<scp>P</scp>‐selectin, <scp>E</scp>‐selectin, and <scp>CD40L</scp> over time in chronic hemodialysis patients
Bibliographic record
Abstract
The aim of this study was to measure P-selectin, E-selectin, and CD-4L levels over time in chronic hemodialysis (HD) patients. Thirty stable patients with end-stage renal failure undergoing chronic HD were included in the study. Blood samples were obtained before HD for measurement of P-selectin, E-selectin, and CD-40L. Measurements were performed at month 0 (T0), 3 (T2), 8 (T3), and 13 (T4). The levels of P-selectin, E-selectin, and CD40L were also analyzed according to the occurrence of cardiovascular disease (CVD) and to CVD-related mortality. The levels of CD40L and P-selectin changed significantly over time, decreasing at month 3 and 6 and returning at the T0 levels at month 13. Conversely, E-selectin levels did not. The levels of CD40L, P-selectin and E-selectin over time did not differ significantly between patients with age ≤ 65 or > 65 years, between patients with or without CVD, or between patients who died or who survived during the follow-up. In end-stage renal failure patients undergoing chronic HD, CD40L and P-selectin, but not E-selectin, showed a transient decrease over time, and the serum levels of these molecules were not associated with CVD or with CVD-related mortality.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".