Assessment of intradialysis calcium mass balance by a single pool variable‐volume calcium kinetic model
Bibliographic record
Abstract
INTRODUCTION: A reliable method of intradialysis calcium mass balance quantification is far from been established. We herein investigated the use of a single-pool variable-volume Calcium kinetic model to assess calcium mass balance in chronic and stable dialysis patients. METHODS: Thirty-four patients on thrice-weekly HD were studied during 240 dialysis sessions. All patients were dialyzed with a nominal total calcium concentration of 1.50 mmol/L. The main assumption of the model is that the calcium distribution volume is equal to the extracellular volume during dialysis. This hypothesis is assumed valid if measured and predicted end dialysis plasma water ionized calcium concentrations are equal. A difference between predicted and measured end-dialysis ionized plasma water calcium concentration is a deviation on our main hypothesis, meaning that a substantial amount of calcium is exchanged between the extracellular volume and a nonmodeled compartment. FINDINGS: The difference between predicted and measured values was 0.02 mmol/L (range -0.08:0.16 mmol/L). With a mean ionized dialysate calcium concentration of 1.25 mmol/L, calcium mass balance was on average negative (mean ± SD -0.84 ± 1.33 mmol, range -5.42:2.75). Predialysis ionized plasma water concentration and total ultrafiltrate were the most important predictors of calcium mass balance. A significant mobilization of calcium from the extracellular pool to a nonmodeled pool was calculated in a group of patients. DISCUSSION: The proposed single pool variable-volume Calcium kinetic model is adequate for prediction and quantification of intradialysis calcium mass balance, it can evaluate the eventual calcium transfer outside the extracellular pool in clinical practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".