Obstructive Sleep Apnea Characterization: A Multimodal Cross-Recurrence-Based Approach for Investigating Atrial Fibrillation

Obstructive sleep apnea (OSA) is believed to contribute significantly to atrial fibrillation (AF) development in certain patients. Recent studies indicate a rising risk of AF with increasing OSA severity. However, the commonly used apnea-hypopnea index in clinical practice may not adequately account for the potential cardiovascular risks associated with OSA.
1) Objective:
to propose and explore a novel method for assessing OSA severity considering potential connection to cardiac arrhythmias.
2) Method:
the approach utilizes cross-recurrence features to characterize OSA and AF by considering the relationships among oxygen desaturation, pulse arrival time, and heart-beat intervals. Multinomial logistic regression models were trained to predict four levels of OSA severity and four groups related to heart rhythm issues. The rank biserial correlation coefficient,
$r_{rb}$
, was used to estimate effect size for statistical analysis. The investigation was conducted using the MESA database, which includes polysomnography data from 2055 subjects.
3) Results:
a derived cross-recurrence-based index showed a significant association with a higher OSA severity (
p

$< $
0.01) and the presence of AF (
p

$< $
0.01). Additionally, the proposed index had a significantly larger effect,
$r_{rb}$
, than the conventional apnea-hypopnea index in differentiating increasingly severe heart rhythm issue groups: 0.14
$>$
0.06, 0.33
$>$
0.10, and 0.41
$>$
0.07.
4) Significance:
the proposed method holds relevance as a supplementary diagnostic tool for assessing the authentic state of sleep apnea in clinical practice.