Onken J E, Brazer S R, Eisen G M, Williams D M, Bouras E P, DeLong E R, Long T T, Pancotto F S, Rhodes D L, Cotton P B
Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA.
Am J Gastroenterol. 1996 Apr;91(4):762-7.
Accurate preoperative prediction of choledocholithiasis is essential in order to minimize patient risk and curtail health care expenditures. This study was designed to identify independent risk factors for choledocholithiasis in patients who had undergone cholecystectomy for symptomatic cholelithiasis and to develop a predictive model based on those factors.
The charts of 1264 consecutive patients who had undergone cholecystectomy at one of three North Carolina hospitals between January 1, 1989 and December 31, 1991 were reviewed; 465 of these patients had confirmed presence or absence of choledocholithiasis by cholangiography and/or common bile duct exploration and were eligible for analysis. Candidate predictor variables included age and maximum preoperative values for each of the following: temperature, alkaline phosphatase, bilirubin, AST, amylase, white blood cell count, and common bile duct diameter. Model development and validation were conducted using standard data-splitting (60% "training," 40% "test") and logistic regression techniques.
Choledocholithiasis was confirmed in 115 (25%) of the 465 eligible patients. Univariate analysis identified bilirubin, common bile duct diameter, AST, temperature, alkaline phosphatase, and age as predictors. Multivariable analysis subsequently identified bilirubin, common bile duct diameter, AST, alkaline phosphatase, and age as independent predictors of choledocholithiasis. A final model containing these variables (except age, whose contribution to the model was small) accurately predicted choledocholithiasis (c-index = 0.76).
Accurate estimates of choledocholithiasis risk can be made using maximum preoperative bilirubin, common bile duct diameter, AST, and alkaline phosphatase values. Use of the model may help physicians select those patients with symptomatic cholelithiasis who would most likely benefit from further investigation to exclude choledocholithiasis.
准确的术前胆总管结石预测对于降低患者风险和减少医疗费用至关重要。本研究旨在确定有症状胆结石行胆囊切除术患者胆总管结石的独立危险因素，并基于这些因素建立预测模型。
回顾了1989年1月1日至1991年12月31日期间在北卡罗来纳州三家医院之一接受胆囊切除术的1264例连续患者的病历；其中465例患者通过胆管造影和/或胆总管探查确诊有无胆总管结石，符合分析条件。候选预测变量包括年龄以及以下各项的术前最高值：体温、碱性磷酸酶、胆红素、谷草转氨酶、淀粉酶、白细胞计数和胆总管直径。使用标准数据拆分（60%“训练”，40%“测试”）和逻辑回归技术进行模型开发和验证。
465例符合条件的患者中，115例（25%）确诊有胆总管结石。单因素分析确定胆红素、胆总管直径、谷草转氨酶、体温、碱性磷酸酶和年龄为预测因素。多因素分析随后确定胆红素、胆总管直径、谷草转氨酶、碱性磷酸酶和年龄为胆总管结石的独立预测因素。包含这些变量的最终模型（年龄除外，其对模型的贡献较小）准确预测了胆总管结石（c指数 = 0.76）。
使用术前最高胆红素、胆总管直径、谷草转氨酶和碱性磷酸酶值可准确估计胆总管结石风险。该模型的应用可能有助于医生选择那些有症状胆结石且最有可能从进一步检查以排除胆总管结石中获益的患者。
