Evidence map›Paper›PMID 39552952›Full record

ArticleCureus2024

Predictors of Gait Variability in Older Inpatients: An Exploratory Study Among Orthopedic Patients.

Chen Xu, Yosuke Ishii, Masanosuke Mizutani, Takato Hashizume, Ryoichi Nakamura, Hiroshi Kurumadani, Makoto Takahashi

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PubMed Full text at PMC Publisher
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Chen XuBiomechanics, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.
Yosuke IshiiBiomechanics, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.
Masanosuke MizutaniBiomechanics, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.
Takato HashizumeBiomechanics, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.
Ryoichi NakamuraRehabilitation, Medical Technology, Shimura Hospital, Hiroshima, JPN.
Hiroshi KurumadaniAnalysis and Control of Upper Extremity Function, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.
Makoto TakahashiBiomechanics, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim Older inpatients have reduced physical function and walking ability with a higher risk of falls after being discharged home. Gait variability can assess ambulation and is strongly related to the risk of falls. However, the clinical factors affecting gait variability in inpatients have not been identified. The purpose of this study was to investigate the predictive factors affecting gait variability in older inpatients. Methods A total of 42 older orthopedic inpatients with fractures of the hip, spine, and other segments and 18 healthy volunteers as the control group were enrolled in this study. Inpatients wore tri-axial accelerometers for a 10m walk before discharge. Gait variability was assessed by the coefficient of variation (CV) based on five consecutive stride times. Clinical assessment of muscle strength, joint mobility, balance, pain, and activities of daily living were also evaluated. Results The CV in inpatients was higher than that in healthy elderly. Quadriceps muscle strength, ankle dorsiflexion range of motion, and balance described the CV. When model 2 (adjusted R

Indexed as

accelerometerfall riskgait variabilityolder inpatientsorthopedics

Identifiers

PMID39552952
PMCPMC11568894

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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.