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Record W4398155110 · doi:10.1016/j.exger.2024.112460

Decadal analysis of efficacy and safety profiles of mesenchymal stem cells from varied sources in knee osteoarthritis patients: A systematic review and network meta-analysis

2024· review· en· W4398155110 on OpenAlexaboutno aff
Xiaofu Tang, Haiqiang Huang, Liang Hao

Bibliographic record

VenueExperimental Gerontology · 2024
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisOsteoarthritisMesenchymal stem cellMedicineInternal medicineBioinformaticsBiologyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Knee Osteoarthritis (KOA) is a debilitating degenerative joint ailment afflicting millions of patients. Numerous studies have assessed the efficacy of mesenchymal stem cells (MSCs) derived from various sources for KOA treatment, yet direct comparisons are scarce and inconsistent. Furthermore, network meta-analysis (NMA) conclusions require updating, while the safety of MSCs therapy remains contentious. This study evaluates therapeutic approaches involving MSCs from different sources in patients with KOA through randomized controlled trials (RCTs) and cohort studies. The objective is to compare the effectiveness and safety of MSCs strategies from various sources for KOA treatment. METHODS: A systematic literature review was conducted to identify RCTs and cohort studies comparing different sources of MSCs in KOA patients. A randomized effects network meta-analysis was used to concurrently evaluate both direct and indirect comparisons across all protocols. RESULTS: The NMA included 16 RCTS and reported 1005 participants. Adipose-derived mesenchymal stem cells (AD-MSCs) were the most effective treatment, showing significant improvements in the Visual Analogue Scale (VAS), the Short Form 36 (SF-36 scale), the International Knee Literature Committee Knee Evaluation Scale (IKDC subjective scores), and the Knee Injury and OA Outcome Score (KOOS). The probabilities are P = 85.3, P = 70.5, P = 88 and P = 87, respectively. Compared with placebo, AD-MSCs resulted in a VAS Score (SMD 0.97; 95%CI 0.37, 1.57), IKDC subjective scores (SMD -0.71; 95%CI -1.20, -0.21) was significantly reduced. Umbilical cord-derived mesenchymal stem cells (UC-MSCs) showed significant improvements in the University of Western Ontario and McMaster University OA (WOMAC) (P = 91.4). Compared with placebo, UC-MSCs had a higher WOMAC Score (SMD 1.65; 95%CI 0.27, 3.03) and ranked first. Compared with MSCs, placebo emerged as the safer option (P = 74.9), with a notable reduction in AEs associated with HA treatment (RR 0.77; 95%CI 0.61, 0.97). AD-MSCs were found to have the least favorable impact on AEs with a probability of P = 13.3. CONCLUSIONS: This network meta-analysis established that MSCs offer pain relief and enhance various knee scores in KOA patients compared to conventional treatment. It also identifies other therapeutic avenues warranting further exploration through high-quality studies. Nonetheless, it underscores the necessity to emphasize the potential complications and safety concerns associated with MSCs.

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 imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.047
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.044
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.095
GPT teacher head0.382
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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