Clinical outcomes of arthroscopic partial meniscectomy at 10 years follow up - A retrospective cohort study
Bibliographic record
Abstract
Objectives: In recent times, the advent of newer meniscal repair systems and studies thereof seem to have implied that meniscectomy procedures should be abandoned or used only as a last resort procedure in most patients. This study was done to report the outcomes of partial meniscectomy done in indicated patients by a skilled arthroscopic surgeon at a long-term follow-up of 10 years. The indications and the appropriate strategy for performing this procedure are also described. Materials and Methods: One hundred consecutive patients who underwent arthroscopic partial meniscectomy (APM) over one year were evaluated 10 years later for functional and clinical outcomes. Results: A retrospective case series of 100 consecutive patients was conducted to study the clinical outcome of APM after 10 years. Their mean age was 41.23 ± 7.81 years. 70% of the selected patients were male. Medial meniscus involvement was the most common (73%). At their 10-year follow-up, the majority of cases were asymptomatic (72%), with a mean international knee documentation committee score of 86.90 ± 5.51. Mean Tegner Lysholm Knee score was 90.05 ± 10.21, the Western Ontario and McMaster Universities Arthritis Index score was 8.83 ± 6.19, and the Western Ontario meniscal evaluation tool score was 85.54 ± 10.91. The subjective assessment after surgery was “excellent” in the majority of patients (48%). Conclusion: With proper patient selection and accurate decision-making, patients operated with APM for isolated meniscus tears can return to their daily routine activities and have good clinical and functional outcomes. The technique of performing arthroscopy and the skill set of the operating surgeon may perhaps also be an important criterion influencing the outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".