Role of adiponectin and its receptor in prediction of reproductive outcome of metformin treatment in patients with polycystic ovarian syndrome
Bibliographic record
Abstract
AIMS: The aim of this study was to examine the effect of metformin on serum adiponectin and adiponectin receptor-1 (AdipoR1) and evaluate their role in prediction of ovulation in patients with polycystic ovarian syndrome (PCOS). MATERIAL AND METHODS: The study cohort included 68 PCOS patients with clomiphene citrate resistance (group 1) and 28 healthy women as controls (group 2). Baseline serum adiponectin, AdipoR1, total testosterone (T), and homeostasis model of insulin resistance (HOMA-IR) were measured in all participants. Group 1 received metformin (1500 mg/day) for 6 months followed by second blood sampling. RESULTS: Group 1 had significantly lower baseline adiponectin and AdipoR1 (P = 0.001) compared to group 2. During treatment, metformin resulted in conception in 5/68 (7%), ovulation in 33/68 (48%) and regular cycles in 41/68 (60%) patients. Group 1 showed post-metformin higher adiponectin and AdipoR1 (P = 0.01) and lower HOMA-IR (P = 0.006) and T (P = 0.001) compared to pre-treatment levels. Post-metformin ovulatory patients had higher adiponectin and AdipoR1 and lower HOMA-IR and T compared to anovulatory patients. Multivariate regression analysis in group 1 showed that only T and HOMA-IR were significant independent factors for predicting ovulatory cycles during metformin treatment (P = 0.04 and P = 0.05, respectively). CONCLUSIONS: Metformin treatment enhances both adiponectin activity and insulin sensitivity, resulting in a less hyperandrogenic state in patients with PCOS. Serum adiponectin and AdipoR1 are poor predictors of ovulatory outcome during treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".