Outcomes Following Stem Cell-Based Therapies for Hip Osteoarthritis: A Scoping Review
Bibliographic record
Abstract
Hip osteoarthritis (OA) is a prevalent and debilitating condition for which current treatment options remain limited, especially in early to moderate stages. Stem cell-based therapies, particularly those using mesenchymal stem cells (MSCs), have gained attention due to their potential regenerative and anti-inflammatory properties. This scoping review aimed to map and summarize current clinical evidence on the efficacy and safety of intra-articular stem cell therapies for hip OA. This review followed the PRISMA-ScR guidelines and was registered on the Open Science Framework (DOI: 10.17605/OSF.IO/G8V9S). A systematic search of PubMed, Embase, Cochrane Library, Web of Science, and Scopus was conducted from December 2024 to January 2025. Inclusion criteria comprised clinical studies evaluating intra-articular stem cell-based therapies in adults with hip OA. Excluded were non-clinical studies, reviews, and studies involving joints other than the hip or non-stem cell interventions. Two reviewers independently selected studies and extracted data, resolving disagreements through discussion with a third reviewer. Out of 286 records identified, 9 studies met the inclusion criteria. These included five cohort studies and four case series, assessing various MSC sources: bone marrow-derived MSCs (BM-MSCs), adipose-derived MSCs (AD-MSCs), stromal vascular fraction (SVF), and amniotic-derived preparations. Pain reduction was consistently observed, with average visual analog scale (VAS) score reductions of 30-50%. Functional improvement was reported via metrics like the Harris Hip Score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Radiologic evidence of cartilage repair was limited and inconsistent. Adverse events were rare and mild, including transient joint discomfort and local swelling, with no major complications reported. Stem cell-based therapies show promising short- to mid-term outcomes in pain relief and functional improvement for hip OA, with favorable safety profiles. However, heterogeneity in study designs and limited long-term structural outcomes highlight the need for standardized protocols and robust randomized trials to confirm regenerative efficacy.
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 | 0.018 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".