Vascular Calcifications as a Footprint of Increased Calcium Load and Chronic Inflammation in Uremic Patients: A Need for a Neutral calcium Balance during Hemodialysis?
Bibliographic record
Abstract
Cardiovascular complications caused by an accelerated atherosclerotic disease represent the largest single cause of mortality in chronic renal failure patients. The rapidly developing atherosclerosis of the uremic syndrome appears to be caused by a synergism of different mechanisms, such as malnutrition, oxidative stress and genetic factors. Recent studies provide evidence that chronic inflammation plays an important role in the pathogenesis of cardiovascular diseases. Hyperphosphatemia and an increased calcium-phosphate ion product have also been associated with an increased risk of death. Cardiovascular calcifications secondary to increases in phosphate and calcium load in dialysis patients might exert an important contribution to the excess cardiovascular mortality and morbidity in dialysis patients. Elevated serum levels of plasma C-reactive protein (CRP) are associated with the extent and severity of the atherosclerotic processes as well as with an increased risk of experiencing myocardial infarction and sudden cardiac death in apparently healthy subjects. In patients affected by pre-dialytic renal failure increased levels of CRP and IL-6 were recorded in 25% of our population; CRP and IL-6 were inversely related with renal function. These data suggest the activation--even in the predialytic phase of renal failure--of mechanisms known to contribute to the enhanced cardiovascular morbidity and mortality of the uremic syndrome. In recent years we have investigated the hypothesis that the chronic inflammatory state of the uremic patient could be at least in part due to the dialytic technique. We have shown that the increase of CRP in stable dialysis patients may be due to the stimulation of monocyte/macrophage by backfiltration of dialysate contaminants. During conventional dialysis, a positive calcium balance and a concomitant inflammatory state may act as cofactors in the development of cardiovascular calcifications. We suggest that this hypothesis should be verified by clinical studies. A reevaluation of the ideal calcium levels in the dialysate is warranted: a neutral intradialytic calcium balance is probably more appropriate, although not easily attainable.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".