Beyond the AHI-pulse wave analysis during sleep for recognition of cardiovascular risk in sleep apnea patients

Recent evidence supports the use of pulse wave analysis during sleep for assessing functional aspects of the cardiovascular system. The current study compared the influence of pulse wave and sleep study-derived parameters on cardiovascular risk assessment. In a multi-centric study design, 358 sleep apnea patients (age 55 +/- 13 years, 64% male, body mass index 30 +/- 6 kg m(-2), apnea-hypopnea index 13 [5-26] events per hr) underwent a standard overnight sleep recording. A novel cardiac risk index was computed based on pulse wave signals derived from pulse oximetry, reflecting vascular stiffness, cardiac variability, vascular autonomic tone and nocturnal hypoxia. Cardiovascular risk was determined using the ESC/ESH cardiovascular risk matrix, and categorized to high/low added cardiovascular risk. Comparisons between cardiac risk index and sleep parameters were performed for cardiovascular risk prediction. Apnea-hypopnea index, oxygen desaturation index and cardiac risk index were associated with high cardiovascular risk after adjustment for confounders (p = .002, .001, < .001, respectively). In a nested reference model consisting of age, gender and body mass index, adding cardiac risk index but not apnea-hypopnea index or oxygen desaturation index significantly increased the area under the receiver operating characteristic curve (p = .012, .22 and .16, respectively). In a direct comparison of oxygen desaturation index and cardiac risk index, only the novel risk index had an independent effect on cardiovascular risk prediction (p(CRI) < .001, p(ODI) = .71). These results emphasize the association between nocturnal pulse wave and overall cardiovascular risk determined by an established risk matrix. Thus, pulse wave analysis during sleep provides a powerful approach for cardiovascular risk assessment in addition to conventional sleep study parameters.

Automated summary

The study revealed the potential of using pulse wave analysis in combination with ECG signals to assess cardiovascular risk. It was found that pulse wave signals during sleep can effectively identify patients at high cardiovascular risk.