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Record W2020412195 · doi:10.4103/0973-6042.145249

Assessment of function in patients with rotator cuff tears: Functional test versus self-reported questionnaire

2014· article· en· W2020412195 on OpenAlexaboutno aff
Selda Başar, Seyit Çıtaker, Ulunay Kanatlı, BurakYagmur Ozturk, Sadettin Kılıçkap, NihanK Kafa

Bibliographic record

VenueInternational Journal of Shoulder Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRotator cuffMedicineTearsMagnetic resonance imagingRandomized controlled trialRange of motionPhysical therapyPhysical medicine and rehabilitationCuffSurgeryRadiology

Abstract

fetched live from OpenAlex

PURPOSE: The rotator cuff tears (RCT) are a well-known cause of shoulder pain and loss of upper extremity function. The purpose of this study was to evaluate the upper extremity function using two different methods in patients with RCT and to determine the parameters that influence the upper extremity function. MATERIALS AND METHODS: A sample of 38 patients (27-76 years; 10 men and 28 women) who were diagnosed with a chronic full-thickness RCT, confirmed by magnetic resonance imaging (MRI), was studied. Upper extremity function was determined using Western Ontario Rotator Cuff Index (WORC) and 9 Hole Peg Test (9PEG). Other assessments included active range of motion (ROM), muscle strength, shoulder pain, and scapular dyskinesis. RESULTS: There was a weak association between WORC scores and 9PEG. A statistically significant, negative relationship was found between 9PEG and ROM in supination, as well as muscle strength of shoulder extensors, adductors, internal and external rotators. CONCLUSIONS: In addition to the weak association between WORC and 9PEG, the difference between the parameters related to each method suggests that they should not be used interchangeably to determine the upper extremity function. We recommend the utilization of 9PEG instead of WORC in assessing the upper extremity function in the setting of loss of muscle strength. LEVEL OF EVIDENCE: Level IV, Therapeutic study.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.304
Teacher spread0.283 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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