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Record W2104639593 · doi:10.1093/ptj/68.8.1209

Evaluation of Two Support Methods for the Subluxated Shoulder of Hemiplegic Patients

2016· article· en· W2104639593 on OpenAlexaff
Renee Williams, Lynne Taffs, Terry Minuk

Bibliographic record

VenuePhysical Therapy · 2016
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsJuravinski HospitalMcMaster UniversityCanadian Physiotherapy Association
Fundersnot available
KeywordsShouldersMedicineSubluxationShoulder jointRadiographyRehabilitationShoulder Impingement SyndromePhysical therapyOrthodonticsSurgeryRotator cuff

Abstract

fetched live from OpenAlex

One of the most troublesome complications in the rehabilitation of hemiplegic patients is inferior subluxation of the glenohumeral joint. The purpose of this study was to determine which of two shoulder supports, the Bobath shoulder roll or the Henderson shoulder ring, would be more effective in the management of hemiplegic patients with a subluxated glenohumeral joint. To determine the degree of subluxation and the amount of reduction after application of a shoulder support, radiographs were taken of 26 hemiplegic patients with subluxated shoulders. Radiographs of the unsupported affected shoulder were compared with radiographs of the same shoulder with each support applied. Radiographs of the unaffected shoulder were used as a comparison in determining the amount of subluxation. An analysis of variance revealed no significant difference in the reduction of inferior subluxation between the two types of shoulder support. A significant difference in subluxation, however, existed between measurements of the unsupported affected shoulder and the unaffected shoulder (p less than .001) and between measurements of the unsupported affected shoulder and the supported affected shoulder (p less than .001). The results of this study demonstrate the benefits of the Bobath shoulder roll and the Henderson shoulder ring in the management of hemiplegic patients with subluxated shoulders.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.112

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.109
GPT teacher head0.488
Teacher spread0.379 · 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 designBench or experimental
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

Citations43
Published2016
Admission routes1
Has abstractyes

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