Key result
COVID-19 infection was associated with a significant reduction in heart rate variability measured by wearable devices, with a decrease in the SD of normal-to-normal interbeat intervals of 3.25 ms.
Why the study?
To assess the utility of wearable device heart rate variability measurements as predictive indicators of COVID-19 and the onset and worsening of symptoms.
Does heart rate variability measurement using wearable devices predict the onset and worsening of COVID-19 compared to healthy individuals?
Systematic Review and Meta-Analysis (n=10,588)
Does heart rate variability measurement using wearable devices predict the onset and worsening of COVID-19 compared to healthy individuals?
Mean Difference: -3.25 (95% CI -5.34–-1.16)
Wearable devices measuring heart rate variability can detect significant reductions in SDNN associated with COVID-19, potentially enabling presymptomatic identification and monitoring.
Supports wearable HRV monitoring for COVID-19 risk stratification; extends observational data but leaves prospective validation open.
BACKGROUND: Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity and a predictor of mortality in infected people. Given the large number of wearable devices that capture physiological signals of the human body easily and noninvasively, several studies have used this equipment to measure the HRV of individuals and related these measures to COVID-19. OBJECTIVE: The objective of this study was to assess the utility of HRV measurements obtained from wearable devices as predictive indicators of COVID-19, as well as the onset and worsening of symptoms in affected individuals. METHODS: A systematic review was conducted searching the following databases up to the end of January 2023: Embase, PubMed, Web of Science, Scopus, and IEEE Xplore. Studies had to include (1) measures of HRV in patients with COVID-19 and (2) measurements involving the use of wearable devices. We also conducted a meta-analysis of these measures to reduce possible biases and increase the statistical power of the primary research. RESULTS: The main finding was the association between low HRV and the onset and worsening of COVID-19 symptoms. In some cases, it was possible to predict the onset of COVID-19 before a positive clinical test. The meta-analysis of studies reported that a reduction in HRV parameters is associated with COVID-19. Individuals with COVID-19 presented a reduction in the SD of the normal-to-normal interbeat intervals and root mean square of the successive differences compared with healthy individuals. The decrease in the SD of the normal-to-normal interbeat intervals was 3.25 ms (95% CI -5.34 to -1.16 ms), and the decrease in the root mean square of the successive differences was 1.24 ms (95% CI -3.71 to 1.23 ms). CONCLUSIONS: Wearable devices that measure changes in HRV, such as smartwatches, rings, and bracelets, provide information that allows for the identification of COVID-19 during the presymptomatic period as well as its worsening through an indirect and noninvasive self-diagnosis.
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Sanches et al. (2023) conducted a systematic review and meta-analysis in COVID-19 (n=10,588). COVID-19 infection vs. Healthy individuals or pre-infection baseline was evaluated on Decrease in the SD of the normal-to-normal interbeat intervals (SDNN) (MD -3.25 ms, 95% CI -5.34 to -1.16). COVID-19 infection was associated with a significant reduction in heart rate variability measured by wearable devices, with a decrease in the SD of normal-to-normal interbeat intervals of 3.25 ms.
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