System and Method to Determine ME/CFS and Long COVID Disease Severity Using a Wearable Sensor (2404.04345v1)

Abstract: Objective: We present a simple parameter, calculated from a single wearable sensor, that can be used to objectively measure disease severity in people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) or Long COVID. We call this parameter UpTime. Methods: Prior research has shown that the amount of time a person spends upright, defined as lower legs vertical with feet on the floor, correlates strongly with ME/CFS disease severity. We use a single commercial inertial measurement unit (IMU) attached to the ankle to calculate the percentage of time each day that a person spends upright (i.e., UpTime) and number of Steps/Day. As Long COVID shares symptoms with ME/CFS, we also apply this method to determine Long COVID disease severity. We performed a trial with 55 subjects broken into three cohorts, healthy controls, ME/CFS, and Long COVID. Subjects wore the IMU on their ankle for a period of 7 days. UpTime and Steps/Day were calculated each day and results compared between cohorts. Results: UpTime effectively distinguishes between healthy controls and subjects diagnosed with ME/CFS ($\mathbf{p = 0.00004}$) and between healthy controls and subjects diagnosed with Long COVID ($\mathbf{p = 0.01185}$). Steps/Day did distinguish between controls and subjects with ME/CFS ($\mathbf{p = 0.01}$) but did not distinguish between controls and subjects with Long COVID ($\mathbf{p = 0.3}$). Conclusion: UpTime is an objective measure of ME/CFS and Long COVID severity. UpTime can be used as an objective outcome measure in clinical research and treatment trials. Significance: Objective assessment of ME/CFS and Long COVID disease severity using UpTime could spur development of treatments by enabling the effect of those treatments to be easily measured.

• The paper introduces UpTime, a wearable sensor-derived metric from an ankle IMU that significantly differentiates ME/CFS (p=0.00004) and Long COVID (p=0.01185) patients from healthy controls.
• It validates UpTime by demonstrating a moderate correlation (r²=0.68) with self-reported upright activity, suggesting patients may overestimate their activity levels.
• The study reveals that daily step counts reliably distinguish only ME/CFS cases, underscoring UpTime’s specificity for capturing orthostatic intolerance in chronic conditions.

Objective Measurement of Disease Severity in ME/CFS and Long COVID using a Single Wearable Sensor

Introduction to UpTime as a Digital Biomarker

Recent research introduces a novel parameter for objectively measuring disease severity in individuals with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Long COVID. Termed "UpTime," this parameter is derived from a single wearable sensor's data, specifically an inertial measurement unit (IMU) attached to the ankle. UpTime quantifies the percentage of a day that individuals spend in an upright position, offering a technological advance in the assessment of diseases that have eluded conventional biomarker identification.

Methodology Overview

The paper involved 55 subjects across three cohorts: healthy controls, ME/CFS patients, and Long COVID patients. Participants wore the IMU for 7 days, with data on UpTime and daily steps (Steps/Day) compared across groups. Notably, this research utilized MbientLab's MetaMotionS sensors for improved battery life and onboard data storage. The UpTime parameter was validated against self-reported Hours of Upright Activity (HUA) and steps taken daily, with significant findings illustrating the method's efficacy in distinguishing ME/CFS and Long COVID from healthy controls.

Key Results

The analysis yielded compelling results:

• UpTime significantly differentiated healthy controls from ME/CFS and Long COVID subjects, with p-values of 0.00004 and 0.01185, respectively.
• Steps/Day was also a differentiator for ME/CFS versus controls (p = 0.01) but was not significant for Long COVID versus controls (p = 0.3).
• Steps/Day did not conclusively serve as a reliable indicator of disease severity due to variability, especially among control subjects.
• An interesting additional analysis correlated self-reported HUA with objectively measured UpTime, finding a moderate correlation (r^2 = 0.68), indicating that patients may overestimate their upright activity.

Implications and Future Directions

This paper's findings underscore the potential of UpTime as a reliable, objective measure of disease severity for ME/CFS and Long COVID, with tangible implications for both clinical and research settings. The contrast between UpTime and Steps/Day in their utility highlights the specificity of UpTime for diseases characterized by orthostatic intolerance. Future investigations can further explore integrating UpTime with complementary digital biomarkers and explore the potential for personalized monitoring and management of ME/CFS and Long COVID. The development of UpTime reflects a growing intersection between wearable technology and healthcare, promising advancements in treatment modalities and our understanding of complex diseases.

Concluding Thoughts

Both practical and theoretical considerations emerge from this paper. The validation of UpTime as a digital biomarker presents a significant step forward in objectively assessing ME/CFS and Long COVID severity. The research not only offers an immediate tool for clinicians but also lays the groundwork for future innovations in disease monitoring and management through wearables. As the scientific community continues to explore the capabilities of digital biomarkers, UpTime represents a confluence of technology and medicine that could revolutionize patient care for chronic illnesses lacking robust diagnostic tools.