Effect of acetate‐free biofiltration with a potassium‐profiled dialysate on the control of cardiac arrhythmias in patients at risk: A pilot study
Bibliographic record
Abstract
Cardiac arrhythmias are a frequent event in chronic hemodialysis patients. The aim of this study was to evaluate the efficacy and safety of acetate-free hemofiltration with potassium-profiled dialysate (AFB-K) dialysis compared with constant potassium acetate-free biofiltration (AFB). Twelve patients (mean age 79 years) affected by cardiac arrhythmias or at a high risk for arrhythmia (advanced age, hypertension, left ventricular hypertrophy, heart valve disease, coronary artery disease, diabetes, paroxysmal atrial fibrillation) participated in a single-center, sequential cohort study. All were treated with hemodialysis 3 times per week, using constant potassium AFB for the first 3 weeks, followed by an AFB-K dialysate for the subsequent 3 weeks. The hemofilter, duration of dialysis, and electrolyte concentration were the same in both treatments. Both AFB-K and constant potassium AFB dialytic techniques were safe and well tolerated. The results of biochemical tests were similar, except for serum potassium levels after 2 hr of dialysis, which were significantly higher in the AFB-K group (4.0 mmol/L) than in the constant potassium AFB group (3.6 mmol/L) (p<0.001). All cardiac variables improved during AFB-K dialysis. There was a significant reduction of postdialysis QT intervals corrected for heart rate in the AFB-K group (448.8 ms) compared with the constant potassium AFB group (456.8 ms) (p=0.039). The severity and mean number of ventricular extasystoles also decreased (163.5 vs. 444.5/24 hr). Potassium profiling during hemodialysis treatment may be beneficial for patients with arrhythmias or at those risk of arrhythmias, particularly those with predialysis hyperkalemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".