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Record W2108197324 · doi:10.1177/0269215511423279

Inpatient versus home-based rehabilitation for older adults with musculoskeletal disorders: a systematic review

2011· review· en· W2108197324 on OpenAlexafffund
Paul Stolee, Sarah N Lim, Lindsay Wilson, Christine Glenny

Bibliographic record

VenueClinical Rehabilitation · 2011
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsMedicineCINAHLRehabilitationMEDLINEPhysical therapyRandomized controlled trialSystematic reviewQuality of life (healthcare)Cohort studyPsychological interventionPsychiatryNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To review and summarize available evidence to compare the outcomes of home-based rehabilitation to inpatient rehabilitation for older patients with musculoskeletal conditions. DATA SOURCES: Relevant articles published prior to August 2011 were identified using MEDLINE, CINAHL and the Cochrane Central Register of Controlled Trials databases. REVIEW METHODS: English-language articles that compared patient outcomes of home-based and inpatient rehabilitation for older adults were included. Outpatient care was not included as home-based or inpatient rehabilitation. Methodological quality of included studies was evaluated by two reviewers using the PEDro scale. RESULTS: A systematic search yielded eight randomized controlled trials and four cohort studies. Older adults who received rehabilitation in the home had equal or higher gains than the inpatient group in function, cognition, and quality of life; they also reported higher satisfaction. CONCLUSION: Home-based rehabilitation may be an effective alternative for treating older patients with musculoskeletal conditions.

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)0.006
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.392
Teacher spread0.359 · 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 designSystematic review
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

Citations62
Published2011
Admission routes2
Has abstractyes

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