Abstract 14142: Patterns of Renin Angiotensin Aldosterone Inhibitor Use in Patients After Hospitalization With Acute Kidney Injury
Bibliographic record
Abstract
Background: Renin-angiotensin system inhibitors (RASi, i.e., ACEIs and ARBs) are vital to chronic disease management and they are often held in the setting of AKI. Reinitiation after hospital discharge requires careful coordination and puts patients at risk of inappropriately remaining off RASi. Aims: Characterize patterns of RASi use post-AKI hospitalization and identify factors associated with RASi discontinuation and reinitiation after discharge. Methods: A retrospective cohort study using ICES administrative data was conducted among adults ≥66 on RASi and discharged after hospitalization with AKI in Ontario (2015-2019). Prescription claims were used to identify patients who experienced RASi discontinuation (no RASi script renewal) after discharge. These patients were then followed for an additional 6 months to monitor for reinitiation. Modified Poisson and Cox regression models were used to identify factors associated with discontinuation and reinitiation, respectively, censoring those who died or were readmitted prior to reinitiation. Results: The cohort included 84,598 patients, mean age 80.3 years, 50.8% male. Overall, 42.2% continued their RASi, 37.1% discontinued, and use was indeterminable for the 20.7% who were readmitted or died before their prescription elapsed. Of the 31,390 patients with RASi discontinuation, 47.4% did not reinitiate and 34.8% reinitiated. Discontinuation was more likely in patients with CKD (RR = 1.13, 95% CI 1.10-1.16) or on diuretics (RR = 1.06, 95% CI 1.03-1.09). Reinitiation was more likely in patients in the highest income quintile (HR 1.08, 95% CI 1.02-1.15) or on diuretics (HR = 1.09, 95% CI 1.04-1.13), and less likely in patients with HF (HR = 0.89 95% CI 0.85-0.93), dementia (HR = 0.72, 95% CI 0.67-0.76), or rural residence (HR = 0.88, 95% CI 0.82-0.94). Conclusions: After hospitalization with AKI, nearly 2 in 5 patients discontinued their RASi at discharge, with one-third of these patients restarting within 6 months. Several patient-, provider-, and system-level factors were associated with patterns of RASi use after discharge. These can be used to identify patients at higher risk of experiencing RASi interruption, which may highlight opportunities for optimization of RASi use to improve patient care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".