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.

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.