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.

Management of alcohol withdrawal syndrome in patients with alcohol-associated liver disease

Alcohol-associated liver disease is a common and severe sequela of excessive alcohol use; effective treatment requires attention to both liver disease and underlying alcohol use disorder (AUD). Alcohol withdrawal syndrome (AWS) can be dangerous, is a common barrier to AUD recovery, and may complicate inpatient admissions for liver-related complications. Hepatologists can address these comorbid conditions by learning to accurately stage alcohol-associated liver disease, identify AUD using standardized screening tools (eg, Alcohol Use Disorder Identification Test), and assess risk for and symptoms of AWS. Depending on the severity, alcohol withdrawal often merits admission to a monitored setting, where symptom-triggered administration of benzodiazepines based on standardized scoring protocols is often the most effective approach to management. For patients with severe liver disease, selection of benzodiazepines with less dependence on hepatic metabolism (eg, lorazepam) is advisable. Severe alcohol withdrawal often requires a "front-loaded" approach with higher dosing, as well as intensive monitoring. Distinguishing between alcohol withdrawal delirium and HE is important, though it can be difficult, and can be guided by differentiating clinical characteristics, including time to onset and activity level. There is little data on the use of adjuvant medications, including anticonvulsants, dexmedetomidine, or propofol, in this patient population. Beyond the treatment of AWS, inpatient admission and outpatient hepatology visits offer opportunities to engage in planning for ongoing management of AUD, including initiation of medications for AUD and referral to additional recovery supports. Hepatologists trained to identify AUD, alcohol-associated liver disease, and risk for AWS can proactively address these issues, ensuring that patients' AWS is managed safely and effectively and supporting planning for long-term recovery.

Sex difference in alcohol withdrawal syndrome: a scoping review of clinical studies

Background

We conducted a review of all studies comparing clinical aspects of alcohol withdrawal syndrome (AWS) between men and women.

Methods

Five databases (PubMed, Cochrane, EMBASE, Scopus and Clinical Trials) were searched for clinical studies using the keywords "alcohol withdrawal syndrome" or "delirium tremens" limited to "sex" or "gender" or "sex difference" or "gender difference." The search was conducted on May 19, 2023. Two reviewers selected studies including both male and female patients with AWS, and they compared males and females in type of AWS symptoms, clinical course, complications, and treatment outcome.

Results

Thirty-five observational studies were included with a total of 318,730 participants of which 75,346 had AWS. In twenty of the studies, the number of patients presenting with or developing AWS was separated by sex, resulting in a total of 8,159 (12.5%) female patients and a total of 56,928 (87.5%) male patients. Despite inconsistent results, males were more likely than females to develop complicated AWS [delirium tremens (DT) and AW seizures, collective DT in Males vs. females: 1,792 (85.4%) vs. 307 (14.6%), and collective seizures in males vs. females: 294 (78%) vs. 82 (22%)]. The rates of ICU admissions and hospital length of stay did not show sex differences. Although variable across studies, compared to females, males received benzodiazepine treatment at higher frequency and dose. One study reported that the time from first hospitalization for AWS to death was approximately 1.5 years shorter for males and males had higher mortality rate [19.5% (197/1,016)] compared to females [16% (26/163)].

Conclusion

Despite the significant heterogeneity of the studies selected and the lack of a focus on investigating potential sex differences, this review of clinical studies on AWS suggests that men and women exhibit different AWS manifestations. Large-scale studies focusing specifically on investigating sex difference in AWS are needed.

Neutrophil-lymphocyte ratio as a predictor of delirium tremens in hospitalized patients with alcohol withdrawal

Delirium Tremens (DT) is a severe form of alcohol withdrawal that can be fatal if not recognized early and treated appropriately. In our study, we aimed to determine the role of Neutrophil-Lymphocyte ratio (NLR), a marker of systemic inflammation, in predicting the development of DT. This retrospective study was conducted in an alcohol and drug treatment center between March 2017 and March 2020. A total of 212 patients with a diagnosis of alcohol use disorder who were admitted to a special care unit after alcohol withdrawal were included. Blood tests were collected within 24 hours of the patients' admission. Comparisons were made according to whether the patients developed DT during the hospitalization. DT was diagnosed in 24.1% of the patients. It was determined that higher NLR level (odds ratio [OR]: 4.38, 95%CI: 2.58-7.43) and history of DT (OR: 1.33, 95%CI: 1.23-11.73) are independent risk factors for the development of DT in the logistic regression analysis. The optimal cut-off value of NLR in predicting DT was 2.67 (sensitivity: 82.4%, specificity: 88.8%). The ROC curve of NLR showed a larger area under the curve (AUC) than the curves of other systemic inflammation markers. NLR is a simple, practical and inexpensive marker that can predict the development of DT in patients with alcohol withdrawal syndrome.

Alcohol Withdrawal Syndrome in Women vs Men: Analysis of 1496 Cases at a Single Site

BACKGROUND

Studies of alcohol withdrawal syndrome indicate a higher prevalence in men than in women. However, it is unknown how the condition differs between the sexes.

OBJECTIVE

To assess alcohol withdrawal syndrome in women versus men at a single site.

METHODS

All cases of alcohol withdrawal syndrome at a public hospital from 2010 to 2014 were reviewed retrospectively. For all 1496 episodes, age, sex, and admission to a general care unit (ward) versus the medical intensive care unit were ascertained, along with patient survival. A detailed analysis was performed of 437 cases: all 239 patients admitted to the medical intensive care unit, all 99 female patients admitted to the ward, and 99 randomly selected male patients admitted to the ward. Also analyzed were administration of benzodiazepines, disease course, length of stay, and complications.

RESULTS

Men accounted for 92% of all cases (1378 of 1496; P < .001) and medical intensive care unit admissions (220 of 239; P < .05). Sixteen percent of both men and women were admitted to the medical intensive care unit. Men were older (mean age, 45.6 vs 43.9 years; P < .01), and women required more benzodiazepines. Similar rates of complications occurred in both sexes, although women had a higher rate of pancreatitis and men had higher rates of pneumonia, higher rates of sepsis, and longer stays.

CONCLUSIONS

Men and women with alcohol withdrawal syndrome have similar complications, courses, and intensive care unit admission rates, although men are more prone to pneumonia and have longer stays.

Alcohol-related phenotypes and platelet serotonin concentration

Alcohol dependence is a chronic relapsing mental disorder with heterogeneous and complex underlying biology. It is frequently associated with nicotine dependence, severity of alcohol dependence symptoms, and diverse alcohol-related phenotypes, including the presence of delirium tremens and withdrawal symptoms, early or late onset of alcohol abuse, aggression, suicidal behavior, and anxiety. While searching for peripheral biomarkers of altered serotonergic (5-HT) function in alcohol dependence and alcohol-related behaviors, we determined a peripheral biomarker, i.e., platelet 5-HT concentration in a large group of Caucasian subjects with alcohol dependence subdivided according to the presence of specific alcohol-related phenotypes and smoking status. Individuals with alcohol dependence (n = 661) of both sexes were evaluated using Structural Clinical Interview based on DSM-IV criteria, while platelet 5-HT concentration was determined using the spectrophotofluorimetric method. Smoking is significantly associated, while sex and age are not, with platelet 5-HT concentration. Severe alcohol dependence and lack of withdrawal symptoms were associated with significantly decreased platelet 5-HT concentration in alcohol-dependent non-smokers. In smokers, significantly lower platelet 5-HT concentration was found in patients with the late onset of alcohol abuse. These results suggested that platelet 5-HT concentration might be used as a peripheral marker of different alcohol-related phenotypes, after controlling for the effects of smoking and sex.

Research Needs for Inpatient Management of Severe Alcohol Withdrawal Syndrome: An Official American Thoracic Society Research Statement

Background: Severe alcohol withdrawal syndrome (SAWS) is highly morbid, costly, and common among hospitalized patients, yet minimal evidence exists to guide inpatient management. Research needs in this field are broad, spanning the translational science spectrum. Goals: This research statement aims to describe what is known about SAWS, identify knowledge gaps, and offer recommendations for research in each domain of the Institute of Medicine T0-T4 continuum to advance the care of hospitalized patients who experience SAWS. Methods: Clinicians and researchers with unique and complementary expertise in basic, clinical, and implementation research related to unhealthy alcohol consumption and alcohol withdrawal were invited to participate in a workshop at the American Thoracic Society 2019 International Conference. The committee was subdivided into four groups on the basis of interest and expertise: T0-T1 (basic science research with translation to humans), T2 (research translating to patients), T3 (research translating to clinical practice), and T4 (research translating to communities). A medical librarian conducted a pragmatic literature search to facilitate this work, and committee members reviewed and supplemented the resulting evidence, identifying key knowledge gaps. Results: The committee identified several investigative opportunities to advance the care of patients with SAWS in each domain of the translational science spectrum. Major themes included 1) the need to investigate non-γ-aminobutyric acid pathways for alcohol withdrawal syndrome treatment; 2) harnessing retrospective and electronic health record data to identify risk factors and create objective severity scoring systems, particularly for acutely ill patients with SAWS; 3) the need for more robust comparative-effectiveness data to identify optimal SAWS treatment strategies; and 4) recommendations to accelerate implementation of effective treatments into practice. Conclusions: The dearth of evidence supporting management decisions for hospitalized patients with SAWS, many of whom require critical care, represents both a call to action and an opportunity for the American Thoracic Society and larger scientific communities to improve care for a vulnerable patient population. This report highlights basic, clinical, and implementation research that diverse experts agree will have the greatest impact on improving care for hospitalized patients with SAWS.

[Clinical and metabolic predictors for delirium tremens]

OBJECTIVE

To search for objective diagnostic criteria for the development of delirium tremens (DT) based on physiological and metabolic parameters.

MATERIAL AND METHODS

The total number of patients was 506, including 393 patients with DT and 113 patients with uncomplicated alcohol withdrawal syndrome (UAWS). Twenty clinical and metabolic indicators were analyzed statistically using comparison of means, logistic regression and ROC-analysis.

RESULTS AND CONCLUSION

Hyponatremia, thrombocytopenia and tachycardia are most prognostically significant indicators, changes in which are observed in the development of DT. These indicators can serve as the basis for objective diagnosis of alcohol withdrawal syndrome complicated by delirium.

Use of Electronic Health Record Data to Estimate the Probability of Alcohol Withdrawal Syndrome in a National Cohort of Hospitalized Veterans

OBJECTIVES

Inpatient alcohol withdrawal syndrome (AWS) is common and early treatment improves outcomes, but no prior study has used electronic health record (EHR) data, available at admission, to predict the probability of inpatient AWS. This study estimated the probability of inpatient AWS using prior-year EHR data, hypothesizing that documented alcohol use disorder (AUD) and AWS would be strongly associated with inpatient AWS while exploring associations with other patient characteristics.

METHODS

The study investigated patients hospitalized ≥24 hours on medical services in the Veterans Health Administration during 2013 using EHR data extracted from the Veterans Health Administration Corporate Data Warehouse. ICD-9-CM diagnosis code, demographic, and healthcare utilization data documented in the year before admission defined prior-year AUD, AWS, and other factors associated with inpatient AWS. The primary outcome, inpatient AWS, was defined by inpatient ICD-9-CM codes.

RESULTS

The unadjusted probability of AWS was 5.0% (95% CI 4.5%-5.4%) among 209,151 medical inpatients overall, 26.4% (95% CI 24.4%-28.4%) among those with prior-year AUD, and 62.5% (95% CI 35.2%-39.7%) among those with prior-year AWS. Of those with AWS, 86% had documented prior-year AUD and/or AWS. Other patient characteristics associated with increased probability of inpatient AWS (P < 0.001) were: male sex, single relationship status, homelessness, seizure, and cirrhosis.

CONCLUSIONS

Although inpatient providers often use history to predict AWS, this is the first study in hospitalized patients to inform and validate this practice, showing that prior-year diagnosis of AUD and/or AWS in particular, can identify the majority of inpatients who should be monitored for AWS.

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.

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.

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.

Thrombocytopenia in Patients Hospitalized for Alcohol Withdrawal Syndrome and Its Associations to Clinical Complications

BACKGROUND

The aim of this study was to assess the predictive value of thrombocytopenia (TP) in alcohol withdrawal syndrome (AWS) as a marker of evolution of non-complicated AWS (nAWS) to severe, complicated AWS (cAWS): delirium tremens (DTs) and withdrawal seizures (wS), and to broaden knowledge about differences between nAWS and cAWS groups in relation to severity of TP.

METHODS

This study involved 300 people (236 males and 64 females), aged 19-65 years (M = 44.64, SD = 11.32), hospitalized in the detoxification ward with ICD-10 diagnosis of F10.3 (AWS) or F10.4 (DTs), divided into nAWS and cAWS groups, 150 cases each. AWS severity was measured by CIWA-Ar. Available clinical and laboratory data were analyzed.

RESULTS

TP was found in 139 (46%) of all subjects (nAWS = 32, cAWS = 107). nAWS and cAWS did not differ according to age, gender, length and severity of the last binge. A relationship between the occurrence of TP and cAWS was found (P < 0.001). The lower was the number of PLT, the more AWS incidence was observed. In CIWA-Ar, TP subjects had at least moderate AWS (P < 0.001). nAWS had higher PLT values than cAWS cases (Mrang = 195.96 vs. 105.04, P < 0.001). The predictive value of TP in cAWS was confirmed.

CONCLUSIONS

The study demonstrates that patients with AWS and TP (in particular <119k/mL) are at higher risk of developing cAWS.

Will This Hospitalized Patient Develop Severe Alcohol Withdrawal Syndrome?: The Rational Clinical Examination Systematic Review

IMPORTANCE

Although severe alcohol withdrawal syndrome (SAWS) is associated with substantial morbidity and mortality, most at-risk patients will not develop this syndrome. Predicting its occurrence is important because the mortality rate is high when untreated.

OBJECTIVE

To assess the accuracy and predictive value of symptoms and signs for identifying hospitalized patients at risk of SAWS, defined as delirium tremens, withdrawal seizure, or clinically diagnosed severe withdrawal.

DATA SOURCES

MEDLINE and EMBASE (1946-January 2018) were searched for articles investigating symptoms and signs predictive of SAWS in adults. Reference lists of retrieved articles were also searched.

STUDY SELECTION

Original studies that were included compared symptoms, signs, and risk assessment tools among patients who developed SAWS and patients who did not.

DATA EXTRACTION AND SYNTHESIS

Data were extracted and used to calculate likelihood ratios (LRs), sensitivity, and specificity. A meta-analysis was performed to calculate summary LR.

RESULTS

Of 530 identified studies, 14 high-quality studies that included 71 295 patients and 1355 relevant cases of SAWS (1051 cases), seizure (53 cases), or delirium tremens (251 cases) were analyzed. A history of delirium tremens (LR, 2.9 [95% CI 1.7-5.2]) and baseline systolic blood pressure 140 mm Hg or higher (LR, 1.7 [95% CI, 1.3-2.3) were associated with an increased likelihood of SAWS. No single symptom or sign was associated with exclusion of SAWS. Six high-quality studies evaluated combinations of clinical findings and were useful for identifying patients in acute care facilities at high risk of developing SAWS. Of these combinations, the Prediction of Alcohol Withdrawal Severity Scale (PAWSS) was most useful, with an LR of 174 (95% CI, 43-696; specificity, 0.93) when patients had 4 or more individual findings and an LR of 0.07 (95% CI, 0.02-0.26; sensitivity, 0.99) when there were 3 or fewer findings.

CONCLUSIONS AND RELEVANCE

Assessment tools that use a combination of symptoms and signs are useful for identifying patients at risk of developing severe alcohol withdrawal syndrome. Most studies of these tools were not fully validated, limiting their generalizability.

Risk factors associated with the development of seizures among adult patients treated with ertapenem: A matched case-control study

Objective

The purpose of this study is to compare the characteristics of those ertapenem-treated adult patients with and without development of seizures, and identify the associated factors for the development of seizures.

Methods

This retrospective study was conducted at Chia-Yi Christian Hospital from January 2012 to December 2014. Patients developing seizures during their ertapenem treatment course were identified as case patients. Those without seizures who had received ertapenem for at least five days were considered as the pool of control patients. For each case patient, four matched patients from the control pool were randomly selected as the final control group, based on age, gender, and the date of ertapenem prescription.

Results

A total of 1706 ertapenem-treated patients were identified, 33 (1.9%) individuals developed seizures with the enrollment of 132 matched control patients. Among these 33 patients, the average age was 79.3 ± 7.5 years, and 20 (60.6%) were male. The mean Charlson co-morbidity score was 4.5 ± 2.4, and the first episode of seizure happened 3.3 ± 2.6 days after receiving ertapenem. In multivariate logistic regression analysis, the independent predictors associated with the development of ertapenem-associated seizures were old stroke (OR, 14.36; 95% CI, 4.38–47.02; p < 0.0001), undergoing brain images within one year prior to the admission (OR, 5.73; 95% CI, 1.78–18.43; p = 0.0034), low hemoglobin level (OR, 3.88; 95% CI, 1.28–12.75; p = 0.0165) and low platelet count (OR, 4,94; 95% CI, 1.56–15.68; p = 0.0067) at presentations, and protective factors against the development of seizures were heart failure (OR, 0.04; 95% CI, 0.00–0.63; p = 0.0222), concomitant use of steroids (OR, 0.19; 95% CI, 0.05–0.77; p = 0.0201), or antiplatelet agents (OR, 0.12; 95% CI, 0.02–0.63, p = 0.0123) with ertapenem.

Conclusions

The development of ertapenem-associated seizures may occur more frequently and much earlier due to its widespread use in treating drug-resistant pathogens, especially when these pathogens emerged worldwide.Our study would help physician to estimate the risk of developing seizure among patients receiving ertapenem.

A Study of Patterns of Platelet Counts in Alcohol Withdrawal

AIMS

This study aimed to evaluate the patterns of platelet counts during the course of alcohol withdrawal and its relationship if any with liver enzymes.

METHODOLOGY

Forty consecutive patients, with alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders-fourth edition, Text Revision criteria, willing for a 10-day inpatient detoxification program and presenting within 12 h of the last consumption of alcohol were recruited in the study. Details about the diagnosis and alcohol consumption patterns were assessed with a detailed psychiatric interview. After admission, routine investigations (complete blood counts [CBCs] and liver function tests) were sent and records were kept. CBC was sent for platelet counts on the 2^nd, 4^th, 6^th, 8^th, and the 10^th day of alcohol withdrawal.

RESULTS

Nearly 40% of the patients developed delirium tremens (DT group) and rest had an uncomplicated alcohol withdrawal (ND group). Platelet counts at baseline and all the 4 days of collection were significantly lower in DT group than the ND group. Platelet counts increased gradually from baseline till 10^th day of alcohol withdrawal, mean increase in platelet counts being 88.61 ± 11.60% (median: 61.11%, range [23.41-391.23%]). Platelet counts in 63% of the patients showed a drop on the 4^th day of withdrawal before rising till the 10^th day of alcohol withdrawal. Platelet counts were not affected by liver enzymes or other alcohol consumption patterns.

CONCLUSIONS

Transient thrombocytopenia and reverse thrombocytosis during alcohol withdrawal are associated with an initial drop in platelet counts. The synchrony between the drop and the onset of DT needs to be evaluated.

Risk factors for the development of delirium in alcohol dependence syndrome: Clinical and neurobiological implications

INTRODUCTION

Alcohol withdrawal delirium (AWD) or delirium tremens (DT) is associated with severe complications and high mortality. Prospectively identifying patients with increased risk of developing DT would have important preventive and therapeutic implications. Thus, the present study aimed to identify clinical risk factors predicting the development of DT.

MATERIALS AND METHODS

The study was a cross-sectional quasi-experimental one with equivalent control group, conducted at a tertiary hospital from August 2014 to May 2015. Forty adult male inpatients, diagnosed with DT, were compared with forty age- and sex-matched inpatients in alcohol withdrawal state without delirium. Assessments were done using confusion assessment method, Clinical Institute Withdrawal Assessment of Alcohol Scale, and Mini-Mental Status Examination. For group comparisons, Pearson's Chi-square test and independent sample t-test were used; logistic regression was applied to identify predictors followed by receiver operating characteristic curve analysis.

RESULTS

Heavy drinking (P = 0.005; odds ratio [OR]: 1.17, confidence interval [CI]: 1.05-1.31), continuous pattern of drinking (P = 0.027; OR: 4.67, CI: 1.19-18.33), past history of delirium (P = 0.009; OR: 552.8, CI: 4.88-625.7), alcohol-induced psychosis (P = 0.002; OR: 74.6, CI: 4.68-1190), and presence of cognitive deficits (P = 0.044; OR: 12.5, CI: 1.07-147.3) emerged as strong predictors of AWD.

CONCLUSION

The risk factors found can be easily evaluated in a clinical setting for physicians to readily identify patients at risk for developing DT and plan intensive therapies for them. At a neurobiological level, patients with preexisting brain neurotransmitter disturbances are at greater risk for developing DT.

The emergency medicine management of severe alcohol withdrawal

INTRODUCTION

Alcohol use is widespread, and withdrawal symptoms are common after decreased alcohol intake. Severe alcohol withdrawal may manifest with delirium tremens, and new therapies may assist in management of this life-threatening condition.

OBJECTIVE

To provide an evidence-based review of the emergency medicine management of alcohol withdrawal and delirium tremens.

DISCUSSION

The underlying pathophysiology of alcohol withdrawal syndrome (AWS) is central nervous system hyperexcitation. Stages of withdrawal include initial withdrawal symptoms, hallucinations, seizures, and delirium tremens. Management focuses on early diagnosis, resuscitation, and providing medications with gamma-aminobutyric acid (GABA) receptor activity. Benzodiazepines with symptom-triggered therapy have been the predominant medication class utilized and should remain the first treatment option with rapid escalation of dosing. Treatment resistant withdrawal warrants the use of phenobarbital or propofol, both demonstrating efficacy in management. Propofol can be used as an induction agent to decrease the effects of withdrawal. Dexmedetomidine does not address the underlying pathophysiology but may reduce the need for intubation. Ketamine requires further study. Overall, benzodiazepines remain the cornerstone of treatment. Outpatient management of patients with minimal symptoms is possible.

CONCLUSIONS

Alcohol withdrawal syndrome can result in significant morbidity and mortality. Physicians must rapidly diagnose these conditions while evaluating for other diseases. Benzodiazepines are the predominant medication class utilized, with adjunctive treatments including propofol or phenobarbital in patients with withdrawal resistant to benzodiazepines. Dexmedetomidine and ketamine require further study.

Alcohol withdrawal syndrome: mechanisms, manifestations, and management

The alcohol withdrawal syndrome is a well‐known condition occurring after intentional or unintentional abrupt cessation of heavy/constant drinking in patients suffering from alcohol use disorders (AUDs). AUDs are common in neurological departments with patients admitted for coma, epileptic seizures, dementia, polyneuropathy, and gait disturbances. Nonetheless, diagnosis and treatment are often delayed until dramatic symptoms occur. The purpose of this review is to increase the awareness of the early clinical manifestations of AWS and the appropriate identification and management of this important condition in a neurological setting.

Clinical predictors for delirium tremens in patients with alcohol withdrawal seizures

BACKGROUND

Delirium tremens (DT) is the severest form of alcohol withdrawal syndrome, frequently after alcohol withdrawal seizures. Delirium tremens occurs in a small proportion of patients with alcohol withdrawal seizures; nevertheless, early identification of high-risk patients is important for intensive preventive management of unexpected episodes due to agitation and its associated increased mortality. However, there are limited studies on clinical predictors of the development of DT in patients with alcohol withdrawal seizures.

METHODS

Patients who visited the emergency department with acute seizures were included in the study when alcohol withdrawal was the only or the strongest precipitating factor for seizures. All patients were carefully observed for at least 48 hours in the intensive care unit after the initial assessment to closely monitor vital signs and development of DT. Clinical and laboratory findings were analyzed for predicting the development of DT.

RESULTS

Of the 97 patients (82 males; mean age, 48.6 ± 13.3 years) with alcohol withdrawal seizures, 34 (35.1%) developed DT. Low platelet count, high blood level of homocysteine, and low blood level of pyridoxine were associated with the subsequent development of DT. Low platelet count and high blood level of homocysteine were independent risk factors with high diagnostic sensitivity and specificity for the development of DT.

CONCLUSIONS

The study indicated that some easily determined parameters are potential clinical predictors for the development of DT in patients with alcohol withdrawal seizures. These findings would be helpful in clinical identification and management patients at high risk for DT.

Alcohol withdrawal delirium - diagnosis, course and treatment

OBJECTIVE

Delirium tremens represents the most severe complication of alcohol withdrawal syndrome and, in its complications, significantly increases the morbidity and mortality of patients. Alcohol withdrawal delirium is characterized by features of alcohol withdrawal itself (tremor, sweating, hypertension, tachycardia etc.) together with general delirious symptoms such as clouded consciousness, disorientation, disturbed circadian rhythms, thought processe and sensory disturbances, all of them fluctuating in time. The treatment combines a supportive and symptomatic approach. Benzodiazepines in supramaximal doses are usually used as drugs of choice but in some countries such as the Czech Republic or Germany, clomethiazole is frequently used as well.

METHOD

A computer search of the all the literature published between 1966 and December 2012 was accomplished on MEDLINE and Web of Science with the key words "delirium tremens", "alcohol withdrawal", "treatment" and "pharmacotherapy". There were no language or time limits applied.

CONCLUSIONS

When not early recognized and treated adequately, delirium tremens may result in death due to malignant arrhythmia, respiratory arrest, sepsis, severe electrolyte disturbance or prolonged seizures and subsequent trauma. Owing to these possible fatalities and other severe unexpected complications, delirium tremens should be managed at an ICU or wards ensuring vital signs monitoring. In symptomatic treatment, high doses of benzodiazepines, especially lorazepam, diazepam and oxazepam are considered the gold standard drugs. Supportive therapy is also of great importance.

Biological markers for alcohol withdrawal seizures: a retrospective analysis

AIMS

Alcohol withdrawal seizures (AWS) are among the most important possible complications during the detoxification treatment of alcohol-dependent patients. Pharmacological therapy is often used during detoxification, but can cause dangerous side effects [Eur Addict Res 2010;16:179-184]. In separate studies several biological markers have been described as being associated with AWS risk. We investigated the role of homocysteine (HCT), carbohydrate-deficient transferrin (CDT) and prolactin (PRL) as biological markers for the risk of developing AWS.

METHODS

The present study included 189 alcohol-dependent patients of whom 51 had a history of AWS. We investigated the HCT, CDT and PRL levels of all patients and calculated sensitivity and specificity. Bayes' theorem was used to calculate positive (PPV) and negative (NPV) predictive values.

RESULTS

The highest combined sensitivity and specificity for %CDT was reached at a plasma cutoff value of 3.75%. The combination of HCT at a cutoff value of 23.9 μmol/l and %CDT at a cutoff value of 3.75% showed the best predictive values (sensitivity 47.1%, specificity 88.4%, PPV 0.504, NPV 0.870).

CONCLUSION

A combined assessment of HCT and CDT levels can be a useful method to identify patients at a higher risk of AWS, which may lead to a more individualized therapy.

Differential patterns of serum brain-derived neurotrophic factor levels in alcoholic patients with and without delirium tremens during acute withdrawal

BACKGROUND

Brain-derived neurotrophic factor (BDNF) is associated with alcohol addiction and withdrawal-related neurotoxicity. Delirium tremens (DT) is the most serious complication of alcohol withdrawal syndrome (AWS). In this study, we explored the differences in serum BDNF levels, measured at baseline and 1 week after alcohol withdrawal among alcoholic patients with and without DT.

METHODS

Sixty-five inpatients, fulfilling the DSM-IV criteria of alcohol dependence and admitted for alcohol detoxification, as well as 39 healthy control subjects were enrolled. The alcoholic patients were divided by the appearance of DTs into the DT group (n = 25) and non-DT group (n = 40). We collected blood samples of the patient groups on the first and seventh days of alcohol withdrawal and measured serum BDNF levels by sandwich enzyme-linked immunosorbent assay.

RESULTS

Serum BDNF levels differed significantly among the three groups: (i) control group 14.8 ± 4.7 ng/ml; (ii) non-DT group 12.3 ± 3.3 ng/ml; (iii) DT group 6.2 ± 2.6 ng/ml (p < 0.001). One week after alcohol withdrawal, the BDNF levels increased significantly for both alcoholic groups. While non-DT group had comparable BDNF levels (13.4 ± 3.5 ng/ml) with controls, the DT group still exhibited lower levels (8.9 ± 4.4 ng/ml).

CONCLUSIONS

This study suggests chronic drinking leads to a reduction in BDNF levels, and patients with more deficient BDNF expression are vulnerable to the development of DTs. Additionally, BDNF levels elevated after prompt alcohol detoxification treatment. These findings indicate that BDNF could involve modifying the phenotypes of AWS as well as the pertinent neuroadaptive processes of alcohol dependence.