Inflammatory Markers and Outcomes in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Increased levels of TNF-α and IL6 are associated with inflammation and cardiovascular disease among patients with normal kidney function. However, little is known about their association with outcomes in kidney transplant recipients. METHODS: We collected sociodemographic, clinical and laboratory parameters, medical and transplant history from 977 prevalent kidney transplant recipients enrolled in the Malnutrition-Inflammation in Transplant-Hungary study. Serum cytokine levels were measured at baseline. Associations between serum TNF-α and IL6 values and death with a functioning graft over a 6-year follow-up period were examined in unadjusted and adjusted models. RESULTS: The mean ± SD age of the study population was 51 ± 13 years, 57% were men, 21% were diabetics. Median serum TNF-α and IL6 concentrations were significantly higher in patients who died with a functioning graft as compared with those who did not die during the follow-up period (TNF-α: median, 1.92 pg/mL; interquartile range [IQR], 1.43-2.67 pg/mL vs median, 2.25 pg/mL; IQR, 1.63-3.08 pg/mL, P < 0.001; and for IL6: median, 1.91 pg/mL; IQR, 1.21-3.02 pg/mL vs median, 2.81 pg/mL; IQR, 1.65-4.97 pg/mL, P < 0.001). Higher serum TNF-α and IL6 levels were associated with higher mortality risk in both unadjusted and fully adjusted models: TNF-α: hazard ratios (HRs)(1 pg/ml increments), 1.24; 95% confidence interval (CI), 1.13-1.36 and HRs(1 pg/ml increments), 1.19; 95% CI, 1.08-1.32; IL6: HRs(1 pg/ml increments), 1.06; 95% CI, 1.03-1.09 and HRs(1 pg/ml increments), 1.03; 95% CI, 0.99-1.06, respectively. Compared with patients whose serum TNF-α or IL6 levels were in the lowest tertile, those in the middle tertile had similar mortality risk (TNF-α: HR, 1.09; 95% CI, 0.74-1.61; IL6: HR, 1.05; 95% CI, 0.68-1.62), but patients in the highest tertile reported higher risk of mortality: TNF-α: HR, 1.45; 95% CI, 1.01-2.09; IL6: HR, 1.55; 95% CI, 1.04-2.32 in multivariable adjusted models. CONCLUSIONS: In prevalent kidney transplant recipients, serum TNF-α and IL6 were independently associated with death with a functioning graft.
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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 | 0.001 | 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) | 0.001 | 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".