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The intra- and inter-rater reliability of plain radiographs for Hill-Sachs and bony glenoid lesions: evaluation of the radiographic portion of the instability severity index score

2012· article· en· W2121611046 on OpenAlexaff
Martin Bouliane, Holman Chan, Kyle Kemp, Robert E. Glasgow, R. Lambert, Lauren A Beaupré, David M Sheps

Bibliographic record

VenueShoulder & Elbow · 2012
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsOttawa HospitalUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsMedicineRadiographyPlain radiographyOrthodonticsReliability (semiconductor)Inter-rater reliabilityRadiologyNuclear medicineMathematics

Abstract

fetched live from OpenAlex

Background The Instability Severity Index Score (ISIS) was developed to help determine the prognosis for recurrent shoulder instability and to assist surgical decision-making. The radiographic portion of the ISIS represents a substantial portion of the total score. The present study examined the intra- and inter-rater agreement, reliability and accuracy of the radiographic components of the ISIS. Methods Four assessors evaluated 49 blinded shoulder radiographs. Assessors documented their observation of the presence of a Hill–Sachs lesion and/or a loss of glenoid contour. Radiographs were reviewed twice in random order over two sessions. Intra- and inter-rater reliability and accuracy were calculated. Results Intra-rater agreement ranged from 71% to 94% for the presence of a Hill–Sachs lesion and 85% to 94% for a loss of glenoid contour. Intra-rater kappa values ranged from 0.41 to 0.86 and 0.56 to 0.74, respectively. Inter-rater agreement was found to be 63% to 78% and 78% to 90% for Hill–Sachs and glenoid lesions, respectively. Corresponding kappa values were 0.31 and 0.48. Accuracy ranged from 29% to 57% for Hill–Sachs and 65% to 73% for glenoid lesions. Conclusions In the present study, intra- and inter-rater reliability of the radiographic portion of the ISIS demonstrated limited kappa and accuracy. We suggest that the ISIS should be used with caution as a guide for surgical management.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.025
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.035
GPT teacher head0.316
Teacher spread0.281 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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