P1201THE AGING OF THE IMMUNE SYSTEM AND FRAGILITY: TWO FEATURES IN PERITONEAL DIALYSIS AND END-STAGE RENAL DISEASE PATIENTS
Bibliographic record
Abstract
Abstract Background and Aims Chronic kidney disease (CKD) is associated with premature immune aging and increased inflammatory activity leading into endothelial damage and macrophage senescence (CD14+CD16+). Objective. To evaluate the influence of CKD in senescent immune cells, and its relationship with fragility in patients with nondialysis CKD (ND-CKD) and Peritoneal Dialysis (PD). Method A descriptive transversal study analysing lymphocyte absolute counts and subpopulations in 74 CKD patients (36 DP, 38 ND-CKD) compared with 10 healthy subjects (HS). We also assessed immunoglobulin levels, C3 and C4 fragment complement, Edmonton fragility score and the percentage of proinflammatory blood monocytes with the CD14+CD16+ phenotype. Results PD patients presented more absolute lymphopenia compared with LCC and HS (PD 1194,2, 1589 ND-CKD and 1802 HS; p <0,001, respectively). This lymphopenia is also maintained in CD3, CD4, CD8 and NK cells. Lower CD4 lymphocytes levels were significantly correlated with higher fragility and incidence of peripheral vascular disease in uremic patients. Senescent macrophage was correlated with CD3 and CD4 lymphocytes all the cohorts (ND-CKD, PD and HS). Conclusion PD patients presented changes in immune system compared with healthy population, that could explain accelerated senescence. Accelerated senescence is associated with more fragility and endothelial damage. There are necessary more studies to identify the role premature aging in ND-CKD and to establish the differences between renal replacement modalities.
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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) | 0.002 | 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".