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Rehabilitation of proximal humerus fractures: An environmental scan of Canadian physiotherapy practice patterns

2017· article· en· W6921017899 on OpenAlexaboutno aff

Bibliographic record

VenueINDIGO (University of Illinois at Chicago) · 2017
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationProximal humerusReferralPsychological interventionRetrainingRange of motionRespondentOrthopedic surgery

Abstract

fetched live from OpenAlex

<div>\n\n<p><small><b>Background:</b> Proximal humerus fractures (PHFs) are \ncommon injuries particularly in older adults. Evidence-based protocols \nfor PHF rehabilitation are lacking and physiotherapists use a variety of\n interventions.</small></p>\n\n<p><b>Purpose:</b> To determine practice patterns and perceptions of physiotherapists who treat adults with PHF in Ontario, Canada.</p>\n\n<p><b>Method:</b> A paper and pencil survey asking about respondent \ndemographics and management of Neer Group 1 (minimally/nondisplaced) and\n complex (displaced 3- and 4-part) PHF was mailed to 875 randomly \nselected physiotherapists who were registered with the College of \nPhysiotherapists of Ontario in 2013/2014 and working in practice areas \nlikely to be accessed by adults with PHF.</p>\n\n<p><b>Results:</b> The response rate was low (10%); 83 physiotherapists \ncompleted the survey - 80% had experience managing PHF. Respondents \ntreated 1-5 individuals with PHF annually; more treated Neer Group 1 PHF\n (89%) than complex PHF (68%). Most individuals with PHF were older than\n 60 years (64%), female (76%) and accessed physiotherapy through a \ndoctor’s referral (91%) more than 1 month post injury (33%).</p>\n\n<p><b>Main findings:</b> Physiotherapists manage PHF using \nmulti-component interventions and a minimum of 76% include the following\n elements: education and progression of passive, active assisted, active\n range of motion exercises and muscle retraining to build coordination \nand strength. Use of other elements was variable. The main factors \ninfluencing the treatment plan were the ability of the individual with \nPHF to comply, bone quality, and fracture type. Most respondents were \nunsure that there is sufficient PHF rehabilitation literature to guide \ntreatment.</p>\n\n<p><b>Conclusions:</b>This environmental scan is the first North \nAmerican study to document practice patterns and attitudes of \nphysiotherapists providing PHF rehabilitation. Elements used by \nphysiotherapists in Ontario treating small numbers of individuals with \nNeer Group 1 or complex PHFs each year align well with the limited PHF \nrehabilitation literature available.</p>\n\n<p><b>Potential implications:</b>Multi-disciplinary collaborations to \ndesign and conduct large, high quality, multi-centre prognostic studies \nand RCTs that evaluate the effectiveness of key aspects of non-surgical \nPHF rehabilitation in various patient groups are needed. Meanwhile, \nconsensus guidelines should be developed in the context of \nregion-specific physiotherapy service models to inform best practice in \nPHF rehabilitation management.</p>\n\n\n</div>

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.280
Teacher spread0.266 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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