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Record W4313020605 · doi:10.1177/1759720x221146005

The role of adipose-derived mesenchymal stem cells in knee osteoarthritis: a meta-analysis of randomized controlled trials

2022· article· en· W4313020605 on OpenAlexaboutno aff
Mohamad Issa, Ahmad Naja, Nour Bouji, Bernard H. Sagherian

Bibliographic record

VenueTherapeutic Advances in Musculoskeletal Disease · 2022
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisWOMACMeta-analysisRandomized controlled trialKnee painPhysical therapyCochrane LibraryQuality of life (healthcare)PlaceboKnee JointInternal medicineSurgeryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Background: Adipose-derived mesenchymal stem cells (ADMSCs) have recently been studied for the treatment of knee osteoarthritis. The goal is pain reduction and improvement of joint function leading to superior health-related quality of life. Objectives: The aim of this study was to provide a comprehensive meta-analysis assessing the evidence on the use of ADMSCs in knee osteoarthritis. Design: This is a Meta-analysis of randomised controlled trials. Data Sources and Methods: PubMed/MEDLINE, Embase, and Cochrane Databases were searched for randomized controlled trials using ADMSCs to treat patients with knee osteoarthritis. Only trials comparing ADMSCs to placebo or conservative treatment were included. The outcomes studied were improvement in functional, pain, and quality of life scores along with radiographic findings. Results: value < 0.0001). Conclusion: ADMSCs are effective in treating knee osteoarthritis symptoms as observed by functional and pain improvements. Furthermore, ADMSCs injection showed improvement of cartilage integrity, which indicates the potential for regenerating the knee cartilage. Future trials with larger number of patients and longer follow-up periods would help to elaborate further the therapeutic potential of ADMSCs. Plain Language Summary: Knee osteoarthritis is an extremely common disease that causes damage of the lining of the knee joint.This will lead to pain and limited range of motion of the knee hence limited functionality.Multiple treatments are used currently for knee osteoarthritis which all aim at slowing down the progression and limiting the need for knee replacement surgery.Adipose-derived mesenchymal stem cells (ADMSCs) are stem cells harvested from the fat around the belly. These stem cells have the potential to be converted into cells of a certain origin (cartilage, muscle, fat).Many studies are being performed to see whether these cells can transform to cartilage and repair the damaged knee joint.In this study, we tried to find how the results of different studies comparing the usual treatments for knee osteoarthritis with that of ADMSCs compared.We were mostly interested in the pain, functional, stiffness, and quality of life scores.We also reviewed the MRI findings to find out whether the lining of the knee joint improved.Four studies were included with 138 patients having knee osteoarthritis.WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) score which is a self-administered questionnaire evaluating hip and knee osteoarthritis, showed better results in patients receiving ADMSC injections compared with other usual treatments at 12-month follow-up.Pain, functional, stiffness, and quality of life scores also showed better results in ADMSCs at 12-month follow-up.MRI images also showed better cartilage lining in the patients treated with ADMSCs.We concluded that ADMSCs are both effective and safe to be used in treating knee osteoarthritis symptoms. However, studies with longer follow-up periods are needed to better assess the regenerative potential of ADMSCs.

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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.540
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.007
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.343
Teacher spread0.309 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations26
Published2022
Admission routes1
Has abstractyes

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