ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Addictive Disorders
A Clinical Prediction Model for Delirium Tremens: Development and Validation in Alcohol-Dependent Patients Using Multivariable Logistic Regression
Provisionally accepted
- The Fourth People's Hospital of Chengdu, Chengdu, China
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Background: Delirium tremens (DT) is a severe complication of alcohol withdrawal. This study aimed to develop and validate a prediction model for DT risk in hospitalized patients with alcohol dependence, using routine laboratory indicators. Methods: We retrospectively analyzed 347 patients with alcohol dependence admitted to the Addiction Medicine Department of a tertiary psychiatric hospital from 2020 to 2024. The primary outcome was DT occurrence. A prediction model was constructed using logistic regression, with data split into training (70%) and validation (30%) sets by random sampling. Model performance was evaluated via the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). Results: Of 347 patients, 118 (34%) developed DT. LASSO regression identified 11 predictors: history of DT, ammonia, creatinine, uric acid, total bilirubin (Tbiliary), albumin (ALB), gamma-glutamyl transferase (GGT), chloride (Cl), free triiodothyronine (Free_T3), free thyroxine (Free_T4), neutrophil percentage (NEU%), and red blood cell (RBC) count. Logistic regression confirmed that history of DT, ammonia, creatinine, ALB, Free_T3, NEU%, and RBC were independent risk factors (P < 0.05). The model demonstrated robust performance: AUC = 0.9881 [95% CI: 0.9794–0.9967] in the training set and 0.9599 [95% CI: 0.9142–1.0000] in the validation set, with high net benefit in DCA. Conclusions: This model, incorporating readily available biomarkers and clinical history, effectively predicts DT risk. Limitations include its retrospective design (potential selection bias) and exclusion of clinical scales (e.g., CIWA-Ar). Prospective multicenter studies are needed to validate its generalizability.
Keywords: alcohol dependence, Clinical prediction model, delirium tremens, DT, Logistic regression
Received: 25 Sep 2025; Accepted: 09 Feb 2026.
Copyright: © 2026 zhong, Huang and yao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: xudong yao
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