Association between irisin and metabolic parameters in nondiabetic, nonobese adults: a meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Irisin has been proposed to have a beneficial influence on the metabolic status of animals and humans. However, the relationship between circulating irisin levels and the risks of metabolic components in humans remains unclear. In the present meta-analysis, we aimed to evaluate the association between circulating irisin and metabolic parameters in nonobese, nondiabetic adults. METHODS: We searched PubMed, Embase, the Cochrane Library, Web of Science and ClinicalTrial.gov using the main search terms and identified original articles published prior to March 7, 2022. Studies that met our inclusion criteria and reported the association between irisin and metabolic parameters were included in our meta-analysis. We used the Newcastle Ottawa scale to assess the quality of the included studies. RESULTS: A total of 14 studies (711 subjects) in 11 articles were included for qualitative and quantitative synthesis. The pooled results showed that circulating irisin was positively and significantly correlated with fasting blood glucose (r = 0.159), HOMA-IR (r = 0.217) and waist-to-hip ratio (WHR) (r = 0.168). However, no significant association was detected between irisin levels and other metabolic parameters. CONCLUSIONS: Thus, these findings indicated the possible link between irisin levels and part of the metabolic parameters in apparently metabolically normal individuals. However, the regulation of irisin in metabolism in humans remains to be fully elucidated, and well-designed prospective studies will be needed in the future. Trial registration The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO): CRD42022315269.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it