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Record W4385163540 · doi:10.52225/narrax.v1i1.73

Exergame for post-stroke rehabilitation among elderly patients: A systematic review and meta-analysis

2023· review· en· W4385163540 on OpenAlexaboutno aff
Teuku F. Duta, ⁠⁠Ghina Tsurayya, Muhammad A. Naufal

Bibliographic record

VenueNarra X · 2023
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationMeta-analysisObservational studyStroke (engine)Physical therapyRandomized controlled trialCognitionCognitive rehabilitation therapyPhysical medicine and rehabilitationMedicineSystematic reviewMEDLINEPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Advancement in gaming technology, including exergame, is thought to offer a promising innovation in rehabilitative treatment owing to its interactive and joyful natures. Elderly, in addition to being prevalent in stroke, they have different perspectives and adaptability toward the utilization of exergame in post-stroke rehabilitation. The aim of this study was to evaluate the effectiveness of exergame-based rehabilitation in ameliorating stroke-associated cognitive impairment among elderly patients. This systematic review followed the Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) guideline. The literatures were retrieved from the searches on PubMed, Scopus, and Embase databases using a combination of ‘exergame’, ‘stroke’, and ‘elderly’ along with their respective synonyms. Included studies were controlled observational studies and randomized clinical trials with subjects’ mean age >60 years old, measuring global cognitive and/or five cognitive domains (attention, language, executive function, memory, and visuospatial ability). Quality appraisals were performed based on the Cochrane ‘risk-of-bias tool’ and Physiotherapy Evidence Database Scale. Studies with high and good qualities were included in the meta-analyses. Six randomized controlled trials involving 179 patients were included in meta-analysis. Studies had variations in terms of type (combination of exergame-based and conventional rehabilitation or exergame-based only) and duration of interventions (30–110 min), length of observation (2–6 weeks), and tools used to examine cognitive outcomes. As compared with conventional rehabilitation, exergame-based rehabilitation was significantly more effective to improve global cognitive based on Montreal Cognitive Assessment Score in acute stroke patients (n=4; mean difference (MD) 3.66; 95% confidence interval (95%CI): 2.08, 5.24; p<0.00001), but significantly less effective in chronic stroke patients (n=2; MD -1.54; 95%CI: -2.28, -0.81; p<0.0001). In conclusion, global cognitive of elderly patients with acute strokes could be improved through exergame-based rehabilitation which is more effective as compared with conventional therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.038
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.357
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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