Hartz A J, Guse C, Kajdacsy-Balla A
College of Medicine, University of Iowa, Dept. of Family Medicine, Iowa City 52242-1097, USA.
J Clin Epidemiol. 1997 Dec;50(12):1357-68. doi: 10.1016/s0895-4356(97)00199-6.
This study derived and evaluated a model that used results of commonly performed laboratory tests to identify men who are heavy drinkers.
The results of 40 commonly available laboratory tests were obtained on a diverse sample of 426 heavy drinkers and 188 light drinkers. A logistic regression equation for identifying heavy drinkers was derived in a training data set of 411 subjects and tested in a validation data set of 203 subjects.
Ten laboratory measurements were included in the final regression equation: chloride, sodium, ratio of direct to total bilirubin level, blood urea nitrogen, high density lipoproteins, monocyte count, phosphorus, platelets, aspartate aminotransferase, and mean corpuscular hemoglobin. In the validation data this model correctly identified 98% of the 161 heavy drinkers and 95% of the 42 light drinkers. Other models reported in previous literature were applied to these subjects and did not perform as well. The model performed better for subjects of lower socioeconomic status.
The laboratory tests in our model may help identify heavy drinkers. The performance of models to identify heavy drinkers depends on the demographic characteristics of the subjects.
本研究推导并评估了一个利用常规实验室检测结果来识别重度饮酒男性的模型。
对426名重度饮酒者和188名轻度饮酒者的不同样本进行了40项常规可用实验室检测。在一个由411名受试者组成的训练数据集中推导出用于识别重度饮酒者的逻辑回归方程，并在一个由203名受试者组成的验证数据集中进行测试。
最终回归方程纳入了10项实验室测量指标：氯化物、钠、直接胆红素与总胆红素水平之比、血尿素氮、高密度脂蛋白、单核细胞计数、磷、血小板、天冬氨酸转氨酶和平均红细胞血红蛋白含量。在验证数据中，该模型正确识别出了161名重度饮酒者中的98%以及42名轻度饮酒者中的95%。先前文献中报道的其他模型应用于这些受试者时表现不如该模型。该模型在社会经济地位较低的受试者中表现更佳。
我们模型中的实验室检测可能有助于识别重度饮酒者。识别重度饮酒者的模型表现取决于受试者的人口统计学特征。
