Effects of hemodialysis with cooled dialysate on high‐sensitivity cardiac troponin I and brain natriuretic peptide
Bibliographic record
Abstract
BACKGROUND: Hemodialysis (HD) triggers recurrent and cumulative ischemic insults to the brain and the heart. Cooled dialysate may have a protective effect on major organs and improve hemodynamic tolerability of dialysis. The aim of the study was to compare HD with cooled dialysate with routine dialysis in terms of hemodynamic stability and levels of high-sensitivity Troponin I (hs-TnI) and N-terminal pro b-type natriuretic peptide (NTproBNP) pre and postdialysis. METHODS: The 45 patients were randomized into two groups. The first group received a 35.5°C dialysate first (hypothermic dialysis) and the second group a 36.5°C dialysate first (routine dialysis). Then groups crossed over, so each group received the alternate dialysate (self-controls) For each patient, the first sample was collected at the beginning of dialysis, and a second sample was taken at the end of dialysis. RESULTS AND CONCLUSION: hs-TnI and NTproBNP increased after routine HD by 10.7 ng\ml (p < 0.001) and (12.0 pg/μl) (p < 0.001), respectively, and by -3.1 ng\ml (p = 0.25) and (4.3 pg/μl) (p < 0.001), respectively after hypothermic HD. Our study results showed a tendency towards less rise in hsTnI and NTproBNP during hypothermic HD (35.5°C) as compared to routine HD (36.5°C). Neither arm experienced statistically significant changes in blood pressure. Further studies in larger cohorts and long follow up are warranted in order to confirm that lower rise in (hs-TnI) and NTproBNP actually translate into lower clinical risk for cardiovascular events.
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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".