Wearable Fitness Trackers to Predict Clinical Deterioration in Maintenance Hemodialysis: A Prospective Cohort Feasibility Study

Kidney Med. 2021 Jun 29;3(5):768-775.e1. doi: 10.1016/j.xkme.2021.04.013. eCollection 2021 Sep-Oct.

Abstract

Rationale & objective: People receiving hemodialysis often require urgent care or hospitalizations. It is possible that reductions in a patient's level of physical activity may serve as an "early warning" of clinical deterioration, allowing timely clinical intervention. We explored whether step count could serve as a trigger for deterioration.

Study design: Prospective observational cohort feasibility study.

Setting & participants: We recruited consenting adult participants from outpatient dialysis clinics in Calgary, AB, between June 28, 2019, and October 10, 2019.

Exposure and outcomes: Participants wore a wristband fitness tracker for 4 weeks. Activity data from the trackers were imported weekly into the study database. Demographic, clinical management, functional impairment, and frailty were assessed at baseline. Clinical events (urgent care and emergency department visits and hospitalizations) were monitored during the observation period.

Analytical approach: Box and whisker plots and line plots were used to describe each participant's daily steps. Adjusted rate ratios (and 95 % confidence intervals) were calculated to assess the associations between the number of steps taken each day and potential predictors.

Results: Data from 46 patients were included; their median age was 64 years (range, 22 to 85), and 63 % were men. The median number of steps taken per day was 3,133 (range, 248-13,753). Fourteen events among 11 patients were reported. Within patients, step count varied considerably; it was not possible to identify a patient-specific normal range for daily step count. There was no association between step count and the occurrence of clinical events, although the number of events was very small.

Limitations: The number of participants was relatively small, and there were too few events to model to examine whether step count could predict clinical deterioration.

Conclusions: Within-patient variation in daily step count was too high to generate a normal range for patients. However, patient-specific norms over a longer period (3- or 7-day periods) appear potentially worthy of future study in a larger sample and/or over a longer follow-up.

Keywords: Fitness tracker; digital health; hemodialysis; prediction.