Cardiovascular Drug Use After Acute Kidney Injury Among Hospitalized Patients With a History of Myocardial Infarction
Bibliographic record
Abstract
Introduction: Patients who survive acute kidney injury (AKI) may receive fewer cardioprotective drugs. Our objective was to measure the difference in time to dispensing of evidence-based cardiovascular drugs in patients with a history of myocardial infarction (MI) with and without AKI. Methods: This was a population-based cohort study of patients 66 years of age and older with a history of MI who survived a hospitalization complicated with AKI, propensity-score matched to patients without AKI. The primary outcome was time to outpatient dispensing of an angiotensin-converting enzyme inhibitor (ACEi)/angiotensin II receptor blocker (ARB), statin, or β-blocker within 1 year of hospital discharge. Results: We identified 28,871 patients with AKI, of whom 21,452 were matched 1:1 to patients without AKI. In the matched cohort, mean age was 80 years, 40% were female, and 34% had an MI during the index hospitalization. AKI was associated with less frequent dispensing of all 3 cardiovascular drug classes within 1 year of hospital discharge (subdistribution hazard ratio [sHR], 0.93; 95% confidence interval [CI], 0.91-0.95). This association was most pronounced in patients with stage 2 (sHR, 0.81; 95% CI, 0.75-0.88) and stage 3 (sHR, 0.71; 95% CI, 0.64-0.79) AKI. We observed less frequent dispensing of statins in patients with stage 2 (sHR, 0.87; 95% CI, 0.81-0.92) and stage 3 (sHR, 0.85; 95% CI, 0.78-0.93) AKI and less frequent dispensing of β-blockers in patients with stage 3 AKI (sHR, 0.86; 95% CI, 0.79-0.94). Conclusion: In patients with a history of MI, survivors of AKI were less likely to receive prescriptions for ACEi/ARB, statins, or β-blockers within 1 year of hospital discharge. This association was most pronounced in patients with stages 2 and 3 AKI.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".