Stopping versus continuing renin–angiotensin–system inhibitors after acute kidney injury and adverse clinical outcomes: an observational study from routine care data
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
Background: The risk-benefit ratio of continuing with renin-angiotensin system inhibitors (RASi) after an episode of acute kidney injury (AKI) is unclear. While stopping RASi may prevent recurrent AKI or hyperkalaemia, it may deprive patients of the cardiovascular benefits of using RASi. Methods: We analysed outcomes of long-term RASi users experiencing AKI (stage 2 or 3, or clinically coded) during hospitalization in Stockholm and Sweden during 2007-18. We compared stopping RASi within 3 months after discharge with continuing RASi. The primary study outcome was the composite of all-cause mortality, myocardial infarction (MI) and stroke. Recurrent AKI was our secondary outcome and we considered hyperkalaemia as a positive control outcome. Propensity score overlap weighted Cox models were used to estimate hazard ratios (HRs), balancing 75 confounders. Weighted absolute risk differences (ARDs) were also determined. Results: . After weighting, those who stopped had an increased risk [HR, 95% confidence interval (CI)] of the composite of death, MI and stroke [1.13, 1.07-1.19; ARD 3.7, 95% CI 2.6-4.8] compared with those who continued, a similar risk of recurrent AKI (0.94, 0.84-1.05) and a decreased risk of hyperkalaemia (0.79, 0.71-0.88). Discussion: Stopping RASi use among survivors of moderate-to-severe AKI was associated with a similar risk of recurrent AKI, but higher risk of the composite of death, MI and stroke.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.005 |
| 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 it