Impact of Phenobarbital-Based Regimens on Clinical Outcomes in Critically Ill Patients with Alcohol Withdrawal Syndrome: A Propensity Score-Matched Cohort Study
Abstract
Objectives: Alcohol withdrawal syndrome (AWS) in the intensive care unit (ICU) often requires escalating sedative therapy and is associated with respiratory complications and prolonged length of stay (LOS). Phenobarbital (PHB) is increasingly used for benzodiazepine (BZD)-refractory AWS, yet comparative effectiveness data in critically ill patients remain limited. We evaluated whether PHB-based regimens were associated with differences in LOS and early safety outcomes compared with non-PHB strategies.
Design: Multicenter retrospective cohort study using multiple imputation and propensity score matching to estimate the average treatment effect in the control (ATC).
Setting: ICUs at four Mayo Clinic sites from June 30, 2017 to July 1, 2024.
Patients: Adults (≥18 years) admitted with AWS (CIWA-Ar ≥10) who received either a PHB-based or non-PHB pharmacologic strategy. Patients admitted after surgical intervention were excluded. The matched cohort included 1,216 patients (PHB n=345; non-PHB n=871).
Measurements and Main Results: Primary outcomes were ICU and hospital LOS. Safety outcomes included hypotension and respiratory compromise (new intubation or aspiration) within 48 hours of treatment initiation. In adjusted ATC analyses, PHB was not associated with significant differences in ICU LOS (+1.18 days; 95% CI −0.08 to 2.44; p=0.067) or hospital LOS (+1.39 days; 95% CI −0.87 to 3.65; p=0.228). Adjusted odds of hypotension and intubation were similar between groups. Aspiration within 48 hours occurred less frequently with PHB (7.8% vs 12.6%; p=0.017). CIWA-Ar reductions at 24 and 48 hours were comparable.
Conclusions: In this multicenter ICU cohort, PHB-based regimens were safe and effective for AWS management but were not associated with improved LOS in an all-comers population. Pragmatic randomized trials are needed to define effectiveness, cost-effectiveness, and identify subgroups most likely to benefit.

