A study published in journal Chest has shown that novel intra-sleep pulse oxymetry can be an effective modality in identifying cardiovascular disease risk in patients. In the study, a modified version of Weinmann‘s SOMNOcheck micro oximeter was used to observe pulse wave attenuation, heart rate acceleration, pulse propagation times, as well as respiration-related pulse oscillations and oxygen desaturation episodes. All the collected data was analyzed by an algorithm, and the prognostic results were checked against European Society of Hypertension/European Society of Cardiology (ESH/ESC) risk factor matrix.
Some details from the study abstract:
Methods: One hundred forty-eight sleep clinic patients (98 men, mean age 50 ± 13 years) underwent an overnight study using a novel photoplethysmographic sensor. CV risk was classified according to the European Society of Hypertension/European Society of Cardiology (ESH/ESC) risk factor matrix. Five signal components reflecting cardiac and vascular activity (pulse wave attenuation, pulse rate acceleration, pulse propagation time, respiration-related pulse oscillation, and oxygen desaturation) extracted from 99 randomly selected subjects were used to train the classification algorithm. The capacity of the algorithm for CV risk prediction was validated in 49 additional patients.
Results: Each signal component contributed independently to CV risk prediction. The sensitivity and specificity of the algorithm to distinguish high/low CV risk in the validation group were 80% and 77%, respectively. The area under the receiver operating characteristic curve for high CV risk classification was 0.84. β-Blocker treatment was identified as an important factor for classification that was not in line with the ESH/ESC reference matrix.
Abstract in Chest: Oximeter-Based Autonomic State Indicator Algorithm for Cardiovascular Risk Assessment
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