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Using consumer-grade physical activity trackers to measure frailty transitions in critical care survivors: An exploratory observational study
ABSTRACT
Background:
Critical illness has been suggested as a sentinel event for frailty development for at-risk older adults. Frail critical illness survivors suffer increased adverse health outcomes but monitoring the recovery post-Intensive Care Unit (ICU) is challenging. Wearable devices (wearables) offer a possibility of measuring frailty.
Objective:
To examine the data collected from wearable devices for the progression of frailty among the critical illness survivors.
Methods:
A prospective observational study was conducted with 12 critical illness survivors from Kingston General Hospital in Canada. Frailty was measured by Clinical Frailty Scale (CFS) at ICU admission (AD), hospital discharge (DC), and 4-week follow-up (FU). Wearable was worn between DC and FU. Wearable collected data on steps, physical activity, sleep and heart rate (HR).
Results:
The CFS increased significantly following critical illness compared pre-ICU frailty level (P=.02, d=-0.53). Frail survivors had significantly lower daily step counts than non-frail survivors (P=.02, d=1.81). There was no difference in sleep and HR measures. Daily step count was strongly correlated with the CFS at FU (r=-0.72, P=.04). Average HR was strongly correlated with the CFS at DC (r=-0.72, P=.046). HR standard deviation was strongly correlated (r=0.78, P<0.05) with the CFS change from AD to FU. No relationship was found between the CFS and sleep measures. Critical illness survivors who increased daily step count over the FU were correlated with the worsening of frailty (r=0.65, P=.03). The trend of increasing HR over this period was correlated with the worsening of frailty (r=0.62, P=.03).
Conclusions:
This study demonstrated a possibility of monitoring frailty and physical recovery using a consumer-grade wearable device. Daily step count and HR showed strong relationship with the frailty progression of the critical illness survivors over time. Understanding this relationship could unlock a new avenue for clinicians to monitor and identify a vulnerable subset of population that might benefit from an early intervention.
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