Adverse effects during treatment with renin–angiotensin–aldosterone system inhibitors; should we stay or should we stop?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: To discuss recent evidence on the benefits and harms of stopping therapy with renin-angiotensin-aldosterone system inhibitors (RAASi) after the occurrence of adverse events or in patients with advanced chronic kidney disease (CKD). RECENT FINDINGS: RAASi may result hyperkalemia or acute kidney injury (AKI), particularly in persons with CKD. Guidelines recommend to temporarily stop RAASi until the problem is resolved. However permanent discontinuation of RAASi is common in clinical practice with the potential to heighten subsequent cardiovascular disease (CVD) risk. A series of studies evaluating the consequences of stopping RAASi (vs. continuing) after an episode of hyperkalemia or AKI consistently report worse clinical outcomes, both higher risk of death and cardiovascular events. The STOP-angiotensin converting enzyme inhibitors (ACEi) trial and two large observational studies also favor the decision to continue ACEi/ angiotensin receptor blockers in advanced CKD, refuting old observations that use of these medications can accelerate the risk of kidney replacement therapy. SUMMARY: Available evidence suggests continuing with RAASi after the occurrence of adverse events or in patients with advanced CKD, primarily attributed to sustained cardioprotection. This is in line with current guideline recommendations.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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