Arthroscopic Treatment of Acetabular Condral Defects Using BST-CarGel
Bibliographic record
Abstract
Objectives: The purpose of this study is to retrospectively analyze prospectively collected data to evaluate the shortterm outcome of patients treated arthroscopically with BSTCarGel for acetabular chondral defect. Methods: Between November 2014 and December 2015, 22 patients (23 hips) underwent hip arthroscopy for correction of femoroacetabular impingement, labral repair and treatment of acetabular chondral defect. Patient evaluations included general assessment with iHOT33 questionnaire at the time of preoperative consultation, and the postoperative followup at 2 weeks, 6 weeks, 3 months, 6 months, 1 year and 2 year marks. Additionally, preoperative and postoperative plain radiographs and MRarthrogram scans were analyzed for evaluation. Results: 22 patients (23 hips) have been evaluated with a mean age of 33.34 years at the time of the index operation. There were 16 males (17 hips, mean age of 32.00) and 6 female (6 hips, mean age of 37.15). The average followup was 1 year, with a minimum followup of 6 months. The preoperative iHOT33 score was 47.1, the 6 months postoperative score was 54.8, and the 12 month postoperative score was 63.7 (p < 0.05) MRIArthrograms demonstrated a decrease in the size of the chondral defects. No significant adverse outcomes have been reported. Conclusion: Arthroscopic treatment of chondral acetabular defect with BSTCarGel demonstrates encouraging signs of cartilage healing as shown on MRarthrograms, without significant adverse outcomes. Longer followup is required to determine if this improvement is maintained.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".