Risk Assessment of Moderate to Severe Alcohol Withdrawal-Predictors for Seizures and Delirium Tremens in the Course of Withdrawal
Risk Assessment of Moderate to Severe Alcohol Withdrawal-Predictors for Seizures and Delirium Tremens in the Course of Withdrawal
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DOI：
10.1093/alcalc/agr053
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发表时间：
2011-07-01
影响因子：
2.8
通讯作者：
Zilker, Thomas
中科院分区：
文献类型：
--
作者：
Eyer, Florian;Schuster, Tibor;Zilker, Thomas
目的：在一个接受酒精戒断综合征（AWS）治疗的大型住院患者队列（n = 827）中，建立中重度AWS期间戒断性癫痫发作（WS）和谵妄发作（DT）的预测模型。方法：重新分析2000年至2009年期间接受治疗的队列研究人群。所有患者均接受了评分指导和自动触发的AWS治疗。采用逐步变量选择程序进行多变量二元logistic回归模型，提供比值比（OR）估计值。结果如下：在多变量回归分析中，AWS治疗期间WS的显著预测因素是入院后戒断严重程度的延迟高峰[OR/10 h：1.23; 95%置信区间（CI）：1.1-1.4; P < 0.001）]，患者病史中结构性脑损伤的患病率（OR 6.5; 95% CI：3.0-14.1; P < 0.001）; WS为入院原因（OR 2.6; 95% CI：1.4-4.8; P = 0.002）。入院时DT发生的重要预测因素是低血钾（OR/1 mmol/l 0.33; 95% CI：0.17-0.65; P = 0.001），血小板计数降低（OR/100.000 0.42; 95% CI：0.26-0.69; P = 0.001）和脑结构病变患病率（OR 5.8; 95% CI：2.6-12.9; P < 0.001）。结论：在这个大型的回顾性队列中，入院时一些容易确定的参数可能有助于预测WS或DT发生的复杂酒精戒断过程。使用提供的列线图，临床医生可以估计患者在戒断过程中发生WS或DT的可能性百分比。在病人的病史中，结构性脑损伤的患病率确实有力地证明了对病人的仔细观察。
Aims: To develop a prediction model for withdrawal seizures (WS) and delirium tremens (DT) during moderate to severe alcohol withdrawal syndrome (AWS) in a large cohort of inpatients treated for AWS (n = 827). Methods: Re-analysis of a cohort study population treated between 2000 and 2009. All patients received a score-guided and symptom-triggered therapy for AWS. Multivariable binary logistic regression models with stepwise variable selection procedures were conducted providing odds ratio (OR) estimates. Results: In the multivariable regression, significant predictors of WS during AWS therapy were a delayed climax of withdrawal severity since admission [OR/10 h: 1.23; 95% confidence interval (CI): 1.1-1.4; P < 0.001)], prevalence of structural brain lesions in the patient's history (OR 6.5; 95% CI: 3.0-14.1; P < 0.001) and WS as the cause of admittance (OR 2.6; 95% CI: 1.4-4.8; P = 0.002). Significant predictors at admission for the occurrence of DT were lower serum potassium (OR/1 mmol/l 0.33; 95% CI: 0.17-0.65; P = 0.001), a lower platelet count (OR/100.000 0.42; 95% CI: 0.26-0.69; P = 0.001) and prevalence of structural brain lesions (OR 5.8; 95% CI: 2.6-12.9; P < 0.001). Conclusion: In this large retrospective cohort, some easily determinable parameters at admission may be useful to predict a complicated course of alcohol withdrawal regarding the occurrence of WS or DT. Using the provided nomograms, clinicians can estimate the percentage likelihood of patients to develop either WS or DT during their course of withdrawal. Prevalence of structural brain lesions in the patient's history does strongly warrant a careful observation of patients.