Potassium Balance in Dialysis Patients
Bibliographic record
Abstract
The advent of dialytic therapy has enabled nephrologists to provide life-saving therapy, but potassium balance continues to be an ever present challenge in the ESRD population. Although a small percent of patients are chronically hypokalemic, hyperkalemia is by far the most common abnormality in dialysis patients. It is associated with increased all-cause mortality, cardiovascular mortality, and arrhythmogenic death. Although alterations of the dialysis bath may decrease predialysis potassium, potassium baths <2 mEq/l are associated with a higher risk of sudden cardiac death. Studies show that patients are aware of the risks of hyperkalemia, but adherence to a low potassium diet is suboptimal. ACEI, ARBs, and spironolactone may cause slight increases in potassium even in anuric patients, requiring increased surveillance. Fludrocortisone and potassium binders have not been proven to be beneficial in lowering interdialytic potassium levels. Frequent hemodialysis may be a viable option, and studies of prophylactic placement of implantable cardioverter/defibrillators are underway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".