Evidence map›Paper›PMID 29950824›Full record

ArticleClinical interventions in aging2018

Thoracopelvic assisted movement training to improve gait and balance in elderly at risk of falling: a case series.

Shmuel Springer, Itamar Friedman, Avi Ohry

Abstract read
In one paragraph

Article in Clinical interventions in aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

3 authors.

Shmuel SpringerDepartment of Physical Therapy, Faculty of Health Sciences, Ariel University, Ariel, Israel.
Itamar FriedmanProMedoss, Charlotte, NC, USA.
Avi OhryFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAge-related changes in coordinated movement pattern of the thorax and pelvis may be one of the factors contributing to fall risk. This report describes the feasibility of using a new thoracopelvic assisted movement device to improve gait and balance in an elderly population with increased risk for falls.

methodsIn this case series, 19 older adults were recruited from an assisted living facility. All had gait difficulties (gait speed <1.0 m/s) and history of falls. Participants received 12 training sessions with the thoracopelvic assisted movement device. Functional performance was measured before, during (after 6 sessions), and after the 12 sessions. Outcomes measures were Timed Up and Go, Functional Reach Test, and the 10-meter Walk Test. Changes in outcomes were calculated for each participant in the context of minimal detectable change (MDC) values.

resultsMore than 25% of participants showed changes >MDC in their clinical measures after 6 treatment sessions, and more than half improved >MDC after 12 sessions. Six subjects (32%) improved their Timed Up and Go time by >4 seconds after 6 sessions, and 10 (53%) after 12 sessions. After the intervention, 4 subjects (21%) improved their 10-meter Walk Test velocity from limited community ambulation (0.4-0.8 m/s) to functional community ambulation (>0.8 m/s).

conclusionThoracopelvic assisted movement training that mimics normal walking pattern may have clinical implications, by improving skills that enhance balance and gait function. Additional randomized, controlled studies are required to examine the effects of this intervention on larger cohorts with a variety of subjects.

Indexed as

Task Performance and AnalysisAccidental FallsAgedExercise TherapyFemaleGaitGeriatric AssessmentHumansPostural BalanceTreatment OutcomeWalkingbalancegaitolder adultstraining

Identifiers

PMID29950824
PMCPMC6016007

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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.