Assessing the renal response in patients with potassium disorders: a shift in emphasis from the TTKG to the urine K+/creatinine ratio
Bibliographic record
Abstract
This article briefly reviews the reasons for replacing the transtubular K+ gradient (TTKG) with the urine K+/creatinine ratio, as a tool for evaluating the response of the kidney in patients with potassium disorders. An appreciation of the magnitude and importance of the intrarenal recycling of urea led to the realization that a large amount of urea is reabsorbed daily in the terminal collecting duct and that this renders invalid the assumption, used by the TTKG, that there is minimal solute reabsorption downstream of the cortical collecting duct (CCD). The urine-to-plasma osmolality ratio can therefore not be used to calculate the volume of fluid exiting the CCD nor the concentration of K+ in the luminal fluid in this nephron segment. We now recommend the use of the K+/creatinine ratio in random urine samples to estimate the rate of K+ excretion. A ratio of less than 1.5 mmol K+/mmol creatinine would be expected if the kidney is responding appropriately to hypokalaemia from a non-renal cause, and a ratio greater than 20 mmol K+/mmol creatinine would be appropriate as the renal response to hyperkalaemia.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".