Statistical Validation of Cardiovascular Digital Biomarkers Towards Monitoring the Cardiac Risk in COPD: A Lyfas Case Study
Background: Mobile health (mHealth) is gaining popularity due to its pervasiveness. Lyfas is a smartphone-based optical biomarker instrument catering to mHealth. It captures the Pulse Rate Variability (PRV) and its associated digital biomarkers from the index finger capillary circulation using the principle of arterial photoplethysmography. PRV surrogates for the Cardiovascular Autonomic Modulation (CvAM) and provides a snapshot of psychophysiological homeostasis of the body. Objective: The paper investigates the roles of (a) physiological factors, e.g., Age, Duration of illness, Heart Rate (HR), Respiration Rate (RR), SpO2 level, and (b) popular digital biomarkers, such as SDNN, LF/HF, RMSSD, pNN50, SD1/SD2 to evaluate the cardiac risk. The paper hypothesizes that low FEV1, which is another physiological factor, plays a critical role in defining such risk. Method: A total of 50 males and females each, suffering from Chronic Obstructive Pulmonary Disease (COPD) took the Lyfas test after appropriate ethical measures. Data, thus collected by Lyfas had been statistically analyzed using histogram plots and Kolmogorov-Smirnov test for normality check, Pearson's Correlations (PC) to measure the strength of associations, and linear regressions to test the goodness of fit of the model. Results: Positive PCs are noted between (a) RMSSD and SDNN ('very high'-females: 0.86 and males: 0.91), (b) pNN50 and RMSSD (PC: moderate 0.46), (c) pNN50 and SDNN (PC: moderate 0.44), (d) Duration of illness and Age ('high'-females: 0.71 and males: 0.77), and (e) Age and RR ('high'-females: 0.67, males: 0.53). Negative PC is noted between (a) LF/HF and FEV1 ('moderately high'-males 0.42) and (b) LF/HF and SpO2 ('moderately high'-males 0.30). Although the R2 values are not so encouraging (most are < 0.5), yet, the models are statistically significant (p-values 0.0336; CI 95%). Conclusion: The paper concludes that Lyfas may be used to predict the cardiac risk in COPD patients based on the LF/HF values correlated to SpO2 and FEV1 levels.