Three-Dimensional Imaging of Displaced Intra-articular Calcaneal Fractures Correlates With the Perioperative Diagnosis
Bibliographic record
Abstract
BACKGROUND: Intra-articular calcaneal fractures are complex injuries, and CT imaging has become the standard imaging in the preoperative assessment. Most classifications of these fractures are CT-based but have been associated with limited interobserver agreement. Three-dimensional imaging has become widely available and may give a better perspective but often with 1 image only. There is not much evidence of the added value of this imaging, compared with the CT imaging. METHODS: Eight experienced trauma surgeons assessed 28 different intra-articular calcaneal fractures, on conventional radiology (CR), CT, and 3-D imaging. All had extensive experience in the diagnosis and treatment of this difficult injury. The main questions concerned Sanders classification, the severity of the injury and the difficulty of the operative procedure, choice of approach, and choice of procedure. RESULTS: The classical 2-D CT imaging of the fractures were associated with a higher Sanders classification ranking, compared with the 3-D imaging scores. However, the interobserver agreement, as measured by the Fleiss kappa, was low for all 3 imaging modalities. We found more frequent Sanders III and IV classifications with CT scan imaging compared with 3-D imaging or CR. The scores obtained after assessing 3-D imaging were also not statistically significantly different from the scores of a consensus achieved by 2 authors and based on the 3 imaging modalities and the perioperative diagnosis. CONCLUSION: The 3-D imaging may result in a more realistic view, reducing the frequency of classifying Sanders III fractures than with the 2-D CT imaging series. 3-D imaging may be more reliable than CT in the planning of operative treatment of displaced intra-articular calcaneal fractures. LEVEL OF EVIDENCE: Level III.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".