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Objective: Wearable activity monitors can provide detailed data on activity after cardiac surgery and discriminate a patient's risk for hospital-based outcomes. However, comparative data for different monitoring approaches, as well as predictive ability over clinical characteristics, are lacking. In addition, data on specific thresholds of activity are needed. The objective of this study was to compare 3 wearable activity monitors and 1 observational mobility scale in discriminating risk for 3 hospital-based outcomes, and to establish clinically relevant step thresholds. Methods: Cardiac surgery patients were enrolled between June 2016 and August 2017 in a cohort study. Postoperative activity was measured by 3 accelerometry monitors (StepWatch Ambulation Monitor, Fitbit Charge HR, and ActiGraph GT9X) and 1 nurse-based observation scale. Monitors represent a spectrum of characteristics, including wear location (ankle/wrist), output (activity counts/steps), consumer accessibility, and cost. Primary outcomes were duration of hospitalization >7 days, discharge to a nonhome location, and 30-day readmission. Results: Data were available from 193 patients (median age 67 years [interquartile range, 58-72]). All postoperative day 2 activity metrics (ie, from StepWatch, Fitbit, ActiGraph, and the observation scale) were independently associated with prolonged hospitalization and discharge to a nonhome location. Only steps as measured by StepWatch was independently associated with 30-day readmission. Overall, StepWatch provided the greatest discrimination (C-statistics 0.71-0.76 for all outcomes). Step thresholds between 250 and 500 steps/day identified between 74% and 96% of patients with any primary outcome. Conclusions: Data from wearable accelerometers provide additive value in early postoperative risk-stratification for hospital-based outcomes. These results both support and provide guidance for activity-monitoring programs after cardiac surgery.
RESUMO
OBJECTIVES: With unprecedented demand for Medicaid long-term services and supports, states are seeking to allocate resources in the most efficient way. Understanding the prevalence of frailty and how it varies across home and community-based services (HCBS) populations can assist states with more precise identification of individuals most in need of services. Early identification of individuals more likely to experience frailty changes could allow for enhanced care planning to prevent or slow the progression of decline. DESIGN: Longitudinal study. SETTING AND PARTICIPANTS: Data from Connecticut's assessment tool (based on interRAI-HC) were analyzed at 2 time points for 16,309 individuals receiving HCBS. The sample included assessments completed between November 1, 2017 and July 15, 2020 across 4 groups: older adults 65+ years old meeting nursing facility level of care (NF LOC), older adults 65+ years old not meeting NF LOC, individuals with acquired brain injury, and individuals <65 years old with physical disability. METHODS: We measured frailty using the Frailty Index (FI) and examined change in FI between baseline and follow-up. A change in FI score of at least ±0.03 was classified as a clinically meaningful change. We compared predictors of clinically meaningful decline or improvement using multivariate logistic regression. RESULTS: In our sample, 54% of individuals experienced a clinically meaningful change: 42% declined and 12% improved. Individuals receiving in-home care services had lower odds of improvement across all HCBS groups and multiple frailty categories with odds ratios ranging from 0.35 to 0.68. Frail older adults 65+ years old meeting nursing facility level of care receiving physical therapy were 21% less likely to experience decline and 1.4 times more likely to improve. CONCLUSIONS AND IMPLICATIONS: The nature of HCBS support provided can impact changes in frailty status. More reactive services such as in-home care may contribute to frailty decline while rehabilitative services such as physical therapy may protect against decline.
