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Record W3095366911 · doi:10.3233/nre-203218

Functional improvement related to enrolment in a Parkinson’s disease rehabilitation program

2020· article· en· W3095366911 on OpenAlexaff
Beverley Chow, Florin Feloiu, Assunta Berardocco, David Ceglie, Shanker Nesathurai

Bibliographic record

VenueNeurorehabilitation · 2020
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsHotel Dieu Shaver Health and Rehabilitation CentreMcMaster University Medical Centre
Fundersnot available
KeywordsMedicinePhysical therapyPhysical medicine and rehabilitationGrip strengthParkinson's diseaseRehabilitationPsychologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder with manifestations such as tremors, rigidity and bradykinesia. OBJECTIVE: The objective of this study was to evaluate the efficacy of outpatient multidisciplinary rehabilitation. METHODS: 179 patients participated in the six-week program. The following outcomes were measured: Timed Up and Go (TUG), sit to stand five times (STSx5) and in 30 seconds (STS30), six minute walk distance (6MWD) and gait velocity (6MWV), MOCA, bilateral grip strength, 360-degree turn (360 R, 360 L) and bilateral nine hole peg test. Pre- and post- data was analyzed via paired t-tests. Multiple regression was used to determine age- or gender-affected outcomes. RESULTS: Patients showed a statistically significant improvement (p < 0.05) in all outcomes. Mean TUG improved by 1.63 seconds (s), STSx5 by 4.19s, STS30 by 2.37 repetitions, 6MWD by 66.8 metres, 6MWV by 0.15 m/s, MOCA by 1.50 points, 360 R by 1.17s, 360 L by 1.60s, Grip R by 0.78 kg, Grip L by 0.95 kg, 9HP R by 1.71s and 9HP L by 1.58s. Gender had no influence. Age was a statistically significant predictor in STSx5 and 6MW. CONCLUSIONS: An outpatient multidisciplinary program successfully decreased motor impairment and increased overall functional independence in PD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.341
Teacher spread0.320 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2020
Admission routes1
Has abstractyes

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