Immersion‐enhanced fluid redistribution can prevent intradialytic hypotension: A prospective, randomized, crossover clinical trial
Bibliographic record
Abstract
INTRODUCTION: Intradialytic hypotension (IDH) is an important cause of morbidity and mortality among hemodialysis patients. We used an immersion model to evaluate the role of reduced effective circulating volume, and to examine whether facilitated refilling can prevent IDH. METHODS: Ten male hemodialysis patients who had frequent episodes of IDH were randomized to a mid-week "wet" or "dry" hemodialysis session, and subsequently underwent the other session in a crossover manner. The wet sessions were performed while immersed up to the neck in a 34 to 35°C bath, and the dry session was standard hemodialysis. Ultrafiltration goals were determined as the mean ultrafiltration during the 10 sessions preceding the first study session ± 10%. FINDINGS: Mean ultrafiltration was similar for the wet and dry sessions (2.99 ± 0.64 kg vs. 2.96 ± 0.74 kg). Symptomatic hypotension did not develop in any of the patients during the wet session, compared to 4 (40%) during the dry session. Systolic blood pressure adjusted to ultrafiltration was stable during the wet session, 0.22 mmHg/15 min (95% CI -0.27 to 0.70), P = 0.38, and significantly decreased during the dry session, -0.68 mmHg/15 min (95%CI -1.24 to -0.11), P = 0.02. Diastolic blood pressure did not change during the sessions. Mean atrial natriuretic peptide significantly increased in the wet session, by 31.36 pgr/mL (95%CI 8.73-53.99), P = 0.007, and slightly and insignificantly decreased in the dry session, by 21.66 pgr/mL (95% CI -52.59 to 9.25), P = 0.167. Aldosterone blood levels did not change. DISCUSSION: Reduced effective circulating volume is a major cause for IDH, which can be prevented using head-out water immersion facilitated redistribution.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".