Cardiovascular Disease Could Be Detected During Sleep

Five signal components were recorded; pulse wave attenuation, pulse rate acceleration, pulse propagation time, respiration-related pulse oscillation, and oxygen desaturation. An autonomic state indicator (ASI) algorithm was developed based on the pulse oximetry results extracted from 99 randomly selected subjects, and the capacity of the algorithm for CV risk prediction was validated in 49 additional patients.

The results demonstrated that the sensitivity and specificity of the algorithm to distinguish high or low CV risk in the validation group were 80% and 77%, respectively; each signal component contributed independently to CV risk prediction. The researchers also found that β-Blocker treatment was identified as an important factor for classification that was not in line with the European Society of Hypertension/European Society of Cardiology (ESH/ESC) risk factor matrix used to classify the CV risk. The study was published in the February 2011 issue of the journal Chest.

"Signals derived from overnight oximetry recording provide a novel potential tool for CV risk classification,” said lead author Ludger Grote, MD, PhD, an associate professor at the center for sleep and vigilance disorders at the Sahlgrenska Academy. "We weigh up these components in a model to assess how great a risk the patient runs of cardiovascular disease. We believe that the patient's values reflect the risk at least as well as the individual's risk factors ‘on paper.'”

As the heart pumps blood to the periphery, a pressure pulse is created which distends the arteries and arterioles in the subcutaneous tissue. The change in volume caused by the pressure pulse is detected by illuminating the skin with a light-emitting diode (LED) and then measuring the amount of light either transmitted or reflected to a photodiode, generating a PPG reading. Since the blood flow to the skin can be modulated by multiple other physiological systems, the PPG can also be used to monitor breathing, hypovolemia, and other circulatory conditions.

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Sahlgrenska Academy at the University of Gothenburg