Development and Validation of a Diagnostic Nomogram for Predicting Hypertension in Patients With Obstructive Sleep Apnea at High Altitude

Obstructive sleep apnea (OSA) has been established as one of the independent risk factors for hypertension, and its coexistence substantially raises the risk of cardiovascular incidents. However, existing clinical predictive models mainly focus on populations in plain areas and fail to take altitude-specific factors into account. The objective of this study was straightforward: to develop and validate a nomogram that can predict hypertension in patients with OSA syndrome living at mid- to high altitudes. We carried out a detailed retrospective review of 1505 patient records from January 2021 to February 2024, all newly diagnosed with OSA through polysomnography (PSG). After applying the inclusion and exclusion criteria, 694 patients were included in the training cohort, and 358 patients were included in the validation cohort. Candidate predictors were selected using LASSO logistic regression, and a nomogram was subsequently established through multivariable logistic regression. The area under the receiver operating characteristic curve, calibrated curves, and decision curve analysis were employed to comprehensively evaluate the model's discriminative capacity, calibration, and clinical applicability. Six variables were identified as risk factors for OSA patients with hypertension, including age, BMI, tonsillar hypertrophy, IVSd, LVPWD, and T90. The nomogram was developed using these variables. The training and validation sequences demonstrate their effectiveness. The AUC of the training and validation cohort was 0.78 (95% CI: 0.74-0.81) and 0.72 (95% CI: 0.66-0.77), respectively. The development of this nomogram can help identify individuals with a higher likelihood of hypertensive conditions among OSA patients in mid- to high-altitude regions, thereby providing a basis for early clinical identification and intervention.