A Correlation Study on the Prediction of Coronary Artery Lesion Degree by Pulse Wave Harmonics Based on SYNTAX Score

Objective This study aimed to investigate the correlation between the differences in pulse wave harmonic indexes between the left and right hands and the SYNTAX score, and to explore the potential of pulse wave harmonics in predicting the degree of coronary artery lesions. Methods The arterial pressure wave signals of the left and right hands of patients scheduled for coronary angiography were collected by photoplethysmography. According to the "visceral resonance theory", taking integer multiples of the heartbeat from 0 to 11 as the resonance frequencies, the collected arterial pressure waves were decomposed into the 0th to 11th harmonics by the Fourier transform method. The harmonic characteristics were quantified by amplitude (Cn), phase (Pn), and energy (Dn) (n is the harmonic serial number), and the coefficient of variation of the indexes was calculated and suffixed as CV. The absolute value of the difference in the corresponding harmonic indexes between the left and right hands of the patients was calculated. The SYNTAX score of the included cases was calculated based on the imaging data of coronary angiography. The included cases were divided into a male group and a female group according to gender. For each group, a logistic regression equation was established with the difference value of the harmonic index as the independent variable and SYNTAX score ≥ 22 as the dependent variable. The equation corresponding to the minimum value of the Akaike information criterion (AIC) was taken as the optimal prediction model. Finally, the discriminant ability of the prediction model was evaluated by the ROC curve method and the Bootstrap internal validation method. Results A total of 348 patients were included, including 249 males and 99 females. The discriminant model for predicting SYNTAX score ≥ 22 based on C10, D6, D9, D10, P8, P10, P1CV, and C9CV in the male group was statistically significant (P < 0.05), with the minimum AIC value of 105.47, the area under the ROC curve (AUC) of 0.89, and the average AUC of 0.85 in the Bootstrap internal validation. The discriminant model based on D2, D3, D5, D6, D9, C2CV, C4CV, C5CV, C6CV, and C9CV in the female group was statistically significant (P < 0.05), with the minimum AIC value of 59.34. The AUC of the ROC curve of this prediction model was 0.92, and the average AUC in the Bootstrap internal validation was 0.84. Conclusion The difference characteristics of pulse wave harmonics between the left and right hands can effectively reflect the degree of coronary artery lesions. Through the analysis of pulse wave harmonics, a diagnostic model with good discriminant ability for predicting the degree of coronary artery lesions can be constructed, which may offer a valuable non-invasive tool for clinical assessment of CAD.