High Risk Characteristics for Recurrent Cardiovascular Events among Patients with Obstructive Sleep Apnoea in the SAVE Study

Weiwei Quan; Danni Zheng; R Douglas McEvoy; Ferran Barbe; Riu Chen; Zhihong Liu; Kelly Loffler; Geraldo Lorenzi-Filho; Yuanming Luo; Sutapa Mukherjee; Manjari Tripathi; Richard Woodman; Qiang Li; Xia Wang; Hisatomi Arima; Yi Xiao; Xilong Zhang; Craig S Anderson; SAVE Investigators

doi:10.1016/j.eclinm.2018.09.002

High Risk Characteristics for Recurrent Cardiovascular Events among Patients with Obstructive Sleep Apnoea in the SAVE Study

EClinicalMedicine. 2018 Sep 21:2-3:59-65. doi: 10.1016/j.eclinm.2018.09.002. eCollection 2018 Aug-Sep.

Authors

Weiwei Quan¹, Danni Zheng^{2

3}, R Douglas McEvoy^{4

5}, Ferran Barbe⁶, Riu Chen⁷, Zhihong Liu⁸, Kelly Loffler⁴, Geraldo Lorenzi-Filho⁹, Yuanming Luo¹⁰, Sutapa Mukherjee⁵, Manjari Tripathi¹¹, Richard Woodman¹², Qiang Li³, Xia Wang³, Hisatomi Arima¹³, Yi Xiao¹⁴, Xilong Zhang¹⁵, Craig S Anderson^{3

16

17}; SAVE Investigators

Affiliations

¹ Department of Cardiology, Rui Jin Hospital and Institute of Cardiovascular Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
² Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
³ The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia.
⁴ Adelaide Institute for Sleep Health, Flinders University, Adelaide, SA, Australia.
⁵ Respiratory and Sleep Services, Southern Adelaide Local Health Network, SA, Australia.
⁶ Respiratory Department, Hospital Universitari Arnau de Vilanova-Santa María, Lleida, Spain.
⁷ The Second Affiliated Hospital of Soochow University, Soochow, China.
⁸ Department of Cardiology, Fuwai Hospital, Beijing, China.
⁹ Instituto do Coracao (Incor) and Hospital Universitario, Sao Paulo, Brazil.
¹⁰ The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, Guangzhou, China.
¹¹ Neurology Department, All India Institute of Medical Sciences, Delhi, India.
¹² Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, SA, Australia.
¹³ Department of Preventive Medicine and Public Health, Fukuoka University, Fukuoka, Japan.
¹⁴ Respiratory Department, Peking University Medical College, Beijing, China.
¹⁵ The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
¹⁶ Neurology Department, Royal Prince Alfred Hospital, Sydney, NSW, Australia.
¹⁷ The George Institute China at Peking University Health Science Center, Beijing, China.

Abstract

Background: Obstructive sleep apnoea (OSA) is a common comorbidity in patients with cardiovascular (CV) disease. We aimed to identify specific OSA clinical phenotypes relating to risks of serious CV events and response to continuous positive airway pressure (CPAP) treatment.

Methods: Post-hoc analyses of the Sleep Apnea Cardiovascular Endpoints (SAVE) study in participants with moderate-to-severe OSA and coronary artery disease (CAD) and/or cerebrovascular disease (CeVD) randomised to CPAP plus usual care or usual care alone. Latent class analysis (LCA) was used to identify OSA clinical phenotypes among 2649 (out of 2687 total) patients with complete data on 19 patient-centered variables, supported by Bayesian information criteria and clinical interpretability. Cox regression models were used to evaluate risks of composite cardiac and stroke outcome events in phenotype groups. Preferential response to CPAP treatment was evaluated using interaction terms as well as the Chi-square test.

Findings: LCA identified four OSA clinical phenotypes: CAD alone and with diabetes mellitus (CAD + DM), and CeVD alone and with DM (CeVD + DM), in 39%, 15%, 37% and 9% of participants, respectively. The rates of composite CV events were the highest in CAD + DM phenotype (HR 2.08, 95% CI 1.57-2.76) and for stroke were highest in CeVD + DM phenotype (HR 6.84, 95% CI 3.77-12.42). Adherence to CPAP treatment (nil or < 4 h vs ≥ 4 h in the first two years of the study) was shown to influence the risk of composite CV outcome in the phenotypes (P-interaction = 0.04); CPAP adherent patients of the CeVD + DM phenotype had the lowest risk of CV outcome (P = 0.02).

Interpretation: High risk clinical phenotypes were identified in relation to CV events and response to CPAP treatment, which may allow improved targeting of therapies in OSA patients.

Funding: The National Health and Medical Research Council (NHMRC) of Australia, Fisher & Paykel Healthcare, and ResMed.

Keywords: Cardiovascular disease; Latent class analysis; Obstructive sleep apnoea; Phenotype; Stroke.