Asprosin levels in women with and without the polycystic ovary syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective: This systematic review and meta-analysis aimed at summarizing the evidence concerning circulating asprosin, and related endocrine and metabolites in women with and without the polycystic ovary syndrome (PCOS).Method: We performed a comprehensive literature search in Pubmed, Web of Science, Scielo, and Chinese National Knowledge Infrastructure for studies published until May 20, 2022, that evaluated circulating asprosin levels in women with and without PCOS, regardless of language. The quality of studies was assessed with the Newcastle-Ottawa Scale. Random-effects models were used to estimate mean differences (MD) or standardized MD (SMD) and their 95% confidence interval (CI).Results: We evaluated eight studies reporting 1,050 PCOS cases and 796 controls of reproductive age. Participants with PCOS were younger (MD = −2.40 years, 95% CI −2.46 to −2.33), with higher values of asprosin (SMD = 2.57, 95% CI 1.64–3.50), insulin (SMD = 2.73, 95% CI 1.18–4.28), homeostatic model assessment of insulin resistance (SMD = 2.70, 95% CI 0.85–4.55), luteinizing hormone (SMD = 2.33, 95% CI 0.60–4.06), total testosterone (SMD = 4.06, 95% CI 1.89–6.22), dehydroepiandrosterone sulfate (SMD = 2.38, 95% CI 0.37–4.40), and triglycerides (SMD = 1.20, 95% CI 0.13 to 2.27). Moreover, PCOS women had lower circulating levels of sex hormone-binding globulin (SMD = −3.36, 95% CI −4.92 to −1.80), and high-density lipoprotein-cholesterol (SMD = −0.85, 95% CI −1.69 to −0.01); with no significant differences observed for glucose, total cholesterol, and low-density lipoprotein-cholesterol levels.Conclusion: Circulating asprosin levels were significantly higher in women with PCOS as compared to those without the syndrome.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| 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".