Evidence map›Paper›PMID 36172447›Full record

ArticleJTCVS open2022

Comparing three wearable accelerometers to measure early activity after cardiac surgery.

Charles H Brown, Lisa Yanek, Ryan Healy, Tiffany Tsay, Junrui Di, Lee Goeddel, Daniel Young, Vadim Zipunnikov, Jennifer Schrack, Cardiac Surgery Mobility Working Group

Abstract read
In one paragraph

Article in JTCVS open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. 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

10 authors.

Charles H BrownDepartment of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.
Lisa YanekDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.
Ryan HealyDepartment of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.
Tiffany TsayDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md.
Junrui DiDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md.
Lee GoeddelDepartment of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Md.
Daniel YoungDepartment of Physical Therapy, University of Nevada, Las Vegas, Las Vegas, Nev.
Vadim ZipunnikovDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md.
Jennifer SchrackDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md.
Cardiac Surgery Mobility Working Group

Funding

Monitoring Cerebral Autoregulation in Patients Undergoing Traumatic Hip Fracture Surgery to Improve Postoperative OutcomesK76AG057020 · NIA · JOHNS HOPKINS UNIVERSITY · PI BROWN, CHARLES HUGH · 2017 to 2021
$1.1M
NIA NIH HHS K76 AG057020
6 · The paper itself

Abstract

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.

Indexed as

accelerometersactivity and mobilitycardiac surgerycritical carefunctional statusICU, intensive care unitIQR, interquartile rangeJH-HLM, Johns Hopkins-Highest Level of MobilitylogEuroSCORE, logistic European System for Cardiac Operative Risk Evaluation scoreolder adultsphysical therapyROC, receiver operating curve

Identifiers

PMID36172447
PMCPMC9510817

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.