Microfractures, autologous matrix-induced chondrogenesis, osteochondral autograft transplantation and autologous chondrocyte implantation for knee chondral defects: a systematic review and network meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Purpose: Despite the publication of several randomized controlled trials (RCTs), it is not clear which technique for the treatment of focal chondral and osteochondral defects of the knee grants the best clinical outcome. The aim of this network meta-analysis (NMA) was to compare the efficacy and safety of microfractures (MF), autologous chondrocyte implantation (ACI), autologous matrix-induced chondrogenesis (AMIC), osteochondral autograft transplantation (OCT) at short (< 1 year), intermediate (1-5 years) and long-term (> 5 years). Methods: We carried out an NMA with Bayesian random-effect model, according to PRISMA guidelines. The search was performed in MEDLINE, EMBASE, Web of Science, CENTRAL, CINAHL, SPORTDiscus, clinicaltrials.gov, WHO ICTRP, from inception to November 2022. The eligibilities were randomized controlled trials on patients with knee chondral and osteochondral defects, undergoing microfractures, OCT, AMIC, ACI, without restrictions for prior or concomitant surgery on ligaments, menisci or limb alignment, prior surgery for fixation or ablation of osteochondritis dissecans fragments, and prior cartilage procedures as microfractures, drilling, abrasion, or debridement. Results: Nineteen RCTs were included. No difference among treatments was shown in the pooled comparison of patient reported outcome measures (PROMs) at any timepoint. Safety data were not available for all trials due to the heterogeneity of reporting, but chondrospheres seemed to have lower failure and reoperation rates. Conclusion: This NMA showed no difference for PROMs with any technique. The lower failure and reoperation rates with chondrospheres must be interpreted with caution since adverse event data was heterogenous among trials. The standardization of the efficacy and safety outcome measures for future trials on knee cartilage repair and regeneration is necessary.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.030 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".