Evidence map›Paper›PMID 33794537›Full record

ArticleGerontology2021

A Wrist-Worn Sensor-Derived Frailty Index Based on an Upper-Extremity Functional Test in Predicting Functional Mobility in Older Adults.

Gu Eon Kang, Aanand D Naik, Ravi K Ghanta, Todd K Rosengart, Bijan Najafi

Open access · greenAbstract read
In one paragraph

Article in Gerontology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 30% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Cellular Senescence and Frailty in Transplantation.Current transplantation reports · 2023
    Article
  5. Article
  6. Review
  7. 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

5 authors at 2 institutions in 1 country.

Gu Eon KangInterdisciplinary Consortium on Advanced Motion Performance (iCAMP), Division of Vascular Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.
Aanand D NaikHouston Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.
Ravi K GhantaDivision of Cardiothoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.
Todd K RosengartDivision of Cardiothoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.
Bijan NajafiInterdisciplinary Consortium on Advanced Motion Performance (iCAMP), Division of Vascular Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, USA.
Michael E. DeBakey VA Medical Center · USBaylor College of Medicine · US

Funding

An Innovative Platform for Objective Monitoring of Instrumental Activities of Daily LivingR42AG060853 · NIA · BIOSENSICS, LLC · PI NGUYEN, HUNG P., VAZIRI, ASHKAN · 2018 to 2020
$4.3M
Research Training Program in Cardiovascular SurgeryT32HL139430 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI Todd K Rosengart · 2018 to 2026
$2.9M
Phase II STTR: Portable Device for Telecare Monitoring of Elderly PeopleR42AG032748 · NIA · BIOSENSICS, LLC · PI GWIN, JOSEPH T, MOHLER, MARTHA JANE · 2012 to 2016
$2.7M
Portable Device for Telecare Monitoring of Elderly PeopleSB1AG032748 · NIA · BIOSENSICS, LLC · PI VAZIRI, ASHKAN · 2018 to 2019
$2.4M
NHLBI NIH HHS T32 HL139430NIA NIH HHS R42 AG032748NIA NIH HHS R42 AG060853NIA NIH HHS SB1 AG032748
6 · The paper itself

Abstract

introductionPreoperative frailty is an independent risk factor for postoperative complications across surgical specialties. Functional mobility such as gait, timed up and go (TUG), and 5 times sit-to-stand (5-STS) are popular preoperative frailty measurements but are not suitable for patients with severe mobility impairment. A wrist-worn sensor-derived frailty index based on an upper-extremity functional test (20-s repetitive elbow flexion-extension task; UEFI) was developed previously; however, its association with functional mobility remained unexplored. We aimed to investigate the predictive power of the UEFI in predicting functional mobility.

methodsWe examined correlation between the UEFI and gait speed, TUG duration, and 5-STS duration in 100 older adults (≥ 65 years) using multivariate regression analysis. The UEFI was calculated using slowness, weakness, exhaustion, and flexibility of the sensor-based 20-s repetitive elbow flexion-extension task.

resultsThe UEFI was a significant predictor for gait speed and TUG duration and 5-STS duration (all R ≥ 0.60; all p < 0.001) with the variance (adjusted R2) of 35-37% for the dependent variables. The multivariate regression analysis revealed significant associations between the UEFI and gait speed (β = -0.84; 95% confidence interval [95% CI] = [-1.19, -0.50]; p < 0.001) and TUG duration (β = 16.2; 95% CI = [9.59, 22.8]; p < 0.001) and 5-STS duration (β = 33.3; 95% CI = [23.6, 43.2]; p < 0.001), found after accounting for confounding variables (e.g., age and fear of falling scale).

conclusionsOur findings suggest that the UEFI can be performed with a wrist-worn sensor and has been validated with other established measures of preoperative frailty. The UEFI can be applied in a wide variety of patients, regardless of mobility limitations, in an outpatient setting.

Indexed as

FrailtyAccidental FallsAgedFearGeriatric AssessmentHumansWristDigital healthFrailtyGaitMotor capacityRisk of fallingSit to standTimed up and goWearable sensors

Identifiers

PMID33794537
PMCPMC9318197
OpenAlexW3151776922

What OpenQuestion holds

Textmetadata
LicenceTDM
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.