Association of metabolic syndrome in patients with vitiligo
Bibliographic record
Abstract
Background: Vitiligo can trigger inflammatory processes due to decreased number of melanocytes and their anti-inflammatory effects as well as oxidative stress. Metabolic syndrome includes hypertension, abdominal obesity, dyslipidemia, glucose intolerance, leading to cardiovascular disease, diabetes mellitus and stroke. Because of the systemic nature of vitiligo, metabolic syndrome or its component may be observed in vitiligo. To observe association of metabolic syndrome in patients with vitiligo. Methods: This case control study included 54 vitiligo patients and 54 age and sex matched controls according to inclusion and exclusion criteria. Detailed history, physical examination and laboratory investigations were done in all participants and revised National Cholesterol Education Program Adult Treatment Panel III criteria were used for diagnosis of metabolic syndrome. Data were analyzed by using SPSS (Statistical Package for Social Sciences) Version 23. Results: Metabolic syndrome was present in 20 (37.0%) patients with vitiligo and in 9 (16.7%) control subjects. Frequency of metabolic syndrome was significantly higher in vitiligo patient compared to control (p=0.017). Systolic blood pressure, diastolic blood pressure, fasting plasma glucose and mean serum triglycerides level were significantly higher in the patient group than that of control group, whereas serum high density lipoprotein cholesterol was significantly lower in the patient group than that of control group. There were no significant difference between cases and controls regarding waist circumference. Conclusions: Presence of metabolic syndrome was higher in patients with vitiligo. Further large-scale studies are needed to establish it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.003 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".