Trochleoplasty with a flexible osteochondral flap
Bibliographic record
Abstract
Aims The Bereiter trochleoplasty has been used in our unit for 12 years to manage recurrent patellar instability in patients with severe trochlea dysplasia. The aim of this study was to document the outcome of a large consecutive cohort of patients who have undergone this operation. Patients and Methods Between June 2002 and August 2013, 214 consecutive trochleoplasties were carried out in 185 patients. There were 133 women and 52 men with a mean age of 21.3 years (14 to 38). All patients were offered yearly clinical and radiological follow-up. They completed the following patient reported outcome scores (PROMs): International Knee Documentation Committee subjective scale, the Kujala score, the Western Ontario and McMaster Universities Arthritis Index score and the short-form (SF)-12. Results Outcomes were available for 199 trochleoplasties in 173 patients giving a 93% follow-up rate at a mean of 4.43 years (1 to 12). There were no infections or deep vein thromboses. In total, 16 patients reported further patella dislocation, giving an 8.3% rate of recurrence. There were 27 re-operations, giving a rate of re-operation of 14%. Overall, 88% were satisfied with the operation and 90% felt that their symptoms had been improved. Conclusion All PROMs improved significantly post-operatively except for the mental component score of the SF-12. Trochleoplasty performed using a flexible osteochondral flap is an effective treatment for recurrent patellar instability in patients with severe trochlea dysplasia and gives good results in the medium term. Cite this article: Bone Joint J 2017;99-B:344–50.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".