Leukocyte telomere length in women with and without polycystic ovary syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
To study the telomere length and the telomerase activity in women with and without polycystic ovary syndrome (PCOS). Relevant studies were searched from PubMed, Embase, and LILACS online databases and manual screening. The mean differences (MDs) or standardized MDs (SMDs) with their 95% confidence intervals (CIs) were calculated. The methodological quality of included studies was evaluated with the Newcastle–Ottawa Scale (NOS), and heterogeneity with the I2 and Tau2 statistics. Six studies including 2109 non-pregnant women with (n = 1155) or without (n = 954) PCOS assessed leukocyte telomere length. There was a non-significant leukocyte telomere length difference (SMD = 0.25, 95% CI: −0.01, 0.51, p = .06, I2 = 81%, Tau2 = 0.08) comparing PCOS patients with the control group. Studied PCOS women were younger (MD = −1.39, 95% CI: −2.47, −0.31 years, I2 = 83%), and had higher body mass index (BMI; MD = 3.66, 95% CI: 2.11, 5.20 kg/m2, I2 = 94%). There were significantly higher testosterone (SMD = 0.88, 95% CI: 0.65, 1.10) and luteinizing hormone levels (SMD = 0.60, 95% CI: 0.12, 1.08) in women with PCOS as compared to controls. There was a low risk of bias and there were not sufficient studies to meta-analyze other cell types. Leukocyte telomere length did not differ between women with and without PCOS. Further studies with large sample sizes and including other outcomes are warranted to further substantiate the reported evidence.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".