Core decompression combined with autologous bone marrow stem cells versus core decompression alone for patients with osteonecrosis of the femoral head: A meta-analysis
Bibliographic record
Abstract
BACKGROUND: The efficacy of core decompression plus autologous bone mesenchymal stem cells (BMSCs) for the treatment of osteonecrosis of the femoral head (ONFH) remains controversial. We conducted a systematic review and meta-analysis to explore the efficacy of core decompression combined with BMSCs for OFNH patients. METHODS: We searched PubMed, Embase, Web of Science, and the Cochrane library databases through October 2018 for randomized controlled trials (RCTs) assessing the effect of core decompression combined with BMSCs for OFNH patients. The primary outcome was the visual analog scale (VAS) score at 6 months, 12 months and 24 months. The pooled data were analyzed using Stata 12.0 software. RESULTS: Fourteen studies with 540 patients (core decompression + BMSCs = 275, core decompression alone = 265) were included in our meta-analysis. Compared with the core decompression alone group, the core decompression + BMSCs group showed a significant decrease in the VAS score at 6 months, 12 months and 24 months, and a decrease in the number of hips undergoing total hip arthroplasty (THA), the Western Ontario and McMaster Universities (WOMAC) score and the volume of the postoperative necrotic zone. Core decompression + autologous BMSCs was associated with an increase in HHS postoperatively. No significant difference existed in adverse events. CONCLUSIONS: Compared with core decompression alone in the treatment of ONFH, the combined utilization of core decompression and autologous BMSCs has better pain relief and clinical outcomes and can delay the collapse of the femoral head more effectively.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.050 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".