Changing trends in the use of cartilage restoration techniques for the patellofemoral joint: a systematic review
Bibliographic record
Abstract
PURPOSE: The patellofemoral (PF) joint contains the thickest articular cartilage in the human body. Chondral lesions to this area are often misdiagnosed and can predispose to secondary osteoarthritis if left untreated. Treatment options range from arthroscopic debridement to cartilage restoration techniques such as microfracture (MFx), autologous chondrocyte implantation (ACI), and osteochondral autograft transplantation. The purpose of this study was to systematically assess the trends in surgical techniques, outcomes, and complications of cartilage restoration of the PF joint. METHODS: This review has been conducted according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). The electronic databases PubMed, MEDLINE, and EMBASE were searched from January 1, 2007 to April 30, 2018. The Methodological Index for Non-randomized Studies (MINORS) was used to assess study quality. A two-proportion z test was used to determine whether the differences between the proportions of cartilage restoration techniques used from 2007 to 2012 and 2013-2018 were statistically significant. RESULTS: Overall, 28 studies were identified, including 708 patients (824 knees) with a mean age of 39.5 ± 10.5 years and a mean follow-up of 39.1 ± 16.0 months. Majority of patients were treated with ACI (45.5%) and MFx (29.6%). A significant increase in the use of the third generation ACI occurred with a simultaneous decreased usage of the conventional MFx over the last 5 years (p < 0.001). All techniques had significant (p < 0.05) improvements in clinical outcomes. The overall complication rate was 9.2%, of which graft hypertrophy (2.7%) was the most prevalent. CONCLUSIONS: ACI was the most common restoration technique. The use of third generation ACI has increased with a concurrent decline in the use of conventional MFx over the latter half of the past decade (p < 0.001). Overall, the various cartilage restoration techniques reported improvements in patient reported outcomes with low complication rates. Definitive conclusions on the optimal treatment remain elusive due to a lack of high-quality comparative studies. LEVEL OF EVIDENCE: Level IV, Systematic Review of Level-II-IV studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".