Should we look beyond <i>Kt</i>/<i>V</i> urea in assessing dialysis adequacy?
Bibliographic record
Abstract
Since the advent of maintenance dialysis therapy, our interpretation of what adequate dialysis really is has broadened and become more controversial. This is not only due to our changing and aging dialysis population but also to our evolving knowledge base. As nephrologists, we strive to achieve both quality and (often) quantity of life for our patients and we feel reassured when we have a quantifiable marker to show for our efforts. However, we suggest that adequate dialysis reaches far beyond the realms of attaining a particular biochemical result. Dialysis adequacy should encompass a more comprehensive assessment of patient well-being. This metric could comprise quality of life and patient-specified goals, sufficient small solute and middle molecule clearance, optimal blood pressure control, and effective bone-mineral balance, all in the context of minimizing mortality and morbidity, and a livable dialysis regimen for the patient.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".