BACKGROUND
Chronic heart failure is a serious complication of the terminal stage of coronary heart disease (CHD); both disorders are leading causes of death. B-type natriuretic peptide (BNP) is a plasma biomarker of the presence and severity of chronic heart failure. Therefore, the timely assessment of the BNP levels and detection of pathological cardiovascular changes are critical for chronic heart failure prevention in patients with CHD. Novel instruments for wrist pulse detection include wearable devices that can be used to obtain pathophysiological information on the cardiovascular system.
OBJECTIVE
we investigated whether wrist pulse detection could be used to assess the BNP levels of patients with CHD and accordingly evaluated the potential of wrist pulse signals for use in the real-time cardiac monitoring of patients with CHD.
METHODS
On the basis of BNP levels, 419 patients with CHD were assigned to Group 1 (BNP < 95 pg/mL, n = 249), 2 (95 < BNP < 221 pg/mL, n = 85), and 3 (BNP > 221 pg/mL, n = 85). Wrist pulse signals were measured noninvasively. Both the time-domain method and multiscale entropy (MSE) method were used to extract pulse features. Decision tree (DT) and random forest (RF) algorithms were employed to construct models for classifying BNP level groups, and the models’ accuracy, precision, recall, and F1-score were compared.
RESULTS
The pulse (time-domain and MSE) features of the three groups differed significantly, suggesting different pathological states of the cardiovascular system in patients with CHD. Moreover, the RF models outperformed the DT models in accuracy and average precision, recall, and F1-score. Furthermore, the optimal RF model was that based on a dataset comprising both time-domain and MSE features, achieving accuracy, average precision, average recall, and an average F1-score of 90.900%, 91.048%, 90.900%, and 90.897%, respectively.
CONCLUSIONS
The wrist pulse detection technology employed in the present study is useful for assessing the cardiac function of patients with CHD.