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Record W4386594644 · doi:10.1186/s13287-023-03475-5

What is the optimal dose of adipose-derived mesenchymal stem cells treatment for knee osteoarthritis? A conventional and network meta-analysis of randomized controlled trials

2023· review· en· W4386594644 on OpenAlexaboutno aff
Zongyuan Huang, Shuai Zhang, Mingde Cao, Zhujian Lin, Lingquan Kong, Xin Wu, Qianshi Guo, Yuxiang Ouyang, Yancheng Song

Bibliographic record

VenueStem Cell Research & Therapy · 2023
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
FundersNatural Science Foundation of Guangdong Province
KeywordsMesenchymal stem cellOsteoarthritisMedicineWOMACMeta-analysisRandomized controlled trialVisual analogue scaleAdverse effectCell therapyAdipose tissueStem cellStem-cell therapyClinical trialInternal medicineSurgeryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Despite increasing clinical investigations underscoring the efficacy and safety of adipose-derived mesenchymal stem cells (AD-MSCs) therapy in knee osteoarthritis (KOA), no article has recently reviewed the cell dosage. This study aimed to evaluate the efficacy and safety of varying doses of AD-MSCs in treating KOA using conventional and network meta-analysis. METHODS: A search of databases in in Chinese and English was performed to identify randomized controlled trials (RCT) on MSCs for knee osteoarthritis from the inception date to May 1, 2022. This study mainly analyzed the efficacy of AD-MSCs in the treatment of KOA, and subgroup analysis was performed on the therapeutic effects of MSCs from different tissues at the same dose. We divided the different cell doses into low, moderate, and high groups, with the corresponding cell doses: (0-25)*10^6, (25-50)*10^6, and > 50*10^6 cells, respectively. We further analyzed the improvement of improvement of the Visual Analog Scale (VAS) and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores and the incidence of adverse events (AEs) after varied dosage injection. RESULTS: A total of 16 literatures were included in this study, of which 8 literatures were about AD-MSCs. Conventional meta-analysis suggests that AD-MSCs can reduce pain and improve function in KOA patients, regardless of the cell doses, up to 12 months of follow-up. The network meta-analysis showed that intra-articular injection of AD-MSCs significantly improved pain and knee function scores in KOA patients compared with the control group at 3, 6, and 12 months. Among the three groups, the high-dose group had the best treatment effect, and the degree of joint pain and dysfunction indicators improved more significantly in the early stage. For adverse events, there was a dose-response trend that increased with increasing doses. CONCLUSIONS: Both cell doses reduced pain and improved knee function in KOA patients. The effect surpassed in the high-dose group than in the moderate-dose, low-dose and control groups. However, adverse events also increase with the increase in dose, which should be carefully considered in clinical application, and the side effects still need to be paid attention to. Considering the limitations of this meta-analysis, future studies need to further explore the efficacy and safety of different doses of treatment, and carry out large sample, multi-center, randomized controlled trials to ensure the reliability and promotion value of the research results.

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)0.045
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
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 score0.974
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.077
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0260.054
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.363
GPT teacher head0.465
Teacher spread0.102 · 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.

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

Citations32
Published2023
Admission routes1
Has abstractyes

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