Evidence map›Paper›PMID 31695020›Full record

ArticleThe American journal of case reports2019

Effects of an Immersive Virtual Reality Environment on Muscle Strength, Proprioception, Balance, and Gait of a Middle-Aged Woman Who Had Total Knee Replacement: A Case Report.

Soungkyun Hong, GyuChang Lee

Abstract readCase Reports
In one paragraph

Article in The American journal of case reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

2 authors.

Soungkyun HongDepartment of Physical Therapy, Graduate School of Kyungnam University, Changwon, South Korea.
GyuChang LeeDepartment of Physical Therapy, Kyungnam University, Changwon, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The purpose of this case study was to apply a training program using virtual reality to a middle-aged woman who had total knee replacement surgery and to investigate its effects on her muscle strength, proprioception, balance, and gait ability. CASE REPORT The subject who participated in this study was a 62-year-old woman, who had been diagnosed with moderate osteoarthritis and had a total knee replacement. Post-operative treatment consisted of virtual reality training along with range of motion exercise of the knee joint, light quadriceps isometric exercise, and conventional physical therapy. This also included thermal and electric therapy for pain control conducted on 10 occasions (5 times a week for 2 weeks). Total treatment time, which included 30 min of conventional physical therapy, was 60 min. Measurement of the subject's lower extremity muscle strength after intervention decreased to 9.43 s, and the error in proprioception decreased to 1.5°. In addition, balance score increased to 56 points, and the time taken to measure gait ability decreased to 9.87 s. CONCLUSIONS The patient responded positively to rehabilitation using virtual reality, and her muscle strength, proprioception, balance, and gait ability improved. These results suggest that the application of rehabilitative training through virtual reality for total knee replacement patients warrants further study and consideration.

Indexed as

Virtual RealityArthroplasty, Replacement, KneeFemaleGaitHumansMiddle AgedMuscle StrengthPhysical Therapy ModalitiesPostural BalanceProprioceptionRecovery of Function

Identifiers

PMID31695020
PMCPMC6859930

What OpenQuestion holds

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Registered trials

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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.