Dataset Information

Alcohol withdrawal syndrome in ICU patients: Clinical features, management, and outcome predictors.

ABSTRACT:

Background

Alcohol withdrawal syndrome (AWS) is a common condition in hospitalized patients, yet its epidemiology in the ICU remains poorly characterized.

Methods

Retrospective cohort of patients admitted to the Nantes University Hospital ICU between January 1, 2017, and December 31, 2019, and coded for AWS using ICD-10 criteria. The objective of the study was to identify factors associated with complicated hospital stay defined as ICU length of stay ≥7 days or hospital mortality.

Results

Among 5,641 patients admitted to the ICU during the study period, 246 (4.4%) were coded as having AWS. Among them, 42 had exclusion criteria and 204 were included in the study. The three main reasons for ICU admission were sepsis (29.9%), altered consciousness (29.4%), and seizures (24%). At ICU admission, median Cushman's score was 6 [4-9] and median SOFA score was 3 [2-6]. Delirium tremens occurred in half the patients, seizures in one fifth and pneumonia in one third. Overall, 48% of patients developed complicated hospital stay, of whom 92.8% stayed in the ICU for ≥7 days, 36.7% received MV for ≥7 days, and 16.3% died during hospital stay. By multivariable analysis, two factors were associated with complicated hospital stay: a higher number of organ dysfunctions at ICU admission was associated with a higher risk of complicated hospital stay (OR, 1.18; 95CI, 1.05-1.32, P = 0.005), whereas ICU admission for seizures was associated with a lower risk of complicated hospital stay (OR, 0.14; 95%CI, 0.026-0.80; P = 0.026).

Conclusions

AWS in ICU patients chiefly affects young adults and is often associated with additional factors such as sepsis, trauma, or surgery. Half the patients experienced an extended ICU stay or death during the hospital stay. The likelihood of developing complicated hospital stay relied on the reason for ICU admission and the number of organ dysfunctions at ICU admission.

SUBMITTER: Vigouroux A

PROVIDER: S-EPMC8687554 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWe conducted a review of all studies comparing clinical aspects of alcohol withdrawal syndrome (AWS) between men and women.MethodsFive 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.ResultsThirty-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)].ConclusionDespite 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.

Project description: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.