文献类型：期刊文献

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

作者：Shi, Wenjia[1];Wang, Ruonan[1];Liu, Dingyuan[2];Sun, Hongyan[1];Qin, Yahong[1];Du, Bang[1];Zhang, Rui[1];Tang, Haiyang[2];Chu, Aiai[1]

第一作者：Shi, Wenjia

通信作者：Chu, AA[1]

机构：[1]Gansu Univ Chinese Med, Gansu Prov Hosp, Dept Echocardiog, Clin Med Sch 1, Lanzhou, Peoples R China;[2]Guangzhou Med Univ, Guangzhou Inst Resp Hlth, Dept Clin Lab,Affiliated Hosp 1, State Key Lab Resp Dis,Natl Clin Res Ctr Resp Dis, Guangzhou, Guangdong, Peoples R China

第一机构：甘肃中医药大学

通信机构：[1]corresponding author), Gansu Univ Chinese Med, Gansu Prov Hosp, Dept Echocardiog, Clin Med Sch 1, Lanzhou, Peoples R China.|[10735]甘肃中医药大学;

年份：2025

卷号：2025

期号：1

外文期刊名：INTERNATIONAL JOURNAL OF HYPERTENSION

收录：;Scopus(收录号：2-s2.0-105025242964);WOS:【SCI-EXPANDED(收录号:WOS:001641297500001)】；

基金：The research team primarily consists of all members of the Ultrasound Department at the Gansu Provincial Hospital. We express our sincere gratitude to all participating patients and medical staff for their support, as well as to the generous funding from the various grants.

语种：英文

外文关键词：hypertension; nomogram; obstructive sleep apnea; prediction model

摘要：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.