Stopping mineralocorticoid receptor antagonists after hyperkalaemia: trial emulation in data from routine care
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Bibliographic record
Abstract
AIMS: Whether to continue or stop mineralocorticoid receptor antagonists (MRA) after an episode of hyperkalaemia is a challenge in clinical practice. While stopping MRA may prevent recurrent hyperkalaemias, it deprives patients of their cardioprotection. We here assessed the association between stopping vs. continuing MRA therapy after hyperkalaemia and the subsequent risks of adverse health events. METHODS AND RESULTS: Observational study from the Stockholm CREAtinine Measurements (SCREAM) project 2006-2018. We identified patients initiating MRA and surviving a first-detected episode of hyperkalaemia (plasma potassium >5.0 mmol/L). Using target trial emulation methods, we assessed the association between stopping vs. continuing MRA within 6 months after hyperkalaemia and subsequent outcomes. The primary outcome was the composite of hospital admission with heart failure, stroke, myocardial infarction, or death. The secondary outcome was occurrence of another hyperkalaemia event. Among 39 518 patients initiating MRA, we identified 7366 who developed hyperkalaemia. Median age was 76 years, 45% were women and 69% had a history of heart failure. Following hyperkalaemia, 2222 (30%) discontinued treatment. Compared with continuing MRA, stopping therapy was associated with a lower 2-year risk of recurrent hyperkalaemia [hazard ratio (HR) 0.75, 95% confidence interval (CI) 0.72-0.79], but a higher risk of the primary outcome (HR 1.10, 95% CI 1.06-1.14). Similar results were observed in patients with heart failure, after censoring when treatment decision was changed, and across pre-specified subgroups. CONCLUSIONS: Stopping MRA after an episode of hyperkalaemia was associated with reduced risk for recurrent hyperkalaemia, but higher risk of death or cardiovascular events. Recurrent hyperkalaemia was common in either strategy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it