Evidence map›Paper›PMID 35220031›Full record

ArticleGait & posture2022

Evaluation of unsupervised 30-second chair stand test performance assessed by wearable sensors to predict fall status in multiple sclerosis.

Lindsey J Tulipani, Brett Meyer, Dakota Allen, Andrew J Solomon, Ryan S McGinnis

Open access · greenAbstract read
In one paragraph

Article in Gait & posture, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
14.8field-weighted citation impact, top 1% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Rotational Power: A New Accelerometer-Derived Metric to Assess Functional Impairment in Multiple Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025
    Article
  7. Article
  8. Article
  9. Assessing Free-Living Postural Sway in Persons With Multiple Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2023
    Article
  15. Article
  16. Article
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  18. The Sit-to-Stand Transition as a Biomarker for Impairment: Comparison of Instrumented 30-Second Chair Stand Test and Daily Life Transitions in Multiple Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2022
    Article
  19. 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 1 institution in 1 country.

Lindsey J TulipaniM-Sense Research Group, Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States.
Brett MeyerM-Sense Research Group, Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States.
Dakota AllenM-Sense Research Group, Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States.
Andrew J SolomonDepartment of Neurological Sciences, University of Vermont, Burlington, VT, United States.
Ryan S McGinnisM-Sense Research Group, Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States. Electronic address: ryan.mcginnis@uvm.edu.
University of Vermont · US

Funding

Just-In-Time Fall Prevention: Development of an mHealth Intervention for Persons with Multiple SclerosisR21EB027852 · NIBIB · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI MCGINNIS, RYAN S. · 2019 to 2021
$610k
NIBIB NIH HHS R21 EB027852
6 · The paper itself

Abstract

backgroundOne in two people with multiple sclerosis (PwMS) will fall in a three-month period. Predicting which patients will fall remains a challenge for clinicians. Standardized functional assessments provide insight into balance deficits and fall risk but their use has been limited to supervised visits. RESEARCH QUESTION: The study aim was to characterize unsupervised 30-second chair stand test (30CST) performance using accelerometer-derived metrics and assess its ability to classify fall status in PwMS compared to supervised 30CST.

methodsThirty-seven PwMS (21 fallers) performed instrumented supervised and unsupervised 30CSTs with a single wearable sensor on the thigh. In unsupervised conditions, participants performed bi-hourly 30CSTs and rated their balance confidence and fatigue over 48-hours. ROC analysis was used to classify fall status for 30CST performance.

resultsNon-fallers (p = 0.02) but not fallers (p = 0.23) differed in their average unsupervised 30CST performance (repetitions) compared to their supervised performance. The unsupervised maximum number of 30CST repetitions performed optimized ROC classification AUC (0.79), accuracy (78.4%) and specificity (90.0%) for fall status with an optimal cutoff of 17 repetitions. SIGNIFICANCE: Brief durations of instrumented unsupervised monitoring as an adjunct to routine clinical assessments could improve the ability for predicting fall risk and fluctuations in functional mobility in PwMS.

Indexed as

Multiple SclerosisWearable Electronic DevicesFatigueHumansPostural BalanceAccelerometerChair stand testFallsMultiple sclerosisWearable

Identifiers

PMID35220031
PMCPMC9086135
OpenAlexW4212977478

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.