Association of Coronary Heart Disease Risk and Lipid Profile in Indian Women With Polycystic Ovarian Syndrome
Bibliographic record
Abstract
Background: Polycystic ovarian syndrome (PCOS) has been one of the major public health problems in India. Women with PCOS are often assumed, a priori , to be at increased risk for cardiovascular disease, given the high prevalence of the metabolic syndrome X among them. Lipoprotein (a) (Lp(a)) is an risk factor for development of atherosclerosis and along with dyslipidemia may add to cardiovascular risk. The aim of the study was to know the lipid profile variation in Indian women with PCOS. Methods: This cross-sectional study was conducted in West Bengal state, India. The subjects enrolled for the study included 180 women with PCOS who were compared with 95 healthy women of the control group; all of them were age and weight matched. Samples were taken after overnight fasting, and then serum lipid levels were analyzed. Results: The mean age of subjects was 28.71 ± 4.12 years in the PCOS group and 30.14 ± 3.29 years in the control group. The lipid profile parameters were comparable between patients and control subjects. There was a statistically significant difference in the Lp(a) levels between patients with PCOS and normal controls (P ≤ 0.0001). There were statistically significant increased levels of total cholesterol, very low-density lipoprotein and low-density lipoprotein cholesterol in PCOS group when compared with the control group (P < 0.05) and decreased level of high-density lipoprotein cholesterol. Conclusion: The changed lipid profile levels may contribute to increased cardiovascular risk in PCOS patients. J Clin Gynecol Obstet. 2016;5(1):23-26 doi: http://dx.doi.org/10.14740/jcgo375w
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".