Autologous micro-fragmented adipose tissue in the treatment of atherosclerosis patients with knee osteoarthritis in geriatric population: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Atherosclerosis and osteoarthritis are closely related. However, no high-quality studies have investigated the potential of micro-fragmented adipose tissue to treat patients with atherosclerosis accompanied by osteoarthritis. METHODS: PubMed, Embase, the Cochrane Library, Web of Science, China National Knowledge Infrastructure, WANFANG DATA, and CQVIP were searched for potentially eligible studies published before October 13, 2022. Due to the statistical limitations of the existing relevant literature, it is not possible to make direct statistics on the patients with osteoarthritis accompanied by atherosclerosis treated by micro-fragmented adipose tissue. The primary outcome consisted of two parts: 1) Correlation between atherosclerosis and osteoarthritis; 2) Scores of the Knee injury and Osteoarthritis Outcome Score (KOOS). And secondary outcomes were pain assessed by visual analog scale (VAS) or numeric rating scale (NRS), quality of life (QoL) (assessed using tools apart from the KOOS), and adverse events (AEs). Random meta-analysis was conducted using STATA 14.0. RESULTS: Nineteen studies were included. The metaanalysis evidenced a positive association between atherosclerosis and osteoarthritis (OR 1.17, CI 1.01-1.36). The mean absolute difference in KOOS subscale scores between pre- and post-treatment (mean with 95% confidence interval [CI]) was 19.65 (13.66, 25.63), 14.20 (4.64, 23.76), 19.95 (13.02, 26.89), 25.23 (14.80, 35.66), and 26.01 (13.68, 38.35) for pain, symptoms, activities of daily living (ADL), sports/recreation, and quality-of-life (QOL), respectively. The mean differences in VAS, resting VAS, activity VAS, and NRS between pre- and post-treatment was -8.24 (-10.66, -5.82), -3.61 (-4.49, -2.72), -4.17 (-4.89, -3.44), and -2.17 (-4.06, and -0.28), respectively. The mean difference in score of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), EQ-5D, and University of California in Los Angeles (UCLA) between pre- and post-treatment was -24.81 (-40.80, -8.82), 0.07 (0.02, 0.12), and 0.30 (-0.42, 1.02), respectively. The mean difference in Tegner score and the International Knee Documentation Committee (IKDC) score between pre- and post-treatment was 0.67 (-0.62, 1.97) and 13.70 (6.35, 21.04), respectively. The use of micro-fragmented adipose tissue was associated with risk of bruising, bleeding, hematoma, drainage, infection, soreness, swelling, pain, and stiffness in harvest and injection sites. CONCLUSION: Atherosclerosis and osteoarthritis share common risk factors and comorbidity. And the use of micro-fragmented adipose tissue may benefit for improving symptoms of knee osteoarthritis accompanied by atherosclerosis although may lead to some mild adverse events. Randomized controlled trials with long-term follow-up are necessary for further evaluation because many limitations of this meta-analysis cannot be ignored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".