Xingjia Hu,1,2,* Yating You,2,* Hui Wang,2 Yiqing Zheng,1,3 Ying Wang2 

1The First Affiliated Hospital of Jinan University, Guangzhou, People’s Republic of China; 2Department of Otolaryngology Head and Neck Surgery, Changde Hospital, Xiangya School of Medicine, Central South University, Changde, People’s Republic of China; 3Department of Otolaryngology-HNS, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yiqing Zheng, Department of Otolaryngology-HNS, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang west Road, Guangzhou, 510120, People’s Republic of China, Email zhengyiq@mail.sysu.edu.cn Ying Wang, Department of Otolaryngology Head and Neck Surgery, Changde Hospital, Xiangya School of Medicine, Central South University, No. 818 Renmin Road, Changde, 415000, People’s Republic of China, Tel/Fax +86-0731-7788212, Email lhly_1018@163.com

Background: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but its long-term efficacy is limited by poor patient adherence. This study aimed to develop and validate a predictive nomogram for CPAP non-adherence in patients with OSA.
Methods: This is a secondary analysis of a retrospective study. A cohort of 695 Danish patients with OSA were followed for 3 years after initiating CPAP therapy. Independently associated factors were evaluated using multivariate Cox regression, and then nomogram predicting adherence to CPAP use were constructed. The discrimination of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA).
Results: Pulmonary disease, oxygen desaturation index (ODI), Epworth Sleepiness Score (ESS) and severity of OSA were identified as predictors and incorporated into the nomogram. The nomogram demonstrated good discrimination with concordance index in training dataset (0.73, 95% CI: 0.69– 0.78) and validation dataset (0.72, 95% CI: 0.66– 0.79). ROC curve, calibration curve, and DCA indicated the nomogram had good clinical utility.
Conclusion: This study provided an effective nomogram for predicting CPAP non-adherence in OSA patients.

Keywords: continuous positive airway pressure, obstructive sleep apnea, nomogram, patient adherence, predictive model