Stem cell therapy for the treatment of early stage avascular necrosis of the femoral head: a systematic review
Bibliographic record
Abstract
BACKGROUND: Avascular necrosis (AVN) of the femoral head (FH) is believed to be caused by a multitude of etiologic factors and is associated with significant morbidity in younger populations. Eventually, the disease progresses and results in FH collapse. Thus, a focus on early disease management aimed at joint preservation by preventing or delaying progression is key. The use of stem cells (SC) for the treatment of AVN of the FH has been proposed. We undertook a systematic review of the medical literature examining the use of SC for the treatment of early stage (precollapse) AVN of the FH, in both pre-clinical and clinical studies. METHODS: Data collected included: Pre-clinical studies - model of AVN, variety and dosage of SC, histologic and imaging analyses. Clinical studies - study design, classification and etiology of AVN, SC dosage and treatment protocol, incidence of disease progression, patient reported outcomes, volume of necrotic lesion and hip survivorship. RESULTS: In pre-clinical studies, the use of SC uniformly demonstrated improvements in osteogenesis and angiogenesis, yet source of implanted SC was variable. In clinical studies, groups treated with SC showed significant improvements in patient reported outcomes; however hip survivorship was not affected. Discrepancies regarding dose of SC, AVN etiology and disease severity were present. CONCLUSIONS: Routine use of this treatment method will first require further research into dose and quality optimization as well as confirmed improvements in hip survivorship.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".