Use of Angiotensin-Converting Enzyme Inhibitors/Angiotensin Receptor Blockers and Acute Kidney Disease after an Episode of AKI: A Multicenter Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Persistence of acute kidney disease (AKD) after an episode of acute kidney injury (AKI) is associated with adverse outcomes. Multiple factors contribute to AKD after AKI, but the role of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (ACEI/ARB) remains controversial. We examined if acute exposure to an ACEI/ARB associates with persistent AKD in survivors of AKI. METHODS: Multicenter prospective cohort study of patients whose hospitalization was complicated by AKI and who attended specialized AKI follow-up clinics between 2013 and 2018. Acute exposure was defined as ACEI/ARB exposure for ≥48 h before or during the AKI episode. The primary outcome was AKD (serum creatinine ≥1.5 times above pre-AKI baseline) at the first clinic visit. We used multivariable logistic regression to adjust for potential confounders. RESULTS: We included 345 survivors of AKI, 112 with persistent AKD at the first outpatient visit. Among 163 patients who were prescribed an ACEI/ARB before hospitalization, only 23% were discharged on an ACEI/ARB. There was no difference in the rate of AKD in patients discharged versus not discharged on an ACEI/ARB (12.5 vs. 15.0%, p = 0.530). Of the patients with AKD, 22 (19.6%) patients had acute ACEI/ARB exposure during the hospitalization. In fully adjusted models, acute exposure to an ACEI/ARB was not associated with AKD at the time of first clinic visit (median [interquartile range] 33 [18-54] days from hospital discharge). CONCLUSION: Acute exposure to an ACEI/ARB before or during an episode of AKI was not associated with persistent AKD at the time of first clinic visit suggesting that the receipt of such agents does not impede kidney recovery following AKI. Contrary to prevailing recommendations and current practice, the continued administration of an ACEI/ARB during an episode of AKI or initiation of these agents prior to discharge may be safe.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".