Inter-observer and intra-observer reliability in the radiographic diagnosis of avascular necrosis of the femoral head following reconstructive hip surgery in children with cerebral palsy
Bibliographic record
Abstract
PURPOSE: The incidence of avascular necrosis (AVN) following reconstructive hip surgery in cerebral palsy (CP) ranges from 0 to 69 % in the current literature. The purpose of this study was to determine the inter- and intra-observer reliability of radiographically diagnosing AVN in children with CP after hip surgery. METHODS: A retrospective review of 65 children with CP who had reconstructive hip surgery between 2009 and 2012 at BC Children's Hospital was completed. Anterior-posterior and lateral radiographs were presented to four pediatric orthopaedic surgeons over two rounds. Surgeons were asked to review the set of unidentified radiographs and comment 'yes' or 'no' for the presence of AVN. Two weeks later the same set of radiographs was sent in a different order and the surgeons were again asked to comment on AVN. Inter- and intra-observer reliability was determined using kappa statistics. RESULTS: The intra-observer reliability ranged from 0.65 to 0.88 with an average score of 0.76. Inter-observer reliability showed greater variability, ranging from 0.41 to 0.77 with an average score of 0.56 across all surgeons. CONCLUSIONS: Although the intra-rater reliability produced a strength of "good" and the inter-rater reliability a strength of "moderate" agreement, the variability within these scores is clinically important as it demonstrates the difficulty in identifying AVN. This may explain the variability in AVN that is reported in the literature. The need for further education and research in the diagnosis of AVN in children with CP who have undergone reconstructive hip surgery is clinically necessary.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".