Evidence map›Paper›PMID 34693257›Full record

ArticleKidney medicine

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

Meaghan Lunney, Natasha Wiebe, Elizabeth Kusi-Appiah, Alexander Tonelli, Rachel Lewis, Reed Ferber, Marcello Tonelli, Alberta Kidney Disease Network

Abstract read
In one paragraph

Article in Kidney medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Meaghan LunneyDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Natasha WiebeDepartment of Medicine, University of Alberta, Edmonton, AB, Canada.
Elizabeth Kusi-AppiahDepartment of Nephrology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Alexander TonelliÉcole Fédérale Polytechnique de Lausanne, Lausanne, Vaud, Switzerland.
Rachel LewisDepartment of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Reed FerberFaculty of Kinesiology, University of Calgary, Calgary, AB, Canada.
Marcello TonelliDepartment of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Alberta Kidney Disease Network

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RATIONALE &

objectivePeople 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

designProspective observational cohort feasibility study. SETTING &

participantsWe 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.

resultsData 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.

conclusionsWithin-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.

Indexed as

digital healthFitness trackerhemodialysisprediction

Identifiers

PMID34693257
PMCPMC8515069

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.