Diagnosed sleep apnea and cardiovascular disease in atrial fibrillation patients: The role of measurement error from administrative data

Rachel P. Ogilvie, Richard F. Maclehose, Alvaro Alonso, Faye L. Norby, Kamakshi Lakshminarayan, Conrad Iber, Lin Y. Chen, Pamela L. Lutsey

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Atrial fibrillation and obstructive sleep apnea are common conditions, but little is known about obstructive sleep apnea and cardiovascular risk among atrial fibrillation patients. Methods: Using the Truven Health MarketScan databases, we constructed a prospective cohort of atrial fibrillation patients from 2007 to 2014. Atrial fibrillation, obstructive sleep apnea, stroke, myocardial infarction, and confounders were defined using the International Classification of Disease-9-CM codes. We matched individuals with an obstructive sleep apnea diagnosis with up to five individuals without a diagnosis by age, sex, and enrollment date. Cox proportional hazards models adjusted for confounders and high-dimensional propensity scores. We included migraines as a control outcome. Bias analysis used published sensitivities and specificities to generate rate ratios adjusted for obstructive sleep apnea misclassification. Results: We matched 56,969 individuals with an obstructive sleep apnea diagnosis to 323,246 without. During a mean follow-up of 16 months, 3234 incident strokes and 4639 incident myocardial infarctions occurred. After adjustment, obstructive sleep apnea diagnosis was strongly associated with reduced risk of incident stroke (hazard ratio = 0.48, 95% confidence interval = 0.43, 0.53) and myocardial infarction (0.40, [0.37, 0.44]) and a smaller reduced risk of migraines (0.82, [0.68, 0.99]). Bias analysis produced wide-ranging or inestimable rate ratios adjusted for misclassification of obstructive sleep apnea. Conclusions: Obstructive sleep apnea diagnosis in atrial fibrillation patients was strongly associated with reduced risk of incident cardiovascular disease. We discuss misclassification, selection bias, and residual confounding as potential explanations.

Original languageEnglish (US)
Pages (from-to)885-892
Number of pages8
JournalEpidemiology
Volume30
Issue number6
DOIs
StatePublished - Nov 1 2019

Bibliographical note

Publisher Copyright:
© 2019 Wolters Kluwer Health, Inc. All rights reserved.

Keywords

  • Administrative data
  • Atrial fibrillation
  • Cardiovascular disease
  • Measurement error
  • Sleep apnea
  • Stroke

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