Leptin and Epicardial Fat: New Markers of Psoriasis in Children? Prospective Cross-Sectional Study
Bibliographic record
Abstract
Background. Psoriasis is a polygenic multifactorial immune-mediated disease. Its course can be aggravated by associated obesity. Recently, there is negative trend that is characterized by the increase in the number of moderate to severe psoriasis cases among children, and majority of them have obesity. Identification of factors that that are relevant in these two conditions will allow us to improve and optimize the genetically engineered biological therapy for this category of patients. Objective. The aim of the study is to evaluate epicardial adipose tissue thickness, serum leptin levels, eating behavior via the data from Children’s Eating Behaviour Questionnaire (CEBQ) for patients with psoriasis and obesity, and compare the results with control group – patients with psoriasis and no associated obesity. Results. We have studied 12 patients with established diagnosis of psoriasis, 5 of them had diagnosis of obesity. Epicardial fat thickening was revealed in 20% of cases in the study group (patients with psoriasis and obesity), and no epicardial fat thickening was revealed in the control group. The increase in serum leptin was revealed in 100% of cases in obese patients with psoriasis, and only in 14% of cases in the control group. The mean leptin level in obese patients was 16.65 ng/ml, in the group with normal body weight – 7.08 ng/ml. Obese patients have shown higher values in “food approach” scales group in comparison to normal weight patients. Conclusion. Patients with obesity and psoriasis has shown elevated leptin levels, higher incidence of epicardial fat thickening, and tendency to develop abnormal eating behavior.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".