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Record W2886298817 · doi:10.1097/phm.0000000000001007

The Impact of Introducing a Physical Medicine and Rehabilitation Trauma Consultation Service to an Academic Level 1 Trauma Center

2018· article· en· W2886298817 on OpenAlexaff
Lawrence R. Robinson, Alan Tam, Shannon L. MacDonald, Edwin Hanada, David Berbrayer, Abdikarim Abdullahi, Bruna G. Camilotti, Homer Tien

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2018
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineTrauma centerRehabilitationRetrospective cohort studyAcute careEmergency medicinePhysical therapyInternal medicineHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: Previous retrospective studies suggest that early physical medicine and rehabilitation (PM&R) consultation for trauma patients improves outcome and reduces acute care length of stay (LOS). There have not been controlled studies to evaluate this impact. This study assesses the impact of PM&R consultations on acute trauma patients. DESIGN: This study compared measured outcomes before and after the introduction of a PM&R consultation service to the trauma program at a large academic hospital. The primary outcome measure was acute care LOS. RESULTS: The 274 historical controls and 76 patients who received a PM&R consultation were not different in injury severity score, age, or sex. Length of stay was not different between the two groups. However, when early (≤8 days after injury) versus late (>8 days) consults were compared, the early group had a markedly lower LOS (12 vs. 30 days, P < 0.001). When adjusted for injury severity score, an early consult was associated with an 11.8-day lower LOS (P < 0.001). The early consult group also had fewer complications and less usage of benzodiazepines and antipsychotics. CONCLUSIONS: An acute care PM&R consultation of 8 days or less after admission is associated with a shorter acute care LOS, fewer complications, and less use of benzodiazepines and antipsychotics.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
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 head0.030
GPT teacher head0.392
Teacher spread0.363 · 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 designOther design
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
Published2018
Admission routes1
Has abstractyes

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