Analysis of Gender Differences in HRV of Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Mobile-Health Technology

Abstract

In a previous study using mobile-health technology (mHealth), we reported a robust association between chronic fatigue symptoms and heart rate variability (HRV) in female patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). This study explores HRV analysis as an objective, non-invasive and easy-to-apply marker of ME/CFS using mHealth technology, and evaluates differential gender effects on HRV and ME/CFS core symptoms. In our methodology, participants included 77 ME/CFS patients (32 men and 45 women) and 44 age-matched healthy controls (19 men and 25 women), all self-reporting subjective scores for fatigue, sleep quality, anxiety, and depression, and neurovegetative symptoms of autonomic dysfunction. The inter-beat cardiac intervals are continuously monitored/recorded over three 5-min periods, and HRV is analyzed using a custom-made application (iOS) on a mobile device connected via Bluetooth to a wearable cardiac chest band. Male ME/CFS patients show increased scores compared with control men in all symptoms and scores of fatigue, and autonomic dysfunction, as with women in the first study. No differences in any HRV parameter appear between male ME/CFS patients and controls, in contrast to our findings in women. However, we have found negative correlations of ME/CFS symptomatology with cardiac variability (SDNN, RMSSD, pNN50, LF) in men. We have also found a significant relationship between fatigue symptomatology and HRV parameters in ME/CFS patients, but not in healthy control men. Gender effects appear in HF, LF/HF, and HFnu HRV parameters. A MANOVA analysis shows differential gender effects depending on the experimental condition in autonomic dysfunction symptoms and HF and HFnu HRV parameters. A decreased HRV pattern in ME/CFS women compared to ME/CFS men may reflect a sex-related cardiac autonomic dysfunction in ME/CFS illness that could be used as a predictive marker of disease progression. In conclusion, we show that HRV analysis using mHealth technology is an objective, non-invasive tool that can be useful for clinical prediction of fatigue severity, especially in women with ME/CFS.

Keywords: HRV; ME/CFS; chronic fatigue syndrome; gender differences; heart rate variability; mHealth; myalgic encephalomyelitis.

Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1

Screenshots sequence corresponding to the custom-made application (FitLab® App). The first screen (left) shows all the stored recordings in the app pending to be synchronized with the server and the possibility to start a new one (“+” symbol). The next three screens ask for the situation where the recording takes place. The last screen (on the right) shows the instantaneous heart rate (in BPM) and the RR series.

Figure 2

Simple regression analysis between physical fatigue perception (FIS-40) and HRV parameters differentiating ME/CFS patients (n = 32) and Control men (n = 19). Physical FIS-40 score is significantly explained from (A) SDNN (p = 0.005), (B) RMSSD (p = 0.026), (C) LF (p = 0.002), and (D) HF (p = 0.016), for ME/CFS patients (black squares, upper regression lines), but not for those healthy controls (white circles, bottom regression lines).

Figure 3

Comparison of the HRV time-domain indices in the whole sample. Mean ± SEM of (A) mean of RR intervals (meanRR), (B) standard deviation of all RR intervals (SDNN), (C) root mean square of differences of successive RR intervals (RMSSD), and (D) the proportion derived by dividing the number of interval differences of successive RR intervals greater than 50 ms by the total number of RR intervals (pNN50). a,b Mean values with unlike letters were significantly different between groups (two-way ANOVA and Duncan’s post hoc comparison, p < 0.05). W-C: Healthy control women (n = 25); W-F: ME/CFS women (n = 44); M-C: Healthy control men (n = 18); M-F: ME/CFS men (n = 32).

Figure 4

Comparison of the HRV frequency-domain indices in the sample. Mean ± SEM of (A) power of the low frequency band (LF), (B) power of the high frequency band (HF), (C) LF/HF ratio, and (D) normalized HF value (HFnu). a,b Mean values with unlike letters were significantly different between groups (two-way ANOVA and Duncan’s post hoc comparison, p < 0.05). W-C: Healthy control women (n = 25); W-F: ME/CFS women (n = 44); M-C: Healthy control men (n = 18); M-F: ME/CFS men (n = 32).