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Record W2415071975

CLINICAL RELIABILITY AND DIAGNOSTIC ACCURACY OF VISUAL SCAPULOHUMERAL MOVEMENT EVALUATION IN DETECTING PATIENTS WITH SHOULDER IMPAIRMENT.

2015· article· en· W2415071975 on OpenAlexaff
Craig A. Wassinger, Duane A. Williams, Stephan Milosavljevic, Eric J. Hegedus

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineInter-rater reliabilityKappaCronbach's alphaReliability (semiconductor)Cohen's kappaPhysical medicine and rehabilitationPhysical therapyIntra-rater reliabilityRehabilitationContingency tableStatisticConfidence intervalPsychometricsPsychologyStatisticsMachine learningRating scaleComputer science
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical investigation of shoulder injuries commonly utilizes visual evaluation of scapular movement to determine if abnormal or asymmetrical movements are related to the injury. To date, the intrarater reliability and diagnostic accuracy of visual evaluation of scapular movement among physical therapists are not known. PURPOSE: The aims of this study were to determine the clinical reliability and diagnostic accuracy of physical therapists visual evaluation of scapulohumeral movements when used to diagnose shoulder impairment. STUDY DESIGN: University based laboratory and an internet based survey. METHODS: Thirty-three physical therapists and 12 patient participants participated in this study. Reliability was measured as percent agreement and using the free marginal kappa statistic (κ) and Cronbach's alpha (α) for interrater and intrarater reliability respectively. Diagnostic accuracy variables such as sensitivity, specificity, likelihood ratios were calculated from contingency table analysis. RESULTS: Visual evaluation yielded the following (95% CI): diagnostic accuracy 49.5%, specificity 60% (56 - 64), and sensitivity 35% (29 - 41), positive and negative likelihood ratios were 0.87 (0.66 - 1.14) and 1.09 (0.92 - 1.27) respectively. Percent agreements of evaluation findings between sessions for static and dynamic symmetry were 69% and 68%, respectively. The alpha statistics for static and dynamic symmetry were both 0.51. Percentage agreement in determining the injured shoulder was 59%, with an alpha statistic of 0.35. CONCLUSION: Visual evaluation of scapular movements, without additional clinical information, demonstrated a poor to fair reliability and poor to fair diagnostic accuracy. CLINICAL RELEVANCE: The clinical utility of the use of isolated visual scapular evaluation is cautioned. More reliable and valid objective measures are needed for diagnosing shoulder impairment. LEVEL OF EVIDENCE: 2b, Exploratory cohort 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.052
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.369
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), 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
Published2015
Admission routes1
Has abstractyes

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