Characterization of alcohol-related seizures in withdrawal syndrome.

OBJECTIVE: Alcohol-related seizures (ARS) are one of the most important consequences of alcohol withdrawal syndrome (AWS). However, demographic and clinical characteristics, and furthermore, the relationship of ARS with delirium tremens (DT), have not yet been evaluated in detail. Therefore, the aim of the present study was to reveal the correlates of ARS and examine the interaction of ARS with the occurrence of DT and with the severity of AWS. METHODS: In the retrospective study (Study 1) 2851 medical charts of inpatient admissions characterized by AWS and DT were listed. Demographic and clinical variables of ARS were assessed. In the follow-up study (Study 2), patients admitted with AWS without (N = 28) and with (N = 18) ARS were enrolled. Study 1 was performed between 2008 and 2023, and Study 2 was performed in 2019 in Hungary. To determine the severity of AWS, the Clinical Institute Withdrawal Assessment Scale for Alcohol, Revised (CIWA-Ar) was used. ARS is a provoked, occasional seizure; therefore, patients with epilepsy syndrome were excluded from the two studies. Statistical analyses were performed by the means of chi-square tests, multinomial logistic regressions, mixed ANOVA, and derivation. RESULTS: The occurrence of DT, the history of ARS, and somatic co-morbidities were found to be risk factors for the appearance of ARS. ARS was proved to be a risk factor for the development of DT. In the follow-up study, there was no difference in the decrease of CIWA-Ar scores between the groups. SIGNIFICANCE: Our present findings support the likelihood of kindling, which is one of the most important mechanisms underlying the development of ARS, but do not directly prove its presence. Additionally, our results revealed that the severity of AWS is not influenced by the presence of ARS. PLAIN LANGUAGE SUMMARY: Provoked, occasional seizures during AWS are defined as ARS. In the present study, predictors and interactions of these seizures with DT-the most severe form of withdrawal-and with the severity of withdrawal were examined in retrospective and follow-up studies. The present study shows that a history of withdrawal seizures, the occurrence of DT, and somatic comorbidities are predictors of the development of seizures. Furthermore, our findings suggest that the presence of seizures does not influence the severity of withdrawal.

Long-term outcome of alcohol withdrawal seizures.

BACKGROUND AND PURPOSE: Alcohol withdrawal seizures (AWS) are a well-known complication of chronic alcohol abuse, but there is currently little knowledge of their long-term relapse rate and prognosis. The aims of this study were to identify risk factors for AWS recurrence and to study the overall outcome of patients after AWS. METHODS: In this retrospective single-center study, we included patients who were admitted to the Emergency Department after an AWS between January 1, 2013 and August 10, 2021 and for whom an electroencephalogram (EEG) was requested. AWS relapses up until April 29, 2022 were researched. We compared history, treatment with benzodiazepines or antiseizure medications (ASMs), laboratory, EEG and computed tomography findings between patients with AWS relapse (r-AWS) and patients with no AWS relapse (nr-AWS). RESULTS: A total of 199 patients were enrolled (mean age 53 ± 12 years; 78.9% men). AWS relapses occurred in 11% of patients, after a median time of 470.5 days. Brain computed tomography (n = 182) showed pathological findings in 35.7%. Risk factors for relapses were history of previous AWS (p = 0.013), skull fractures (p = 0.004) at the index AWS, and possibly epileptiform EEG abnormalities (p = 0.07). Benzodiazepines or other ASMs, taken before or after the index event, did not differ between the r-AWS and the nr-AWS group. The mortality rate was 2.9%/year of follow-up, which was 13 times higher compared to the general population. Risk factors for death were history of AWS (p < 0.001) and encephalopathic EEG (p = 0.043). CONCLUSIONS: Delayed AWS relapses occur in 11% of patients and are associated with risk factors (previous AWS >24 h apart, skull fractures, and pathological EEG findings) that also increase the epilepsy risk, that is, predisposition for seizures, if not treated. Future prospective studies are mandatory to determine appropriate long-term diagnostic and therapeutic strategies, in order to reduce the risk of relapse and mortality associated with AWS.

[Assessment of alcohol withdrawal syndrome: new perspectives]. / Az alkoholmegvonásos szindróma ellátása: új perspektívák.

Alcohol withdrawal syndrome is one of the most important consequences of alcohol use disorder, a complex neuropsychiatric disorder, which is firstly treated in non-specific and secondly in psychiatric/addictive in- or outpatient units. On the other hand, alcohol withdrawal syndrome is one of the most important outcomes of the severity of alcohol use disorder, further, it can lead to the development of alcohol-related seizure and delirium tremens. Hence, early recognition and optimal treatment of alcohol withdrawal syndrome have a critical importance. Therefore, the main goal of the present review was - by systematically summarizing the scientific data published during the past two decades - to form a unique diagnostic and therapeutic algorithm. During the recognition and the course of alcohol withdrawal syndrome, the Clinical Institute Withdrawal Assessment for Alcohol, Revised scale, while in the risk assessment the Prediction of Alcohol Withdrawal Severity Scale are the recommended psychometric tools. Benzodiazepines are the key elements of the pharmacotherapy of alcohol withdrawal syndrome. Many studies have evaluated that diazepam, chlordiazepoxide, lorazepam and oxazepam with distinct indications have sufficient evidence in the treatment of alcohol withdrawal syndrome. However, in the past few years some authors have recommended the importance of non-benzodiazepine medications. The efficacy of propofol, phenobarbital, carbamazepin, oxcarbamazepin and alpha-2 receptor agonists in the treatment of alcohol withdrawal syndrome have been revealed. Furthermore, it has been evaluated that benzodiazepines are recommended in the treatment of alcohol-related seizure and delirium tremens. In the present review, our aim was to construct a unique, up-to-date diagnostic and therapeutic algorithm by summarizing the related papers published during the past two decades. Hence this scheme may be useful in the optimal treatment of patients diagnosed with alcohol use disorder and it could help to conduct further clinical researches. Orv Hetil. 2023; 164(38): 1487-1496.

Targeted Inhibition of Upregulated Sodium-Calcium Exchanger in Rat Inferior Colliculus Suppresses Alcohol Withdrawal Seizures.

The inferior colliculus (IC) is critical in initiating acoustically evoked alcohol withdrawal-induced seizures (AWSs). Recently, we reported that systemic inhibition of Ca2+ entry via the reverse mode activity of the Na+/Ca2+ exchanger (NCXrev) suppressed AWSs, suggesting remodeling of NCX expression and function, at least in the IC, the site of AWS initiation. Here, we probe putative changes in protein expression in the IC of NCX isoforms, including NCX type 1 (NCX1), 2 (NCX2), and 3 (NCX3). We also evaluated the efficacy of targeted inhibition of NCX1rev and NCX3rev activity in the IC on the occurrence and severity of AWSs using SN-6 and KB-R943, respectively. We used our well-characterized alcohol intoxication/withdrawal model associated with enhanced AWS susceptibility. IC tissues from the alcohol-treated group were collected 3 h (before the onset of AWS susceptibility), 24 h (when AWS susceptibility is maximal), and 48 h (when AWS susceptibility is resolved) following alcohol withdrawal; in comparison, IC tissues from the control-treated group were collected at 24 h after the last gavage. Analysis shows that NCX1 protein levels were markedly higher 3 and 24 h following alcohol withdrawal. However, NCX3 protein levels were only higher 3 h following alcohol withdrawal. The analysis also reveals that bilateral microinjections of SN-6 (but not KB-R7943) within the IC markedly suppressed the occurrence and severity of AWSs. Together, these findings indicate that NCX1 is a novel molecular target that may play an essential role in the pathogenesis and pathophysiology of AWSs.

Alcohol withdrawal produces changes in excitability, population discharge probability, and seizure threshold.

BACKGROUND: Alcohol withdrawal syndrome (AWS) results from the sudden cessation of chronic alcohol use and is associated with high morbidity and mortality. Alcohol withdrawal-induced central nervous system (CNS) hyperexcitability results from complex, compensatory changes in synaptic efficacy and intrinsic excitability. These changes in excitability counteract the depressing effects of chronic ethanol on neural transmission and underlie symptoms of AWS, which range from mild anxiety to seizures and death. The development of targeted pharmacotherapies for treating AWS has been slow, due in part to the lack of available animal models that capture the key features of human AWS. Using a unique optogenetic method of probing network excitability, we examined electrophysiologic correlates of hyperexcitability sensitive to early changes in CNS excitability. This method is sensitive to pharmacologic treatments that reduce excitability and may represent a platform for AWS drug development. METHODS: We applied a newly developed method, the optogenetic population discharge threshold (oPDT), which uses light intensity response curves to measure network excitability in chronically implanted mice. Excitability was tracked using the oPDT before, during, and after the chronic intermittent exposure (CIE) model of alcohol withdrawal (WD). RESULTS: Alcohol withdrawal produced a dose-dependent leftward shift in the oPDT curve (denoting increased excitability), which was detectable in as few as three exposure cycles. This shift in excitability mirrored an increase in the number of spontaneous interictal spikes during withdrawal. In addition, Withdrawal lowered seizure thresholds and increased seizure severity in optogenetically kindled mice. CONCLUSION: We demonstrate that the oPDT provides a sensitive measure of alcohol withdrawal-induced hyperexcitability. The ability to actively probe the progression of excitability without eliciting potentially confounding seizures promises to be a useful tool in the preclinical development of next-generation pharmacotherapies for AWS.

Quantitative electroencephalographic analysis of delirium tremens development following alcohol-withdrawal seizure based on a small number of male cases.

INTRODUCTION: Seizures and delirium tremens (DTs) are recognized as severe alcohol-withdrawal symptoms. Prolonged admission and serious complications associated with alcohol withdrawal are responsible for increased costs and use of medical and social resources. This study investigated the predictive value of quantitative electroencephalography (QEEG) for developing alcohol-related DTs after alcohol-withdrawal seizure (AWS). METHODS: We compared differences in QEEG in patients after AWS (n = 13). QEEG was performed in the intensive care unit within 48 h of admission, including in age- and sex-matched healthy controls. We also investigated the prognostic value of QEEG for the development of alcohol DTs after AWS in a retrospective, case-control study. The spectral power of each band frequency and the ratio of the theta to alpha band (TAR) in the electroencephalogram were analyzed using iSyncBrain® (iMediSync, Inc., Korea). RESULTS: The beta frequency and the alpha frequency band power were significantly higher and lower, respectively, in patients than in age- and sex-matched healthy controls. In AWS patients with DTs, the relative beta-3 power was lower, particularly in the left frontal area, and the TAR was significantly higher in the central channel than in those without DTs. CONCLUSION: Quantitative EEG showed neuronal excitability and decreased cognitive activities characteristic of AWS associated with alcohol-withdrawal state, and we demonstrated that quantitative EEG might be a helpful tool for detecting patients at a high risk of developing DTs during an alcohol-dependence period.

Prevention of alcohol withdrawal seizure recurrence and treatment of other alcohol withdrawal symptoms in the emergency department: a rapid review.

BACKGROUND: Patients who experience harms from alcohol and other substance use often seek care in the emergency department (ED). ED visits related to alcohol withdrawal have increased across the world during the COVID-19 pandemic. ED clinicians are responsible for risk-stratifying patients under time and resource constraints and must reliably identify those who are safe for outpatient management versus those who require more intensive levels of care. Published guidelines for alcohol withdrawal are largely limited to the primary care and outpatient settings, and do not provide specific guidance for ED use. The purpose of this review was to synthesize published evidence on the treatment of alcohol withdrawal syndrome in the ED. METHODS: We conducted a rapid review by searching MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (1980 to 2020). We searched for grey literature on Google and hand-searched the conference abstracts of relevant addiction medicine and emergency medicine professional associations (2015 to 2020). We included interventional and observational studies that reported outcomes of clinical interventions aimed at treating alcohol withdrawal syndrome in adults in the ED. RESULTS: We identified 13 studies that met inclusion criteria for our review (7 randomized controlled trials and 6 observational studies). Most studies were at high/serious risk of bias. We divided studies based on intervention and summarized evidence narratively. Benzodiazepines decrease alcohol withdrawal seizure recurrence and treat other alcohol withdrawal symptoms, but no clear evidence supports the use of one benzodiazepine over another. It is unclear if symptom-triggered benzodiazepine protocols are effective for use in the ED. More evidence is needed to determine if phenobarbital, with or without benzodiazepines, can be used safely and effectively to treat alcohol withdrawal in the ED. Phenytoin does not have evidence of effectiveness at preventing withdrawal seizures in the ED. CONCLUSIONS: Few studies have evaluated the safety and efficacy of pharmacotherapies for alcohol withdrawal specifically in the ED setting. Benzodiazepines are the most evidence-based treatment for alcohol withdrawal in the ED. Pharmacotherapies that have demonstrated benefit for treatment of alcohol withdrawal in other inpatient and outpatient settings should be evaluated in the ED setting before routine use.

Delirium Tremens in the Older Adult.

INTRODUCTION: Caring for patients experiencing alcohol withdrawal syndrome can be challenging. Patients 65 and older are at increased risk for alcohol withdrawal syndrome related complications. The higher prevalence of co-morbidities, including cognitive impairment, longer drinking history and greater sensitivity to alcohol withdrawal syndrome treatment are the result of decreased ability of the brain to adapt to stressors such as illness, trauma, or surgery. DELIRIUM TREMENS: Symptoms may appear earlier from the last drink and present with a wide range of symptoms. The most effective interventions require high-quality nursing care delivery to prevent, decrease the severity and shorten the duration of delirium. NURSING IMPLICATIONS: Strategies that help minimize these challenges starts with obtaining the patient's selfreport of their alcohol use history. Nurses should be diligent in their monitoring for signs of active alcohol withdrawal. Screening and assessment tools such as the Clinical Institute Withdrawal Assessment for Alcohol-Revised should guide pharmacological management. To support nurses in identifying delirium tremens, this manuscript seek to describe the underlying pathophysiology, key assessment components and nursing management of delirium tremens in the older adult.

Development of disturbance of consciousness is associated with increased severity in acute pancreatitis.

BACKGROUND: Disturbance of consciousness (DOC) may develop in acute pancreatitis (AP). In clinical practice, it is known that DOC may worsen the patient's condition, but we have no exact data on how DOC affects the outcome of AP. METHODS: From the Hungarian Pancreatic Study Groups' AP registry, 1220 prospectively collected cases were analyzed, which contained exact data on DOC, included patients with confusion, delirium, convulsion, and alcohol withdrawal, answering a post hoc defined research question. Patients were separated to Non-DOC and DOC, whereas DOC was further divided into non-alcohol related DOC (Non-ALC DOC) and ALC DOC groups. For statistical analysis, independent sample t-test, Mann-Whitney, Chi-squared, or Fisher exact test were used. RESULTS: From the 1220 patients, 47 (3.9%) developed DOC, 23 (48.9%) cases were ALC DOC vs. 24 (51.1%) Non-ALC DOC. Analysis between the DOC and Non-DOC groups showed a higher incidence of severe AP (19.2% vs. 5.3%, p < 0.001), higher mortality (14.9% vs. 1.7%, p < 0.001), and a longer length of hospitalization (LOH) (Me = 11; IQR: 8-17 days vs. Me = 9; IQR: 6-13 days, p = 0.049) respectively. Patients with ALC DOC developed more frequently moderate AP vs. Non-ALC DOC (43.5% vs. 12.5%), while the incidence of severe AP was higher in Non-ALC vs. ALC DOC group (33.3% vs. 4.4%) (p < 0.001). LOH showed a tendency to be longer in Non-ALC DOC compared to ALC DOC, respectively (Me:13; IQR:7-20 days vs. Me:9.5; IQR:8-15.5 days, p = 0.119). CONCLUSION: DOC during AP is associated with a higher rate of moderate and severe AP and increases the risk of mortality.

A machine learning approach to risk assessment for alcohol withdrawal syndrome.

At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to predict alcohol withdrawal outcomes at the individual subject level using information easily attainable at patients' admission. An observational machine learning analysis using nested cross-validation and out-of-sample validation was applied to alcohol-dependent patients at two major detoxification wards (LMU, n = 389; TU, n = 805). 121 retrospectively derived clinical, blood-derived, and sociodemographic measures were used to predict 1) moderate to severe withdrawal defined by the alcohol withdrawal scale, 2) delirium tremens, and 3) withdrawal seizures. Mild and more severe withdrawal cases could be separated with significant, although highly variable accuracy in both samples (LMU, balanced accuracy [BAC] = 69.4%; TU, BAC = 55.9%). Poor outcome predictions were associated with higher cumulative clomethiazole doses during the withdrawal course. Delirium tremens was predicted in the TU cohort with BAC of 75%. No significant model predicting withdrawal seizures could be found. Our models were unique to each treatment site and thus did not generalize. For both treatment sites and withdrawal outcome different variable sets informed our models' decisions. Besides previously described variables (most notably, thrombocytopenia), we identified new predictors (history of blood pressure abnormalities, urine screening for benzodiazepines and educational attainment). In conclusion, machine learning approaches may facilitate generalizable, individualized predictions for alcohol withdrawal severity. Since predictive patterns highly vary for different outcomes of withdrawal severity and across treatment sites, prediction tools should not be recommended for clinical practice unless adequately validated in specific cohorts.

Alcohol-induced thrombocytopenia: Current review.

Thrombocytopenia is a decrease in the platelet count below 150,000 in a microliter of blood, i.e., below the lower limit of the reference range, which is 150,000-400,000/µL. The phenomenon of thrombocytopenia related to heavy drinking began to arouse interest in the 1960s and 1970s. It was initially described in case reports and clinical studies on small groups. In the following years, the phenomenon itself and the significance of alcohol-induced thrombocytopenia was studied. Many methodological difficulties inhibiting objective conclusions from research were encountered. Model pathological mechanisms of alcohol thrombocytopenia and the effects of alcohol on the structure and function of platelets were described. Furthermore, the phenomenon of rapid normalization of the number of platelets in people who stopped drinking was described. Relationships between alcohol use, its intensity and occurrence, and intensity of thrombocytopenia have been demonstrated. Predictive platelet counts for alcohol withdrawal syndrome complications have been proven and calculated. The risk of occurrence of withdrawal seizures or delirium tremens in alcohol withdrawal syndrome increases significantly when the platelet count is less than 119,000/µL. The knowledge of the nature of the phenomenon of alcohol-induced thrombocytopenia in a clinical environment allows decisions that are more rational. The attention of clinicians should be drawn to the importance of results of blood tests routinely collected on admission.

Derivation and validation of a multivariable model, the alcohol withdrawal triage tool (AWTT), for predicting severe alcohol withdrawal syndrome.

BACKGROUND: Alcohol withdrawal and its consequences are a common concern for the large numbers of patients who present to emergency departments (EDs) with alcohol use disorders. While the majority of patients who go on to develop alcohol withdrawal experience only mild symptoms, a small proportion will experience seizures or delirium tremens. The aim of this study was to develop a tool to predict the need for hospital admission in patients at risk for alcohol withdrawal using only objective criteria that are typically available during the course of an ED visit. METHODS: We conducted a retrospective study at an academic medical center. Our primary outcome was severe alcohol withdrawal syndrome (SAWS), which we defined as a composite of delirium tremens, seizure, or use of high benzodiazepine doses. All candidate predictors were abstracted from the electronic health record. A logistic regression model was constructed using the derivation dataset to create the alcohol withdrawal triage tool (AWTT). RESULTS: Of the 2038 study patients, 408 20.0 %) developed SAWS. We identified eight independent predictors of SAWS. Each of the predictors in the regression model was assigned one point. Summing the points for each predictor generated the AWTT score. An AWTT score of 3 or greater was defined as high risk based on sensitivity of 90 % and specificity of 47 % for predicting SAWS. CONCLUSIONS: We were able to identify a set of objective, timely, independent predictors of SAWS. The predictors were used to create a novel clinical prediction rule, the AWTT.

Are Patients With Alcohol-Related Seizures a Specific Subgroup?

OBJECTIVE: Alcohol-related seizures are acute symptomatic seizures most frequently associated with alcohol withdrawal. However, little is known about the phenotypic characteristics of patients with alcohol-related seizures. This study evaluated the clinical features and personality traits of alcohol use disorder patients with alcohol-related seizures. METHODS: This comparative correlational study assessed the clinical and psychological covariates of alcohol-related seizures. A total of 144 alcohol-dependent patients were recruited from an alcoholism unit from January 2017 to January 2019 and divided into 2 subgroups: alcohol-dependent patients reporting alcohol-related seizures and alcohol-dependent patients with no history of alcohol-related seizures. RESULTS: The alcohol-related seizures subgroup significantly started to abuse (F = 4.1, P = .019) and depend (F = 0.12, P = .008) on alcohol at an earlier age and had more alcohol detoxification episodes (F = 4.4, P = .048), a higher degree of alcohol dependence severity (F = 0.30, P = .009), and a more frequent family history of alcoholism (χ² = 4.9, P = .026). These patients also had lower levels of openness to experience (F = 4.0, P = .029) after adjustment for current age, age at onset of alcohol misuse and dependence, severity of alcohol dependence level, number of previous alcohol detoxifications, and family history. CONCLUSIONS: The findings will help clinicians better understand this subgroup of patients and highlight the importance of considering personality traits and other clinical features when tailoring treatment for these individuals.

Activity of hippocampal adult-born neurons regulates alcohol withdrawal seizures.

Alcohol withdrawal (AW) after chronic alcohol exposure produces a series of symptoms, with AW-associated seizures being among the most serious and dangerous. However, the mechanism underlying AW seizures has yet to be established. In our mouse model, a sudden AW produced 2 waves of seizures: the first wave includes a surge of multiple seizures that occurs within hours to days of AW, and the second wave consists of sustained expression of epileptiform spikes and wave discharges (SWDs) during a protracted period of abstinence. We revealed that the structural and functional adaptations in newborn dentate granule cells (DGCs) in the hippocampus underlie the second wave of seizures but not the first wave. While the general morphology of newborn DGCs remained unchanged, AW increased the dendritic spine density of newborn DGCs, suggesting that AW induced synaptic connectivity of newborn DGCs with excitatory afferent neurons and enhanced excitability of newborn DGCs. Indeed, specific activation and suppression of newborn DGCs by the chemogenetic DREADD method increased and decreased the expression of epileptiform SWDs, respectively, during abstinence. Thus, our study unveiled that the pathological plasticity of hippocampal newborn DGCs underlies AW seizures during a protracted period of abstinence, providing critical insight into hippocampal neural circuits as a foundation to understand and treat AW seizures.

A view from the acute hospital: managing patients with alcohol problems.

Regular heavy consumption of alcohol is associated with a wide range of physical, psychological and social problems. All health-care clinicians should be able to screen for and detect problematic levels of alcohol consumption in their patients, and deliver an effective brief intervention. When patients with alcohol dependence are admitted to hospital there must be an assessment of whether medication is required to prevent withdrawal symptoms and potential delirium tremens and withdrawal seizures. Medically assisted alcohol withdrawal using a long-acting benzodiazepine such as chlordiazepoxide should be carefully monitored and titrated to effect, and the clinician should be aware of the risk of Wernicke-Korsakoff syndrome and other complications. Abstinence from alcohol is usually only the first step in treatment, and effective linkage to community alcohol services is an important step.

[The first step towards a unified approach: validation of the Hungarian version of the Clinical Institute Withdrawal Assessment of Alcohol, Revised in Hungarian general hospital settings]. / Elso lépés egy egységes szemlélet felé: az Alkohol Megvonási Skála bevezetése a hazai betegellátási gyakorlatba.

Introduction and aim: The available literature and protocols have unequivocally suggested that the Clinical Institute Withdrawal Assessment of Alcohol, Revised is a psychometric scale for identifying and following the signs of alcohol withdrawal. However, there has not been any validated tool for the identification of withdrawal symptoms in Hungarian general hospital settings. The aim of the present study was to evaluate the validity and the reliability of the Hungarian version of this scale among patients hospitalized with alcohol withdrawal syndrome. Method: The translation of the scale into Hungarian was done by 'back translation' method, followed by testing the face validity. The empirical phase was performed in the Department of Psychiatry, University of Szeged. Patients admitted with alcohol withdrawal syndrome (n = 30) were recruited from the inpatient units of the clinic. Clinical Institute Withdrawal Assessment of Alcohol, Revised and Clinical Global Impression - Severity Scale were recorded every two days. Statistical comparisons of data were performed with repeated-measures ANOVA. Cronbach's alpha, item-total correlation, convergent and discriminant validity were determined. Results: Significant decrease of the total scores of Clinical Institute Withdrawal Assessment of Alcohol, Revised and Clinical Global Impression - Severity Scale was observed between the six measurements (F = 202.46, p<0.001; F = 503.04, p<0.001). Cronbach alpha values were above 0.7 during the first 3 measurement days. The withdrawal and severity scores recorded the same day showed positively significant correlations (>0.45). Conclusion: Our findings demonstrate that the Clinical Institute Withdrawal Assessment of Alcohol, Revised is a reliable and valid psychometric tool for the detailed analysis of withdrawal symptoms in Hungarian general hospital settings. Orv Hetil. 2019; 160(30): 1184-1192.