Determination of the critical absolute blood volume for intradialytic morbid events
Bibliographic record
Abstract
The reduction of blood volume below a critical threshold is assumed to trigger intradialytic morbid events (IME). Recently, we presented a simple method to determine the absolute blood volume during routine hemodialysis (HD) carried out without blood sampling and without injection of dyes or radiolabeled markers. Such information could be used to detect excessive volume reduction during HD and to prevent IME. Therefore, we performed a pilot study in IME-prone patients to identify the absolute blood volume at which they developed clinical symptoms. A volume of 240 mL of ultrapure dialysate was automatically infused into the extracorporeal circulation using the bolus function of a commercial online hemodiafiltration machine incorporating a blood volume monitor (BVM). The increase in relative blood volume (RBV) caused by the infusion was measured and used to determine the absolute blood volume at that time. The blood volume per kilogram body mass at the time of symptomatic IME was also determined. All IME-prone patients of a single-dialysis center were included in the study. Ten out of 12 patients became symptomatic at a specific blood volume between 65 and 56 mL/kg (mean 62 mL/kg) whereas RBV showed a wide scatter (82-97%). A specific blood volume of 65 mL/kg seems to represent the threshold for IME by this method. The technique could be completely automated without altering the hardware of the dialysis device. Present feedback systems for automated blood volume-controlled ultrafiltration could be adapted to maintain absolute blood volume above this critical volume to safely prevent volume-dependent IME.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".