Hyperuricemia Remission After Sleeve Gastrectomy in Chinese Patients and Establishment of a Preoperative Predictive Model: A Retrospective Cohort Study with a Mean Follow-Up of 20 Months

中国患者袖状胃切除术后高尿酸血症缓解及术前预测模型的建立:一项平均随访20个月的回顾性队列研究

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Abstract

BACKGROUND: A significant proportion of patients with obesity have comorbid hyperuricemia (HUA). However, the curative effect of sleeve gastrectomy (SG) on HUA remains debated. OBJECTIVE: To clarify the remission effect of SG on HUA, analyze potential influencing factors, and establish a predictive model using preoperative data. METHODS: Pre- and post-operative data from 130 patients with obesity and HUA who underwent SG in our hospital were collected and evaluated for the therapeutic effect on HUA. Binary logistic regression analysis was employed to screen the influencing factors and the ones with predictive value. Predictive model was constructed, then evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and internal and external validations. Complete remission of HUA was defined as a follow-up SUA level that no longer met the reference value for diagnosing HUA, i.e., an SUA concentration of <428 μmol/L (in males) or <357 μmol/L (in females), according to the reference value in our hospital's laboratory. RESULTS: The mean follow-up duration is 20.4 months. After ≥ one year post SG, the complete remission rate of HUA was 58%. Preoperative hip circumference (HC) and preoperative serum uric acid (SUA) level were found to be predictive variables, the AUC values of which, along with their combination in predicting this outcome, were 0.696, 0.731, 0.738, respectively, p >0.05. The joint predictive model was found to have a sensitivity and specificity of 0.776 and 0.738, respectively, and its reliability was confirmed by internal and external validations. CONCLUSION: Some patients can achieve HUA complete remission following SG after 1 year. Preoperative SUA concentration and HC can be utilized to predict this outcome in Chinese patients with obesity. The joint predictive model offers potentially better clinical value.

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