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Record W3011405158 · doi:10.1097/md.0000000000019434

Clinical efficacy and safety of stem cell therapy for knee osteoarthritis

2020· review· en· W3011405158 on OpenAlexaboutno aff
Rui Huang, Wei Li, Ying Zhao, Fan Yang, Meng Xu

Bibliographic record

VenueMedicine · 2020
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisCochrane LibraryPhysical therapyVisual analogue scaleRandomized controlled trialMeta-analysisSurgeryInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: We performed a meta-analysis of the efficacy and safety of stem cell therapy as a clinical treatment of knee osteoarthritis. This meta-analysis is expected to provide evidence of the efficacy of stem cell therapy, which is currently controversial, as a conservative treatment for knee osteoarthritis. METHODS: An online search for relevant articles was conducted in the PubMed, EMBASE, and Cochrane Library databases. The search terms were "stem cells" and "osteoarthritis." We conducted a quality assessment of the included articles and extracted the following indicators: Visual Analogue Scale (VAS) score, Subjective International Knee Documentation Committee (IKDC) score, Western Ontario and McMaster Universities (WOMAC) subscales, and adverse events. The RevMan5.3 software was used for determining effect sizes. RESULTS: Nine randomized controlled trials involving 339 patients were included. VAS score and IKDC score from baseline to 24 months were improved in the stem cell therapy group compared to those in the control group. However, no significant difference was observed between the 2 groups in IKDC score changes from baseline to 6 and 12 months, as well as in WOMAC-Pain, WOMAC-Stiffness, and WOMAC-Physical Function score changes at each visit point. CONCLUSION: Stem cell therapy is certainly superior to traditional treatments in the conservative treatment of KOA; it considerably reduces pain with no obvious additional side effects.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.448
Teacher spread0.292 · 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 teacher head, not a consensus.

Study designOther design
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

Citations24
Published2020
Admission routes1
Has abstractyes

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