Capsulotomy in Unstable Slipped Capital Femoral Epiphysis and the Odds of AVN: A Meta-analysis of Retrospective Studies
Bibliographic record
Abstract
BACKGROUND: Unstable slipped capital femoral epiphysis (SCFE) may lead to avascular necrosis (AVN) in up to 60% of patients. The aim of this study was to assess the best clinical evidence to determine the effect of capsular decompression (CD) on odds of AVN in unstable SCFE. METHODS: Medline, Embase, and Cochrane databases were systematically searched for comparative studies investigating AVN rates in unstable SCFE treated with or without CD (aspiration, percutaneous, or open). Quality was evaluated by the Newcastle Ottawa Scale. A comparative analysis with pooled effect estimates using random-effects modeling was calculated. Secondary analysis pooled AVN rates from both comparative studies and case series. RESULTS: Comparative analysis included 17 retrospective studies with 453 hips (201 with CD, 252 without CD). Thirty-four of 201 (17%) hips with CD developed AVN, while 67 of 252 (27%) hips without CD developed AVN. The odds of AVN for patients treated with or without CD [odds ratio=0.80, 95% confidence interval (CI): 0.48-1.35] was not statistically different. Subanalysis on patients treated with in situ pinning or positional reduction and pinning showed no difference in AVN rates with or without CD (odds ratio=0.97, 95% CI: 0.44-2.10). In the secondary analysis of 17 comparative studies and 23 case series, the average rate of AVN was 17%, 0.17 (95% CI: 0.13-0.23) for patients treated with CD (60/447 hips) and 28%, 0.28 (95% CI: 0.22-0.35) for patients treated without CD (129/464 hips). CONCLUSIONS: There was no statistically significant decrease in odds of AVN with CD. However, studies were limited by their retrospective nature and inadequate documentation of CD techniques; the majority lacked femoral head blood flow monitoring to demonstrate adequate decompression. Future prospective studies with carefully documented complete decompression may help to elucidate the effect of CD on AVN risk. Although there was no statistically different odds of AVN with or without CD, even this large meta-analysis was underpowered, and one cannot conclude that there was truly no difference in odds of AVN without an appropriately powered study. Therefore, we recommend routine CD for all unstable SCFEs pending additional research, as CD adds little to the surgical procedure and may minimize the risk of a devastating insult to the femoral head.
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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.038 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".