Correlation of hypoxic burden with blood pressure diurnal rhythm in obstructive sleep apnea.

STUDY

OBJECTIVES

Obstructive sleep apnea is associated with disturbances in blood pressure patterns, which is recognized as an independent cardiovascular risk factor. However, conventional hypoxic indicators of obstructive sleep apnea severity showed inconsistent associations with these blood pressure disturbances. Hypoxic burden, a metric integrating the frequency, depth, and duration of desaturation, may better represent the characteristics of hypoxia. We hypothesized that hypoxic burden would be more closely associated with blood pressure patterns compared to other traditional hypoxia indicators.

MATERIALS AND

METHODS

Hypoxic burden was measured from polysomnography, followed by 24-h ambulatory blood pressure monitoring in 377 patients with suspected obstructive sleep apnea. Patients were grouped based on the rhythms of systolic blood pressure and diastolic blood pressure. Logistic regression analysis was conducted to assess the association between hypoxic burden and blood pressure rhythm impairment.

RESULTS

Hypoxic burden was significantly higher in the non-dipper groups than that in the dipper groups. After adjusting for various confounders, subjects with higher hypoxic burden in the fourth quartile were more likely to exhibit systolic blood pressure non-dipping pattern in model 3. Similarly, the association between hypoxic burden and nocturnal hypertension also remained statistically significant after adjusting for all the confounding factors. However, none of the conventional hypoxic metrics were consistently associated with blood pressure rhythm abnormalities after adjusting for various confounders.

CONCLUSIONS

Compared to conventional polysomnography hypoxic parameters, hypoxic burden is more closely associated with circadian systolic blood pressure rhythm and nocturnal hypertension in obstructive sleep apnea. Hypoxic burden may be a promising indicator for guiding early intervention in high-risk obstructive sleep apnea patients and predicting adverse cardiovascular outcomes.