A Novel Methodology for the Synchronous Collection and Multimodal Visualization of Continuous Neurocardiovascular and Neuromuscular Physiological Data in Adults with Long COVID

  1. Feng Xue
  2. Ann Monaghan
  3. Glenn Jennings
  4. Lisa Byrne
  5. Tim Foran
  6. Eoin Duggan
  7. Roman Romero-Ortuno

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Abstract

Background: Reports suggest that adults with post-COVID-19 syndrome or long COVID may be affected by orthostatic intolerance syndromes, with autonomic nervous system dysfunction as a possible causal factor of neurocardiovascular instability (NCVI). Long COVID can also manifest as prolonged fatigue, which may be linked to neuromuscular function impairment (NMFI). The current clinical assessment for NCVI monitors neurocardiovascular performance upon the application of orthostatic stressors such as an active (i.e., self-induced) stand or a passive (tilt table) standing test. Lower limb muscle contractions may be important in orthostatic recovery via the skeletal muscle pump. In this study, adults with long COVID were assessed with a protocol that, in addition to the standard NCVI tests, incorporated simultaneous lower limb muscle monitoring for NMFI assessment. Methods: To conduct such an investigation, a wide range of continuous non-invasive biomedical sensing technologies were employed, including digital artery photoplethysmography for the extraction of cardiovascular signals, near-infrared spectroscopy for the extraction of regional tissue oxygenation in brain and muscle, and electromyography for assessment of timed muscle contractions in the lower limbs. Results: With the proposed methodology described and exemplified in this paper, we were able to collect relevant physiological data for the assessment of neurocardiovascular and neuromuscular functioning. We were also able to integrate signals from a variety of instruments in a synchronized fashion and visualize the interactions between different physiological signals during the combined NCVI/NMFI assessment. Multiple counts of evidence were collected, which can capture the dynamics between skeletal muscle contractions and neurocardiovascular responses. Conclusions: The proposed methodology can offer an overview of the functioning of the neurocardiovascular and neuromuscular systems in a combined NCVI/NMFI setup and is capable of conducting comparative studies with signals from multiple participants at any given time in the assessment. This could help clinicians and researchers generate and test hypotheses based on the multimodal inspection of raw data in long COVID and other cohorts.

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  1. Version published to 10.3390/s22051758
  2. ScreenIT

    SciScore for 10.1101/2021.12.24.21268370: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    This methodological study was conducted within the wider context of a cross-sectional observational study on a participant cohort recruited for the TROPIC (Technology assisted solutions for the Recognition of Objective Physiological Indicators of post-Coronavirus-19 fatigue) investigation at Trinity College Dublin and St.
    Trinity
    suggested: (Trinity, RRID:SCR_013048)
    The beat-to-beat Finapres® NOVA signals were recorded in NOVAScope® v1.9 and exported in .csv format.
    NOVAScope®
    suggested: None
    2.4.1 Data merging: All the raw data collected was processed in R version 4.0.5 using RStudio 1.4.1106 (Boston, MA).
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.12.24.21268370v1 on medRxiv