Endotoxins and inflammation in hemodialysis patients
Bibliographic record
Abstract
Long-term endotoxin challenge may promote frequent complications in dialysis patients, namely malnutrition, chronic inflammation, and atherosclerosis, which are recognized as the so-called MIA syndrome. Circulating soluble vascular cell adhesion molecule-1 (sVCAM-1) levels may be used to determine the stage of atherosclerosis. This study aimed to assess endotoxin level in hemodialysis (HD) patients and its role in inducing inflammation. The study was conducted on 50 HD patients, chosen from four dialysis centers in Alexandria. Serum blood samples were collected for the determination of albumin and C-reactive protein (CRP), and whole blood samples were used for the measurement of hemoglobin level. A heparinized whole blood sample was taken postdialysis for endotoxin assay by limulus amebocyte lysate test, and in addition to sVCAM-1 was estimated using enzyme-linked immunosorbent assay. The mean endotoxin level was 76.30 pg/mL;80% exhibited values higher than 60 pg/mL. Half the studied patients had CRP values that exceeded the upper limit of the laboratory reference range (<6.0 mg/L). A statistically significant correlation was found between endotoxin and CRP levels (r = 0.47, P = 0.001). The mean pre-HD level of VCAM was 1851.00 ng/mL, while the mean post-HD level was 2829.00 ng/mL with statistically significant correlation (r = 0.354, P = 0.012) and it also correlated significantly with endotoxin as well as CRP levels. Endotoxemia may play an important role in the aggravation of endothelial dysfunction in HD patients as indicated by the post-HD rise in sVCAM-1.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".