Obesity hypoventilation syndrome (OHS) is frequently misdiagnosed and undertreated, increasing the risk of perioperative complications. We aimed to determine the predictors of OHS and to develop and validate a novel nomogram and online calculator for identifying patients at risk of OHS in bariatric surgery candidates. We retrospectively analyzed the data of patients undergoing bariatric surgery between March 2017 and June 2020. Predictors were identified using univariate and multivariate analyses to establish the nomogram. The discriminative ability, calibration, and clinical value of the nomograms were tested using C-statistics, calibration plots, and decision curve analysis. The nomogram was internally validated using bootstrap resampling. A total of 577 patients were enrolled, and OHS was presented in 17.9% (103/577). Body mass index (BMI) (odds ratio [OR], 1.11; 95% confidence interval (CI), 1.04-1.18; p = 0.001), neck circumference (OR, 1.09; 95% CI, 1.01-1.18; p = 0.035), type 2 diabetes (T2D) (OR, 2.02; 95% CI, 1.17-3.45; p = 0.011), serum bicarbonate (OR, 1.47; 95% CI, 1.30-1.67; p < 0.001), and C-reactive protein (CRP) (OR, 1.03; 95% CI, 1.01-1.06; p = 0.017) were independent risk factors for OHS and incorporated to develop the nomogram. The nomogram revealed good discrimination, with a C-index of 0.830 (95% CI: 0.784-0.876) (0.8227 through internal validation), and good calibration. Decision curve analysis further confirmed the nomogram's clinical usefulness. The novel nomogram and online calculator provided an excellent preoperative individualized prediction of OHS in patients undergoing bariatric surgery, hereby potentially assisting clinicians and surgeons in the early detection and intensive monitoring of OHS.
Read full abstract