Sleep characteristics that predict atrial fibrilation

From www.heartrhythmjournal.com.

My comments are in italics.
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Background

The relationship between sleep disruption, independent of obstructive sleep apnea (OSA), and atrial fibrillation (AF) is unknown.

Objective

The purpose of this study was to determine whether poor sleep itself is a risk factor for AF.

Methods

We first performed an analysis of participants in the Health eHeart Study and validated those findings in the longitudinal Cardiovascular Health Study, including a subset of patients undergoing polysomnography. To determine whether the observed relationships readily translated to medical practice, we examined 2005–2009 data from the California Healthcare Cost and Utilization Project.

Results

Among 4553 Health eHeart participants, the 526 with AF exhibited more frequent nighttime awakening (odd ratio [OR] 1.47; 95% confidence interval [CI] 1.14–1.89; P = .003).

This says something about the probability of frequent nighttime awakening given AF, not the probability of developing AF given frequent nighttime awakening. It is the latter that is of interest.

 In 5703 Cardiovascular Health Study participants followed for a median 11.6 years, frequent nighttime awakening predicted a 33% greater risk of AF (hazard ratio [HR] 1.33; 95% CI 1.17–1.51; P <.001).

The hazard ratio, HR, is a measure of relative risk. It would be nice to know the increased probability of developing AF from frequent nighttime awakening. That could be small even with a high HR.

In patients with polysomnography (N = 1127), every standard deviation percentage decrease in rapid eye movement (REM) sleep was associated with a 18% higher risk of developing AF (HR 1.18; 95% CI 1.00–1.38; P = .047).

This illustrates how the HR must be interpreted with care. The model is linear, so increasing the variable of interest, frequent nighttime awakening, enough leads to certainty of developing AF. This may be a limitation of the linear form of the model that, taken to extremes, does not reflect reality.

 Among 14,330,651 California residents followed for a median 3.9 years, an insomnia diagnosis predicted a 36% increased risk of new AF (HR 1.36; 95% CI 1.30–1.42; P <.001).

Conclusion

Sleep disruption consistently predicted AF before and after adjustment for OSA and other potential confounders across several different populations. Sleep quality itself may be important in the pathogenesis of AF, potentially representing a novel target for prevention.