Can Extracellular Fluid Volume Expansion in Hemodialysis Patients Be Safely Reduced Using the Hemocontrol Biofeedback Algorithm? A Randomized Trial
Bibliographic record
Abstract
Extracellular fluid volume (ECFV) expansion in hemodialysis patients is associated with increased mortality. Attempts to remove excess fluid often result in intradialytic hypotension (IDH). Blood volume monitoring has been used to aid selection of ultrafiltration rates and dialysate conductivity to minimize IDH. Automating ultrafiltration and dialysate conductivity using the Hemocontrol Biofeedback System (HBS) has reduced IDH in IDH-prone subjects. We undertook a randomized controlled trial to determine if the HBS could safely reduce ECFV in ECF-expanded subjects. Patients with ECFV >45% of total body water were randomized to receive hemodialysis by either HBS or best clinical practices for 6 months. The primary endpoint was change in ECFV; exploratory variables included frequency of IDH, interdialytic weight gain, and changes in serum Na. Treatment with HBS did not result in any change in ECFV, even after multivariable adjustment. The frequency of IDH was however significantly lower with HBS when compared with best clinical practices without differences in other variables.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".