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Original Research |

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

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

Journal Subject Codes: Sleep apnea, atrial fibrillation, cardiac surgery

Summary conflict of interest statement

RM has received NIH funding for which she has served as Principal Investigator (NHLBI RO1 1 R01 HL 109493, R21 HL108226). Her institution has received positive airway pressure machines and equipment from Philips Respironics for use in NIH-funded research. She serves as the Associate Editor for the journal CHEST. She has received royalties from Up to Date.

Funding Sources:

Supported by NIH HL079114 (RM) and NIH HL109493 (RM).

1Hospital Medicine, Cleveland Clinic, Cleveland, OH

2Sleep Disorders Center, Neurologic Institute, Cleveland Clinic, Cleveland, OH

3Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH

Corresponding author: Reena Mehra, MD, MS Cleveland Clinic Foundation Sleep Center, Neurologic Institute 9500 Euclid Avenue Cleveland, OH 44195.


Copyright 2017, . All Rights Reserved.


Chest. 2017. doi:10.1016/j.chest.2017.03.006
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Abstract

Introduction  As the inter-relationships of objectively-ascertained sleep disordered breathing (SDB), post-cardiac surgery atrial fibrillation (PCSAF) and obesity remain unclear; we aimed to further investigate in a clinic-based cohort.

Methods  Patients with polysomnography (PSG) 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 pre-existing AF. 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, body mass index (BMI) and hypertension. Statistical interaction and stratification by median BMI was performed. Odds ratios and 95% confidence intervals are presented.

Results  190 patients comprised the analytic sample; age: 60.6±11.4 years, 36.1% females, 80% white, BMI:33.3±7.5 kg/m2, 93.2% had AHI >5 and 30% with PCSAF. Unlike unadjusted analyses (OR=1.06, 1.01-1.1), in the adjusted model, increasing AHI was not significantly associated with increased odds of PCSAF: OR=1.04 (0.98, 1.1). Neither CSA nor ODI was associated with PCSAF. A significant interaction with median BMI was noted (p=0.015). Effect modification by median BMI was observed; those with a higher BMI>32 kg/m2 had 15% increased odds of PCSAF: OR=1.15 (1.05, 1.26; P<0.003).

Conclusion  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 in order to reduce PCSAF and its associated morbidity.


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