Establishing the Relationship Between Clinical Outcome and Extent of Osseous Bridging Between Computed Tomography Assessment in Isolated Hindfoot and Ankle Fusions
Bibliographic record
Abstract
BACKGROUND: Determining the success of joint fusion operations is often a diagnostic dilemma, and many factors may be considered. Most would agree that the broad categories of clinical success and radiographic success are likely most useful to determine the overall success of a joint fusion operation. Very little evidence exists to assist the surgeon in determining what constitutes a successful radiographic fusion. The aim of this study was to determine the extent of osseous bridging as measured by computed tomography (CT) that was associated with a good clinical outcome as measured by the 12-Item Short Form (SF-12), Foot Function Index (FFI), and American Orthopaedic Foot & Ankle Society (AOFAS) clinical outcomes questionnaires at 24 weeks. METHODS: Patients who had isolated joint fusions were evaluated (n = 275) to determine the correlation of extent of osseous bridging with clinical outcome. The extent of osseous bridging across the joint in question was categorized as absent (0%-24%), minimal (25%-49%) moderate (50%-74%), or complete (75%-100%). Clinical outcome scores included the SF-12, FFI, and AOFAS outcomes score. RESULTS: Patients evaluated to have at least minimal osseous bridging at fusion sites (25%-49%) on CT reported a clinically important improvement in SF-12, FFI, and AOFAS, whereas those with "absent" osseous bridging (0%-24%) did not report a clinically important improvement in outcome scores. CONCLUSION: This study suggests that osseous bridging of greater than 25% to 49% at the fusion site measured by CT may be necessary to consider a hindfoot or ankle fusion clinically successful. LEVEL OF EVIDENCE: Level IV, case series.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".