks and brain healing, for people sober from 6 to 48 months. But one study did find a link after 5 weeks of sobriety, which might mean it is only true for early sobriety.

Neurocognitive Performance at Baseline

One study found that how well someone could use thinking skills at the start of the study predicted how well they would use those skills after 15 months of being sober.

Medical

Blood Values

Three studies looked at how blood test results were linked to brain healing. Two studies found that better learning, memory, and attention were linked to certain blood values after 1.5 months in treatment.

A third study found that bad results from blood and urine tests at the start meant less healing in thinking skills after 15 months of sobriety.

In short, the proof for a link between blood values and brain healing is limited.

Medical Conditions

Three studies looked at how other health problems were linked to brain healing. Two studies found no link between conditions like high blood pressure or hepatitis C and healing in thinking skills, learning, memory, how fast people think, attention, or understanding space, for people sober for 4 to 8 months.

One study found that having fewer health problems at the start helped with healing of speaking skills after 1.5 months of sobriety.

In short, the proof for a link between health problems and brain healing is mixed and limited.

Brain Volumes

Five out of six studies found a link between brain size and healing in memory (especially visual memory), visual learning, and how fast people think. This was seen in people sober from 1 week to 8 months.

In people with AUD who did not smoke, a part of the brain called the hippocampus grew, and this was linked to better visual memory after one month of sobriety. Changes in the hippocampus were also linked to better learning and memory depending on a certain gene. Also, in non-smoking AUD patients, other brain parts grew, which was linked to faster thinking.

One study found that changes in total brain size were linked to better visual learning in people with AUD who smoked. However, faster brain growth early on in smoking AUD patients was linked to worse visual memory later on. Even with some brain growth, smoking AUD patients' visual learning and memory healing was still worse than non-smoking AUD patients.

Changes in certain fluid-filled spaces in the brain (ventricles) were linked to worse overall memory after 3 weeks to 2 years of sobriety.

In short, most studies show that changes in brain size while sober are linked to brain healing, and smoking can affect this.

Perfusion

One study found no link between blood flow in certain brain areas and changes in thinking skills, learning, memory, how fast people think, understanding space, or intelligence after one month of sobriety.

Discussion

This review looks at what science says about things that affect brain healing in people who stopped drinking alcohol.

First, much of the proof shows that smoking is mostly bad for brain healing in areas like how fast people think, learning, memory, understanding space, thinking skills, and small muscle movements. This was seen for up to nine months of not drinking. The way nicotine and alcohol work together on the brain is important because many people with AUD also smoke, making health risks much worse. Future studies should look at smoking habits and separate people who smoke now, used to smoke, or never smoked.

Second, a growing brain size within one year of not drinking alcohol is linked to better memory (especially visual memory), learning, and how fast people think. Some proof also shows that smaller fluid spaces in the brain are linked to better memory. When people stay sober, these fluid spaces get smaller, and parts of the brain grow bigger. This review supports the idea that brain healing is linked to changes in brain size, and other things like smoking or certain genes might affect this link.

Two other things that have been studied a lot are how much alcohol was used and how much schooling someone had. The proof consistently shows these are mostly not linked to brain healing. For alcohol amounts, this might be because people with AUD can have trouble remembering past events accurately, which affects how they report their past drinking. For schooling, while it is thought to affect brain function, these findings come from studies that looked at things only at one moment, not how brain function changed over time.

Finally, there is not enough proof for a clear link between other factors like using many substances, how the brain worked before, or gender, and brain healing. Mostly, studies show no link, but these areas have not been studied enough. Age also shows mixed results. Many of these factors need more research, especially because alcohol use disorder often comes with other mental health problems, which can make things worse.

Recommendations for Future (Longitudinal) Research

Based on this review, some ideas can help guide future studies on how the brain heals when someone stops drinking.

  • Brain healing was worse for people who smoked. Future studies should always look at smoking status (never smoked, used to smoke, or still smokes) because it affects healing.

  • There is enough proof that how much alcohol someone said they used is not linked to brain healing. People with AUD can have trouble remembering the past, so studies should be careful when asking people about their past drinking.

  • Most studies started brain tests within two weeks of people stopping alcohol. But stopping alcohol can cause withdrawal effects that hurt brain function. So, it is best to test brain function after at least two weeks of being sober, or even after six weeks.

  • This review found that most factors need more study. Future studies should look at age, gender, using many substances, number of past detoxes, blood results, health problems, sadness, and ASPD. These studies should follow people over time and consider how long someone has been sober.

  • How social skills heal is an area of brain function that needs more study.

Limitations

This review has some limits. First, how studies were done needs to be thought about. If a study found no link, it means there was no link based on how that study was set up. Studies in this review looked at a very different number of things. Also, good studies that look at one point in time and many factors were not included.

Second, the information from different studies could not be combined because not all facts were available. Third, the brain tests used in these studies were very different and varied in how good they were. Studies also differed in how much they thought about people getting better at tests just by doing them more often.

Finally, there is a chance of 'publication bias' because only studies that were published were included. However, this risk is probably small because the things looked at were often not the main focus of the studies. This led to many studies finding no link, for example, between how much alcohol was used and brain healing.

Conclusion

Even with these limits, this is the first review to clearly show the things that might affect brain healing in people who stopped drinking alcohol. The clearest findings are that smoking is mostly bad for brain healing. Also, changes in the size of different brain parts (like the hippocampus or fluid spaces) are linked to brain healing.

There is enough proof that brain healing is not linked to how much alcohol someone said they drank, or to how much schooling someone had. More research is needed on many factors. These include using many substances, number of past detoxes, family history, gender, sadness, ASPD, reading skills, blood results, starting brain function, health problems, and blood flow. These have not been studied enough over time or show mixed results (like age).

It is best to use studies that follow people over time, with many tests, starting at least two weeks after they stop drinking. This is because withdrawal can affect brain test results. Results from such studies can help clear up confusing findings about brain healing. They can also help us better understand how much the brain heals in people with AUD. In the end, this will help doctors find people who might heal slower or not as much. This can lead to better, more personal care for each patient.

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Footnotes and Citation

Cite

Staudt, J., Kok, T., de Haan, H. A., Walvoort, S. J. W., & Egger, J. I. M. (2023). Neurocognitive Recovery in Abstinent Patients with Alcohol Use Disorder: A Scoping Review for Associated Factors. Neuropsychiatric disease and treatment, 19, 2039–2054. https://doi.org/10.2147/NDT.S424017

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