Is the modified Gartland classification system important in deciding the need for operative management of supracondylar humerus fractures?
Bibliographic record
Abstract
PURPOSE: This study examined levels of agreement between paediatric orthopaedic surgeons in the need for operative management of extension-type supracondylar humerus fractures. METHODS: This was the second phase of a two-part study. De-identified baseline anteroposterior and lateral elbow radiographs from 60 paediatric patients with extension-type supracondylar humerus fractures were compiled. After classifying each fracture according to Gartland classification guidelines, radiographs were randomized, and surgeons indicated whether they would use operative or non-operative management to treat each fracture. Kappa statistics using pairwise comparisons were calculated to determine agreement levels. RESULTS: In total, 11 international surgeons participated, and 10/11 completed both survey rounds. The overall weighted interobserver agreement was moderate (0.530, 95%CI [0.215,0.854]) while overall weighted intraobserver agreement was substantial (0.740, 95%CI [0.513,0.963]). The largest variability in preferred treatment methods between surgeons was observed for type IIA fractures, with 6/11 preferring non-operative and 5/11 preferring operative management. The largest individual surgeon variability was observed for type IIA fractures, with 8/11 showing variability (defined by not having made the same decision for at least 90% of the cases) in choosing whether to operate. CONCLUSIONS: Our findings suggest moderate interobserver, and substantial intraobserver agreement in treatment decision making. The largest disagreements between surgeons were observed for type IIA and IIB fractures and treatment decisions did not follow expected trends based on surgeons' preferred treatment methods for each fracture type. This suggests differences in treatment approaches between surgeons in the management of type IIA fractures and highlights the role of other variables that underlie differences between surgeons' treatment preferences. LEVEL OF EVIDENCE: III.
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".