Effectiveness of sodium and conductivity kinetic models in predicting end‐dialysis plasma water sodium concentration: Preliminary results of a single‐center experience
Bibliographic record
Abstract
The attainment of a neutral sodium balance represents a major objective in hemodialysis patients. It requires that at the end of each dialysis session, total body water volume (V(f)) and total plasma water sodium concentration (Na(pwf)) are constant. Whereas to achieve a constant V(f) it is sufficient that ultrafiltration equals the interdialytic increase in body weight, it is impossible to predict the value of Na(pwf) and calculate the dialysate sodium concentration needed to obtain it without making use of kinetic mathematical models. The effectiveness of both sodium and conductivity kinetic models in predicting Na(pwf) has already been validated in previous clinical studies. However, applying the sodium kinetic model appears to be poorly feasible in the everyday clinical practice, due to the need for blood samples at the start of each dialysis session for the determination of predialysis plasma water sodium concentration. The conductivity kinetic model appears to be more easily applicable, because no blood samples or laboratory tests are needed to determine plasma water conductivity (C(pw)) and ionic dialysance (ID), used in place of plasma water sodium concentration and sodium dialysance, respectively. We applied the 2 models in 69 chronic hemodialysis patients using the Diascan Module for the automatic determination of C(pw) and ID, and using the latter as an estimate of sodium dialysance in the sodium kinetic model. The conductivity kinetic model was shown to be more accurate and precise in predicting Na(pwf) as compared with the sodium kinetic model. Both accuracy and imprecision of the 2 models were not significantly affected by the method used to estimate total body water volume. These findings confirm the conductivity kinetic model as being an effective and easily applicable instrument for the achievement of a neutral sodium balance in chronic hemodialysis patients.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".