Evidence map›Paper›PMID 40636779›Full record

ArticleDigital biomarkers

A Smartphone Application to Measure Walking Cadence before Major Abdominal Surgery in Older Adults.

Daniel Steven Rubin, Marcin Straczkiewicz, Emi Yamamoto, Maria Lucia L Madariaga, Mark Ferguson, Jennifer S Brach, Nancy W Glynn, Sang Mee Lee, Margaret Danilovich, Megan Huisingh-Scheetz

Abstract read
In one paragraph

Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Daniel Steven RubinDepartment of Anesthesia and Critical Care, The University of Chicago, Chicago, IL, USA.
Marcin StraczkiewiczDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Emi YamamotoDepartment of Anesthesia and Critical Care, The University of Chicago, Chicago, IL, USA.
Maria Lucia L MadariagaDepartment of Surgery, The University of Chicago, Chicago, IL, USA.
Mark FergusonDepartment of Surgery, The University of Chicago, Chicago, IL, USA.
Jennifer S BrachSchool of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
Nancy W GlynnSchool of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Sang Mee LeeDepartment of Public Health Sciences, University of Chicago, Chicago, IL, USA.
Margaret DanilovichDepartment of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, USA.
Megan Huisingh-ScheetzDepartment of Medicine, Section of Geriatrics, University of Chicago, Chicago, IL, USA.

Funding

At-home gait-cadence functional assessment and recovery trajectory for older adults undergoing major abdominal surgeryR03AG078957 · NIA · UNIVERSITY OF CHICAGO · PI RUBIN, DANIEL STEVEN · 2022 to 2023
$328k
NIA NIH HHS R03 AG078957
6 · The paper itself

Abstract

Introduction: Preoperative physical functional assessments (i.e., assessments that measure capability to perform physical activity) are integral to estimate perioperative risk for older adults. However, these assessments are not routinely performed in-clinic prior to surgery. Walking cadence, or the number of steps walked in a specified amount of time (i.e., steps/min), measures activity intensity and may be able to identify high-risk patients prior to surgery. Smartphones can measure walking characteristics and guide patients through remote functional assessments. Here, we assess feasibility, acceptability, and accuracy of Walk Test, a smartphone application designed to measure walking cadence. Methods: We performed a prospective cohort study of older adults prior to abdominal surgery and enrolled them remotely to perform at-home usual- and fast-paced walks with subsequent validation in-clinic. Each walk (usual- and fast-paced) was 2 min in duration. Feasibility was assessed if 80% of patients could perform all study procedures; acceptability was measured using the Post-Study Survey Usability Questionnaire (PSSUQ); accuracy of our approach was assessed with Lin's concordance coefficient (CCC). activPAL thigh worn accelerometer worn during the in-clinic walk served as a gold standard comparison. We used the CCC to compare the at-home and in-clinic walks as performed by Walk Test. Results: We enrolled 41 participants (mean age 69 ± 5 years, 26 (63%) female); 88% (36/41) successfully completed entire study protocol including independent installation of the application, walk tests (at-home and in-clinic) and questionnaires. Median (interquartile range) overall score of PSSUQ was 1 (1, 1) indicating strong acceptability and usability. The Lin's CCC between the in-clinic activPAL and Walk Test for usual-paced walk was 0.97 (95% CI: 0.96, 0.99, Conclusion: We successfully demonstrated the feasibility, acceptability and accuracy of Walk Test to measure walking cadence. Future work is needed to standardize walk test performance at-home to ensure consistency between in-clinic and at-home measures.

Indexed as

AccelerometerCadenceRemote assessmentSmartphoneWearable physical activity monitoring

Identifiers

PMID40636779
PMCPMC12240576

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.