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Record W2891867924 · doi:10.1093/ptj/pzy145

Conceptual Framework for an Episode of Rehabilitative Care After Surgical Repair of Hip Fracture

2019· article· en· W2891867924 on OpenAlexaff
Katie Jane Sheehan, Toby O. Smith, Finbarr C. Martin, Antony Johansen, Avril Drummond, Lauren A Beaupré, Jay Magaziner, Julie Whitney, Ami Hommel, Ian D. Cameron, I Price, Catherine Sackley

Bibliographic record

VenuePhysical Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of Alberta
FundersNational Institute on AgingNational Institutes of HealthNational Institute for Health and Care Research
KeywordsRehabilitationHip fractureOperationalizationScope (computer science)Physical therapyMedicinePhysical medicine and rehabilitationComputer scienceOsteoporosis

Abstract

fetched live from OpenAlex

Researchers face a challenge when evaluating the effectiveness of rehabilitation after a surgical procedure for hip fracture. Reported outcomes of rehabilitation will vary depending on the end point of the episode of care. Evaluation at an inappropriate end point might suggest a lack of effectiveness leading to the underuse of rehabilitation that could improve outcomes. The purpose of this article is to describe a conceptual framework for a continuum-care episode of rehabilitation after a surgical procedure for hip fracture. Definitions are proposed for the index event, end point, and service scope of the episode. Challenges in defining the episode of care and operationalizing the episode, and next steps for researchers are discussed. The episode described is intended to apply to all patients eligible for entry to rehabilitation after hip fracture and includes most functional recovery end points. This framework will provide a guide for rehabilitation researchers when designing and interpreting evaluations of the effectiveness of rehabilitation after hip fracture. Evaluation of all potential care episodes facilitates transparency in reporting of outcomes, enabling researchers to determine the true effectiveness of rehabilitation after a surgical procedure for hip fracture.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.345
Teacher spread0.326 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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