Modifications to bicarbonate conductivity: A way to increase phosphate removal during hemodialysis? Proof of concept
Bibliographic record
Abstract
Abstract Introduction Hyperphosphatemia and cardiovascular mortality are associated particularly with end‐stage renal disease. Available therapeutic strategies (i.e., diet restriction, calcium [or not]‐based phosphate binders, calcimimetics) are associated with extrarenal blood purification. Compartmentalization of phosphate limits its depuration during hemodialysis. Several studies suggest that plasmatic pH is involved in the mobilization of phosphate from intracellular to extracellular compartments. Consequently, the efficiency of modified bicarbonate conductivity to purify blood phosphate was tested. Methods Ten hemodialysis patients with chronic hyperphosphatemia (>2.1 mmol/L) were included in the two three–sessions‐per week periods. Bicarbonate concentration was fixed at 40 mmol/L and 30 mmol/L in the first and second periods, respectively. Phosphate depuration was evaluated by phosphate mobilization clearance (KM). Findings Although bicarbonatemia was lower during the second period (21.0 ± 2.7 vs. 24.4 ± 3.1 mmol/L, P < 0.01), no difference was observed in phosphatemia (2.4 ± 0.5 vs. 2.3 ± 0.4 mmol/L, P = NS). The in‐session variation of phosphate was lower (−1.45 ± 0.42 vs. −1.58 ± 0.44 mmol/L, P < 0.05) and KM was higher during the second period (82.94 ± 38.00 vs. 69.74 ± 24.48 mL/min, P < 0.05). Discussion The decrease of in‐session phosphate and the increase in KM reflect phosphate refilling during hemodialysis. Thus, modulation of serum bicarbonate may play a role in controlling the phosphate pool. Even though correcting metabolic acidosis during hemodialysis remains important, alkaline excess can impair phosphate mobilization clearance. Clinical trials are needed to test the efficiency and relevance of a strategy where bicarbonatemia is corrected less at the beginning of sessions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".