Objectives: To construct a nomogram prediction model using common preoperative indicators for early weight loss (EWL) 1 year after laparoscopic sleeve gastrectomy (LSG). Methods: Relevant data of obese patients who had undergone LSG from January 2015 to May 2022 in Fujian Medical University Union Hospital and Quanzhou First Hospital Affiliated Fujian Medical University were analyzed. Patients with a history of major abdominal surgery, severe gastroesophageal reflux disease, pregnancy within 1 year after surgery, or who were lost to follow-up were excluded, resulting in a total of 200 patients in the study (190 from Fujian Medical University Union Hospital and 10 from Quanzhou First Hospital Affiliated Fujian Medical University). The participants were 51 men and 149 women of a mean age 29.9±8.2 years and a body mass index (BMI) 38.7±6.5 kg/m2. All patients in this group underwent standardized LSG procedure. Achieving ideal weight (BMI≤25 kg/m2) 1 year after LSG was defined as goal of EWL. Logistic regression analyses were performed to identify factors that independently influenced EWL. These factors were incorporated into the nomogram model. Receiver operating characteristic (ROC) curves (the larger the area under the curve [AUC], the better the predictive ability and accuracy of the model), likelihood ratio test (higher likelihood ratio indicates greater model homogeneity), decision curve analysis (higher net benefit indicates a better model), Akaike information criterion (AIC; smaller AIC indicates a better model), and Bayesian information criterion (BIC; smaller BIC indicates a better model) were used to validate the predictive ability of the column line diagram model. Results: In this study of 200 obese patients who underwent LSG surgery, 136 achieved EWL goal, whereas the remaining 64 did not. The rate of EWL goal achievement of the entire group was 68.0%. Compared with patients who did not achieve EWL goal, those who did had lower BMI, alanine transaminase, aspartate transaminase, triglycerides, and higher cholesterol. Additionally, the proportion of female was higher and the proportions of patients with fatty liver and hypertension lower in those who achieved EWL goal (all P<0.05). Univariate and multivariate logistic regression analysis revealed that preoperative BMI (OR=0.852, 95%CI: 0.796-0.912, P<0.001), alanine transaminase (OR=0.992, 95%CI: 0.985-0.999, P=0.024), presence of fatty liver (OR=0.185, 95%CI: 0.038-0.887, P=0.035) and hypertension (OR=0.374, 95%CI: 0.144-0.969, P=0.043) were independently associated with failure to achieve EWL goal. Cholesterol (OR=1.428, 95%CI: 1.052-1.939, P=0.022) was independently associated with achieving EWL goal. We used the above variables to establish an EWL nomogram model. ROC analysis, the likelihood ratio test, decision curve analysis, and AIC all revealed that the predictive value of the model was better than that of BMI alone (nomogram model vs. BMI: area under the curve 0.840 vs. 0.798, P=0.047; likelihood ratio: 58.785 vs. 36.565, AIC: 193.066 vs. 207.063, BIC: 212.856 vs. 213.660). Conclusion: Our predictive model is more accurate in predicting EWL after LSG compared with using BMI.
目的： 构建一个基于常见术前指标预测肥胖患者腹腔镜袖状胃切除术（LSG）后早期（1年内）减重效果的列线图模型。 方法： 回顾性分析2015年1月至2022年5月于福建医科大学附属协和医院和福建医科大学附属泉州第一医院行LSG的肥胖症患者的临床病例资料。排除腹部大手术史、严重胃食管反流病、术后1年内怀孕及失访患者后，共200例患者入组（福建医科大学附属协和医院190例，福建医科大学附属泉州第一医院10例），其中男性51例，女性149例，年龄（29.9±8.2）岁，体质指数（BMI）为（38.7±6.5）kg/m2。本组患者均接受标准化程序的LSG手术。将LSG术后1年达到理想体质量，即BMI≤25 kg/m2定义为早期减重达标。采用单因素和多因素分析患者基本资料、临床指标、术前血液学指标以及合并症情况与LSG术后早期减重达标的关系，并将相关因素纳入列线图预测模型。采用受试者工作特征（ROC）曲线［曲线下面积（AUC）越大，模型的预测能力和预测准确性越好］、似然比检验（似然比越高，模型同质性越强）、决策曲线分析法（DCA；净获益越高，模型越好）、赤池信息量准则（AIC值；AIC值越小，模型拟合越好）及贝叶斯信息量准则（BIC值；BIC值越小，模型拟合越好）验证列线图模型的预测性能。 结果： 200例接受LSG手术的肥胖患者中，早期减重达标136例（68.0%）。与未早期减重达标组（64例）相比，早期减重达标组患者BMI更小，丙氨酸转氨酶（ALT）、天冬氨酸转氨酶（AST）、甘油三酯（TG）水平更低，总胆固醇（CHOL）水平更高；女性占比更高，合并脂肪肝及高血压比率更低（均P<0.05）。多因素logistic回归分析显示，术前BMI（OR=0.852，95%CI：0.796~0.912，P<0.001）、ALT（OR=0.992，95%CI：0.985~0.999，P=0.024）及合并脂肪肝（OR=0.185，95%CI：0.038~0.887，P=0.035）和高血压（OR=0.374，95%CI：0.144~0.969，P=0.043）是阻碍早期减重达标的独立影响因素，CHOL（OR=1.428，95%CI：1.052~1.939，P=0.022）是有利于早期减重达标的独立影响因素。基于以上变量，我们建立了减重效果列线图预测模型。ROC曲线分析、决策曲线分析、似然比检验、赤池信息量准则（AIC值）及贝叶斯信息量准则（BIC值）均显示，列线图模型预测性能明显优于BMI（AUC值：0.840比0.798，P=0.047；似然比：58.785比36.565，AIC值：193.066比207.063，BIC值：212.856比213.660）。 结论： 相较于只基于BMI的预测模型，本研究构建的术前指标预测模型可以更有效地预测LSG术后早期减重达标。.