Evidence map›Paper›PMID 35287574›Full record

ArticleBMC geriatrics2022

Frailty assessment using a novel approach based on combined motor and cardiac functions: a pilot study.

Nima Toosizadeh, Maryam Eskandari, Hossein Ehsani, Saman Parvaneh, Mehran Asghari, Nancy Sweitzer

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Sensor-Based Frailty Assessment Using Fitbit.Sensors (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
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

6 authors at 3 institutions in 1 country.

Nima ToosizadehDepartment of Biomedical Engineering, University of Arizona, 1230 N Cherry Avenue, Tucson, AZ, 85719, USA. ntoosizadeh@email.arizona.edu.
Maryam EskandariDepartment of Computer Sciences, University of Arizona, Tucson, AZ, USA.
Hossein EhsaniKinesiology Department, University of Maryland, College Park, MD, USA.
Saman ParvanehEdwards Life Sciences, Irvine, CA, USA.
Mehran AsghariDepartment of Biomedical Engineering, University of Arizona, 1230 N Cherry Avenue, Tucson, AZ, 85719, USA.
Nancy SweitzerArizona Sarver Heart Center, Department of Medicine, University of Arizona, Tucson, USA.
University of Arizona · USEdwards Lifesciences (United States) · USUniversity of Maryland, College Park · US

Funding

Functional Capacity Assessment in Hospitalized Bed-bound COPD Patients; Predicting OutcomesR21AG059202 · NIA · UNIVERSITY OF ARIZONA · PI MOHLER, MARTHA JANE, TOOSIZADEH, NIMA · 2019 to 2020
$410k
NIA NIH HHS R21 AG059202
6 · The paper itself

Abstract

backgroundPrevious research showed association between frailty and an impaired autonomic nervous system; however, the direct effect of frailty on heart rate (HR) behavior during physical activity is unclear. The purpose of the current study was to determine the association between HR increase and decrease with frailty during a localized upper-extremity function (UEF) task to establish a multimodal frailty test.

methodsOlder adults aged 65 or older were recruited and performed the UEF task of rapid elbow flexion for 20 s with the right arm. Wearable gyroscopes were used to measure forearm and upper-arm motion, and electrocardiography were recorded using leads on the left chest. Using this setup, HR dynamics were measured, including time to peak HR, recovery time, percentage increase in HR during UEF, and percentage decrease in HR during recovery after UEF.

resultsFifty-six eligible participants were recruited, including 12 non-frail (age = 76.92 ± 7.32 years), and 40 pre-frail (age = 80.53 ± 8.12 years), and four frail individuals (age = 88.25 ± 4.43 years). Analysis of variance models showed that the percentage increase in HR during UEF and percentage decrease in HR during recovery were both 47% smaller in pre-frail/frail older adults compared to non-frails (p < 0.01, effect size = 0.70 and 0.62 for increase and decrease percentages). Using logistic models with both UEF kinematics and HR parameters as independent variables, frailty was predicted with a sensitivity of 0.82 and specificity of 0.83.

conclusionCurrent findings showed evidence of strong association between HR dynamics and frailty. It is suggested that combining kinematics and HR data in a multimodal model may provide a promising objective tool for frailty assessment.

Indexed as

FrailtyAgedFrail ElderlyGeriatric AssessmentHumansPilot ProjectsRange of Motion, ArticularFrailtyHeart rate variabilityKinematicsOlder adultsWearable sensor

Identifiers

PMID35287574
PMCPMC8919591
OpenAlexW4220653505

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.