Body Mass Index and Gonadotropin Hormones (LH & FSH) Associate With Clinical Symptoms Among Women With Polycystic Ovary Syndrome
Bibliographic record
Abstract
UNLABELLED: To evaluate the relevance of body mass index (BMI), luteinizing hormone (LH), follicle-stimulating hormone (FSH) and LH/FSH ratio with clinical symptoms in polycystic ovary syndrome (PCOS) women. METHODS: We reviewed the medical records of all women visited in the PCOS Clinic of Babol (Iran) from 2008 to 2012. A retrospective cross-sectional study was conducted on 175 PCOS women; aged 18-38 years diagnosed based on the Rotterdam criteria. Among the PCOs women, the prevalence of oligomenorrhea, acne, and hirsutism were found to be 92.0%, 31.4%, and 78.9%, respectively. Positive finding of polycystic ovaries was observed in 89.1% of PCOS women with by using sonography. A total of 69.2% overweight/obesity patients had polycystic ovary morphology on ultrasound image. Compared with non- overweight/obesity, the adjusted OR of PCOS women for sonographic view of polycystic ovaries was 4.33 (95% CI, 1.42-13.15, p=0.001), Nevertheless, the adjusted odds ratio (OR) showed no significant associations between LH, FSH, and LH/FSH ratio with clinical symptoms in these women. The findings of this study indicated that the overweight/obese women with PCOS are at an increased risk for sonographic view of polycystic ovaries. Therefore, it is suggested that successful weight loss is the most effective method of restoring ovulation, menstruation that should be used as major advice in obese PCOS patients.
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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 | 0.001 | 0.001 |
| 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".