What Influences Cardiovascular Instability and Discomfort during Daily Hemodialysis?
Bibliographic record
Abstract
Background: Daily hemodialysis (DHD) markedly ameliorates cardiovascular instability (CVI) and discomfort (DIS) during dialysis, but patients continue to have some of these problems during DHD. We studied what contributed to these problems during 4445 DHD in 23 patients. Methods: Dependent variables were increase in pulse rate (PR), maximal (MAX) and overall (OV) fall of systolic blood pressure (BP), and a subjective score of patients' overall evaluation of the quality of dialysis (OEQ), adding a score of 14 symptoms (0 best, 40 worst). Independent variables were ultrapure dialysate and biocompatible dialysis (UP) (1626 dialyses) vs. conventional dialysis (CONV) (2819 dialyses), ultrafiltration (Uf) as percentage of body weight (BW), pre–post BUN (ΔBUN), time on dialysis (T), speed of dialysis (K/V in mL min−1 kg BW−1), and target −post‐dialysis BW (Ta‐Po BW). Relations were analyzed by backward multiple regression analysis. Results: PR increased by 1.6 ± 13/min; MAX BP fall was 25 ± 20 mmHg; OV BP fall was 13 ± 22 mmHg; OEQ = 0.6 ± 1.2. In multiple stepwise backward regression analysis, independents in order of importance: PR = ΔBUN × 0.12 + Ta‐Po BW × 1.8 + K/V × 1.1 − 5 r = 0.13, p < 0.0001 MAX BP = CONV × 8 + T × 0.2 − Ta‐Po BW × 6 + Uf × 2.7 −13 r = 0.33, p < 0.0001 OV BP = CONV × 11 + Uf × 4 − Ta‐Po BW × 4 + ΔBUN × 0.3 − 9 r = 0.35, p < 0.0001 OEQ = K/V × 0.3 − Ta‐Po BW × 0.1 − 0.2 r = 0.20, p < 0.0001 Conclusion: To minimize drop in BP and hypotensive crashes, use of ultrapure dialysate and a biocompatible membrane (UP) was by far the most important factor, followed by slowing dialysis. To avoid post‐dialysis tachycardia and discomfort during dialysis, slow dialysis was most important. Overall, “fast” dialysis and use of “impure” regular dialysate appear to be the major dialysis factors causing CV instability and discomfort during daily hemodialysis.
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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 | 0.005 |
| 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 | 0.001 | 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".