Heterotopic Ossification After Revision Total Knee Arthroplasty
Bibliographic record
Abstract
A consecutive series of revision total knee arthroplasties done at two centers was evaluated for the presence of heterotopic ossification on radiographs taken before and after revision using the classification system of Harwin et al. Knee Society scores were obtained preoperatively and at annual intervals postoperatively. The patients' demographics and clinical scores were correlated with the incidence and grade of heterotopic ossification. Minimum 2-year followup was obtained in 135 of 151 patients who had revision total knee arthroplasty during this period (89%). The incidence of heterotopic ossification before revision surgery was 23%, which increased to 56% at most recent followup (mean, 30 months; range, 24-48 months). The only risk factor identified for the development of heterotopic ossification was the presence of infection (76%), which was significantly higher than the 47% incidence of heterotopic ossification in patients who did not have an infection. The average postoperative Knee Society score was lower in patients with heterotopic ossification compared with patients without heterotopic ossification (129 points versus 148 points). Patients with heterotopic ossification had significantly lower functional scores particularly on stair climbing but did not have a significantly decreased range of motion. Parameters not associated with subsequent development of heterotopic ossification included gender (males), patient size (body mass index), surgical time, operative approach, or number of prior knee procedures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".