Assessing C reactive protein/albumin ratio as a new biomarker for polycystic ovary syndrome: a case–control study of women from Bahraini medical clinics
Bibliographic record
Abstract
OBJECTIVE: Polycystic ovary syndrome (PCOS) is an endocrine disorder affecting approximately one in seven women who experience androgen excess, menstrual cycle irregularities, frequent anovulation and a tendency for central obesity and insulin resistance. Chronic subclinical inflammation is now recognised as being common in the context of PCOS, which led to the postulation that PCOS may fundamentally be an inflammatory process. This study aimed to: (1) evaluate serum C reactive protein (CRP)/albumin ratio as a potential predictive biomarker for PCOS; (2) compare the relationship between CRP/albumin and PCOS to variables classically associated with the syndrome. DESIGN: Case-control study. SETTING: Adult obstetrics/gynaecology, endocrinology and outpatient clinics; university hospital in Bahrain. PARTICIPANTS: 200 premenopausal women with a diagnosis of PCOS, and 119 ethnically matched eumenorrheic premenopausal women. MAIN OUTCOME MEASURES: CRP/albumin ratio, anthropometric measures, insulin resistance, androgen excess. RESULTS: Independent of body mass index (BMI), receiver operating characteristic curve for CRP/albumin ratio as a selective biomarker for PCOS was 0.865 (95% CI 0.824 to 0.905), which was more sensitive than CRP alone. Binary regression analysis showed that CRP/albumin ratio outperformed classical correlates, Free Androgen Index and insulin resistance, in predicting PCOS for every BMI category. CONCLUSION: CRP/albumin ratio, a marker for inflammation related to metabolic dysfunction, was found to have a stronger association with PCOS than either androgen excess or insulin resistance. Inflammation is known to be influenced by adiposity, but relative to controls, women with PCOS have higher levels of CRP/albumin irrespective of BMI. These findings support the view that inflammation plays a central role in the pathophysiology of PCOS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".