Nomogram to diagnosis of obstructive sleep apnoea‐hypopnoea syndrome in high‐risk Chinese adult patients

• DOI: 10.1111/crj.13682
• Publication Date: 2023-08-03T04:44:17Z
• Authors: Jie Liu; Feng Pang; Xiaofeng Huang; Xiangmin Zhang; Minmin Lin; Wenmin Deng; Tianrun Liu; Zhen Long
• Keywords: Nomogram; Stepwise regression; Univariate; Univariate analysis; Clinical prediction rule

Many scales are designed to screen for obstructive sleep apnoea-hypopnoea syndrome (OSAHS); however, there is a lack of an efficiently and easily diagnostic tool, especially Chinese. Therefore, we conduct cross-sectional study in China develop validate efficient simple clinical model help patients at risk OSAHS.This based on 782 high-risk (aged >18 years) admitted the Sleep Medicine department Sixth Affiliated Hospital, Sun Yat-sen University from 2015 2021. Totally 34 potential predictors were evaluated. We divided all into training validation dataset model. The univariable multivariable logistic regression used build nomogram was finally built.Among 602 with median age 46 (37, 56) years, 23.26% women. After selecting using univariate model, 15 factors identified. further stepwise method final five factors: age, BMI, total bilirubin levels, high Berlin score, symptom morning dry mouth or breathing. AUC 0.780 (0.711, 0.848), sensitivity 0.848 (0.811, 0.885), specificity 0.629 (0.509, 0.749), accuracy 0.816 (0.779, 0.853). discrimination ability had been verified dataset. Finally, established base above model.We developed validated predictive acquire diagnose OSAHS patient population well discriminant ability. Accordingly,