Role of Nitric Oxide, Endothelin‐1, Interleukin‐1, and Tumor Necrosis Factor‐α in Hemodialysis‐Induced Hypotension
Bibliographic record
Abstract
Serum level of nitrite plus nitrate (NO2 plus NO3), endothelin‐1 (Et‐1), interleukin‐1 (IL‐1), and tumor necrosis factor‐α (TNF‐α) have been estimated in 20 patients with end stage renal failure (ESRF) undergoing regular hemodialysis treatment in a trial to explain the hypotension occurring in some of these patients. According to the incidence of hypotension, patients were divided into GI (n = 10) hypotension prone patients and GII (n = 10) hypotension resistant patients (normotensive). Clinical examination with measurement of systolic and mean arterial blood pressure was performed in all cases before and after hemodialysis (HD) settings. After HD, GI showed significant increase in the serum levels of (NO2 plus NO3), IL‐1, and TNF‐α, whereas a significant decrease in serum Et‐1 level was noticed. GII showed no significant change in serum level of the 4 parameters mentioned above. In hypotensive patients, there was a significant positive correlation between (NO2 plus NO3) and the duration of dialysis, and a significant negative correlation between (NO2 plus NO3) and post dialysis systolic blood pressure, also between IL‐1 and Et‐1. From the previous results, it could be concluded that the vascular endothelial factors studied (NO and Et‐1) together with the inflammatory cytokines IL‐1 and TNF‐α contribute to the development of HD‐induced hypotension in ESRF subjects which is evidenced by: (1) the coupling of decrease of blood pressure and increase in NO2 plus NO3 level after HD in group I; (2) Et‐1, which is a powerful vasoconstrictor, showed a significant decrease postdialysis; and (3) levels of cytokines (IL‐1 and TNF‐α) (which are potent NO inducers) were found to be significantly increased postdialysis in group I.
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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) | 0.000 | 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".