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Original Research: Sleep Disorders |

Obesity as an Effect Modifier in Sleep-Disordered Breathing and Postcardiac Surgery Atrial Fibrillation

Roop Kaw, MD; Samer El Zarif, MD; Lu Wang, MS; James Bena, MS; Eugene H. Blackstone, MD; Reena Mehra, MD
Author and Funding Information

FUNDING/SUPPORT: This study was supported by the National Institutes of Health [Grants NHLBI R01 HL109493, R21 HL108226 to R. M].

aSleep Disorders Center, Neurologic Institute, Cleveland Clinic, Cleveland, OH

bDepartment of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

cQuantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

dRespiratory Institute and Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH

eHospital Medicine and Outcomes Research, Anesthesiology, Cleveland Clinic, Cleveland, OH

fThoracic and Cardiovascular Surgery and Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH

CORRESPONDENCE TO: Reena Mehra, MD, Cleveland Clinic Foundation, Sleep Center, Neurologic Institute, 9500 Euclid Ave, Cleveland, OH 44195


Copyright 2017, American College of Chest Physicians. All Rights Reserved.


Chest. 2017;151(6):1279-1287. doi:10.1016/j.chest.2017.03.006
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Background  Because the interrelationships of objectively ascertained sleep-disordered breathing (SDB), postcardiac surgery atrial fibrillation (PCSAF), and obesity remain unclear, we aimed to further investigate the interrelationships in a clinic-based cohort.

Methods  Patients with polysomnography and cardiac surgery (coronary artery bypass surgery and/or valvular surgery) within 3 years, from January 2009 to January 2014, were identified, excluding those with preexisting atrial fibrillation. Logistic models were used to determine the association of SDB (apnea hypopnea index [AHI] per 5-unit increase) and secondary predictors (central sleep apnea [CSA] [central apnea index ≥ 5] and oxygen desaturation index [ODI]) with PCSAF. Models were adjusted for age, sex, race, BMI, and hypertension. Statistical interaction and stratification by median BMI was performed. ORs and 95% CIs are presented.

Results  There were 190 patients who comprised the analytic sample (mean age, 60.6 ± 11.4 years; 36.1% women; 80% white; BMI, 33.3 ± 7.5 kg/m2; 93.2% had an AHI ≥ 5; 30% had PCSAF). Unlike unadjusted analyses (OR, 1.06; 95% CI, 1.01-1.1), in the adjusted model, increasing AHI was not significantly associated with increased odds of PCSAF (OR, 1.04; 95% CI, 0.98-1.1). Neither CSA nor ODI was associated with PCSAF. A significant interaction with median BMI was noted (P = .015). Effect modification by median BMI was observed; those with a higher BMI > 32 kg/m2 had 15% increased odds of PCSAF (OR, 1.15; 95% CI, 1.05-1.26; P < .003).

Conclusions  SDB was significantly associated with PCSAF in unadjusted analyses, but not after taking into account obesity; those with both SDB and obesity may represent a vulnerable subgroup to target to reduce PCSAF and its associated morbidity.

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