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Record W4404254046 · doi:10.3390/life14111468

Effects of Intra-Articular Stromal Vascular Fraction Injection on Clinical Symptoms and Cartilage Health in Osteoarthritic Knees: A Single-Center Pilot Study

2024· article· en· W4404254046 on OpenAlexaboutno aff
Chun-Ru Lin, Chia–Nan Lin, Chung-Chen Lee, Yong‐Chen Chen, Yu-Jen Chen, Ming-Hao Chen, Yu‐Chih Lin, Shu-Hao Chang

Bibliographic record

VenueLife · 2024
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisCartilageArticular cartilageArthritisStromal vascular fractionKnee JointSurgeryInternal medicineStromal cellPathologyAnatomy

Abstract

fetched live from OpenAlex

Osteoarthritis (OA) is a prevalent form of arthritis worldwide. Intra-articular stromal vascular fraction (SVF) injections are a potential therapeutic option for patients with OA. This study aims to assess the effects of intra-articular SVF injections on knee OA. Ten patients with knee OA participated in this study. After administering them with intra-articular SVF injections, their outcomes were evaluated using various questionnaires. MRI T2 mapping was conducted and compared before the intervention and 6 months after. All the data underwent analysis using various tests. Significant differences were observed in the change of Western Ontario and McMaster Universities Arthritis Index, VAS, and Knee Injury and Osteoarthritis Outcome Score between pre-intervention and 6 months post-intervention. The T2 values were significantly lower in the anterior superficial layer of the medial femoral cartilage and middle superficial layer of the lateral femoral cartilage. However, no positive effects were observed in any other regions of the knee cartilage. This study revealed significant differences between the pre- and 6-month post-intervention questionnaires. However, the T2 values did not show consistent changes across all regions of the knee cartilage. Despite positive effects in two regions, the degenerative process appeared to continue in other regions during the tracking period.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.306
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized 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

Citations5
Published2024
Admission routes1
Has abstractyes

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