Abstract | April 4, 2022

How Much Can your Electrocardiogram Tell You of Obstructive Sleep Apnea?

Presenting Author: Allen Gee, BS, MS, Medical Student, 1st Year, Nova Southeastern University School of Osteopathic Medicine, Davie, Florida

Coauthors: Constantine E. Kosmas, MD, Cardiology, Attending, Montefiore Medical Center, New York, NY; Arthur Tarricone, DPM/MPH, Podiatry, PGY1, SUNY Downstate Medical Center, New York, NY; Eliscer Guzman, MD, Cardiology, Attending, Montefiore Medical Center, New York, NY

Learning Objectives

  1. Examine the association between different electrocardiogram patterns with obstructive sleep apnea;
  2. Differentiate the ECG patterns that present in OSA versus non OSA patients.

Background: Obstructive Sleep Apnea (OSA) continues to be a prevalent, life-limiting, disorder around the world. Early diagnosis of the condition has shown favorable outcomes; however, standard diagnostic procedures are lengthy and expensive, with a primary reliance on polysomnography tests. Electrocardiograms have been speculated to provide additional surveillance for OSA through the identification of the rSr’ pattern in leads V1-V2; however, research on this topic remains limited.

Methods: The following study retrospectively analyzed a patient database from a single outpatient clinic in New York City. OSA was confirmed through the Apnea-Hypopnea Index derived from polysomnography and electrocardiograms were abstracted through electronic medical records. Multivariate logistic regression was performed to determine associated factors of OSA.

Results: 670 consecutive patients of Hispanic/Latino heritage (131 with OSA and 539 without OSA), with a mean age of 62.06 ± 10.11 years were included in the study. The frequency of rSr’ pattern in leads V1- V2 in sleep apneic patients was significantly higher than in non-sleep apneic patients (29.77% vs 20.41%; p<0.05). OSA patients also exhibited higher incidence of hypertension (89.3% vs 5.0%; P<0.01), longer QRS duration (92.59ms vs 90.48ms; p<0.05), and increased rate of S waves in leads V5-V6 (75.57% vs 64.38%; p<0.05) compared to non-sleep apneic patients. In the final multivariate logistic regression, hypertension, overweight/obesity (BMI ≥25 kg/m2) and presence of rSr’ in leads V1-V2 were predictors for OSA.

Conclusion: These findings suggest that the presence of an rSr’ electrocardiographic pattern in leads V1- V2 patterns may be a predictive tool for the diagnosis of OSA.

References and Resources:

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