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Record W2014310850 · doi:10.1186/1471-2474-14-70

Radiographic union score for hip substantially improves agreement between surgeons and radiologists

2013· article· en· W2014310850 on OpenAlexaff
Mohit Bhandari, Mary M. Chiavaras, Naveen Parasu, Hema Choudur, Olufemi R. Ayeni, Rajesh Chakravertty, Simrit Bains, A. Elisabeth Hak, Sheila Sprague, Brad Petrisor

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2013
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsWestern UniversityCanada Research ChairsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineOrthopedic surgeryRadiographyHip fractureChecklistBone healingFemoral neckSports medicineSurgeryPhysical therapyInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the prominence of hip fractures in orthopedic trauma, the assessment of fracture healing using radiographs remains subjective. The variability in the assessment of fracture healing has important implications for both clinical research and patient care. With little existing literature regarding reliable consensus on hip fracture healing, this study was conducted to determine inter-rater reliability between orthopedic surgeons and radiologists on healing assessments using sequential radiographs in patients with hip fractures. Secondary objectives included evaluating a checklist designed to assess hip fracture healing and determining whether agreement improved when reviewers were aware of the timing of the x-rays in relation to the patients' surgery. METHODS: A panel of six reviewers (three orthopedic surgeons and three radiologists) independently assessed fracture healing using sequential radiographs from 100 patients with femoral neck fractures and 100 patients with intertrochanteric fractures. During their independent review they also completed a previously developed radiographic checklist (Radiographic Union Score for Hip (RUSH)). Inter and intra-rater reliability scores were calculated. Data from the current study was compared to the findings from a previously conducted study where the same reviewers, unaware of the timing of the x-rays, completed the RUSH score. RESULTS: The agreement between surgeons and radiologists for fracture healing was moderate for "general impression of fracture healing" in both femoral neck (ICC = 0.60, 95% CI: 0.42-0.71) and intertrochanteric fractures (0.50, 95% CI: 0.33-0.62). Using a standardized checklist (RUSH), agreement was almost perfect in both femoral neck (ICC = 0.85, 95% CI: 0.82-0.87) and intertrochanteric fractures (0.88, 95% CI: 0.86-0.90). We also found a high degree of correlation between healing and the total RUSH score using a Receiver Operating Characteristic (ROC) analysis, there was an area under the curve of 0.993 for femoral neck cases and 0.989 for intertrochanteric cases. Agreement within the radiologist group and within the surgeon group did not significantly differ in our analyses. In all cases, radiographs in which the time from surgery was known resulted in higher agreement scores compared to those from the previous study in which reviewers were unaware of the time the radiograph was obtained. CONCLUSIONS: Agreement in hip fracture radiographic healing may be improved with the use of a standardized checklist and appears highly influenced by the timing of the radiograph. These findings should be considered when evaluating patient outcomes and in clinical studies involving patients with hip fractures. Future research initiatives are required to further evaluate the RUSH checklist.

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)0.045
metaresearch head score (Gemma)0.123
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 score0.045
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.123
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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

Citations71
Published2013
Admission routes1
Has abstractyes

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