Heart Rate Variability as a Prospective Predictor of Early COVID-19 Symptoms
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Abstract
Heart rate variability (HRV) is the fluctuation in the time interval between consecutive heartbeats, the measurement of which is a non-invasive method for assessing the autonomic status. The autonomic nervous system plays an important role in physiological situations, and in various pathological processes such as in cardiovascular diseases and viral infections. This study examined the cardiac autonomic responses, as measured by HRV before, after, and during coronavirus disease. In this study, we used beat interval data extracted from the Welltory app from 14 eligible subjects (9 men and 5 women) with a mean age (SD) of 44 (8.7) years. HRV analysis was performed through an assessment of time-domain indices (SDNN and RMSSD). Group analysis did not reveal any statistical difference between HRV metrics before, during, and after COVID-19. However, HRV at the individual level showed a statistically significant individual change during COVID-19 in some users. These data further support the usefulness of using individual-level HRV tracking for the detection of early diseases inclusive of COVID-19.
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SciScore for 10.1101/2021.07.02.21259891: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Upon downloading the Welltory app, users provide informed consent for their anonymized data to be used by the company for internal research purposes if such research can help provide users with better services or improve the app’s functionality. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was …SciScore for 10.1101/2021.07.02.21259891: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Upon downloading the Welltory app, users provide informed consent for their anonymized data to be used by the company for internal research purposes if such research can help provide users with better services or improve the app’s functionality. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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