SP648ASSOCIATION BETWEEN SERUM LEPTIN LEVEL AND MORTALITY IN KIDNEY TRANSPLANT RECIPIENTS
Bibliographic record
Abstract
Introduction and Aims: Leptin is a hormone made by adipocytes and associated with hypertension, inflammation, and coronary artery disease, especially in males. However, low serum leptin level was associated with higher risk of death in patients with chronic kidney disease Stage 5. Nevertheless, little is known about the association of serum leptin with outcomes in kidney transplant recipients. Methods: We collected socio-demographic and clinical parameters, medical and transplant history, and laboratory data from 979 prevalent kidney transplant recipients enrolled in the Malnutrition-Inflammation in Transplant - Hungary Study (MINIT-HU study). Serum leptin levels were measured at baseline. Associations between serum leptin level and death with a functioning graft over a 6-year follow-up period were examined in unadjusted and adjusted survival models. Results: The mean±SD age of the study population was 51±13 years, among whom 58% were men and 21% were diabetics. Serum leptin levels showed moderate negative correlation with eGFR (R=-0.21,p<0.001) and had positive correlations with BMI (R=0.48,p<0.001) and C-reactive protein (R=0.20,p<0.001). Each 10 ng/ml higher serum leptin level was associated with 7% lower risk of death with functioning graft (HR (95%CI): 0.93 (0.87-0.99)), and this strong association remained qualitatively the same even after adjustment for confounders in our fully adjusted model: HR (95%CI): 0.90 (0.84-0.98).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".