Contrast-Associated AKI and Use of Cardiovascular Medications after Acute Coronary Syndrome
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: AKI after coronary angiography is associated with poor long-term outcomes. The relationship between contrast-associated AKI and subsequent use of prognosis-modifying cardiovascular medications is unknown. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A cohort study of 5911 participants 66 years of age or older with acute coronary syndrome who received a coronary angiogram in Alberta, Canada was performed between November 1, 2002, and November 30, 2008. AKI was identified according to Kidney Disease Improving Global Outcomes AKI criteria. RESULTS: In multivariable logistic regression models, compared with participants without AKI, those with stages 1 and 2-3 AKI had lower odds of subsequent use of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker within 120 days of hospital discharge (adjusted odds ratio, 0.65; 95% confidence interval, 0.53 to 0.80 and odds ratio, 0.34; 95% confidence interval, 0.23 to 0.48, respectively). Subsequent statin and β-blockers use within 120 days of hospital discharge was significantly lower among those with stages 2-3 AKI (adjusted odds ratio, 0.44; 95% confidence interval, 0.31 to 0.64 and odds ratio, 0.46; 95% confidence interval, 0.31 to 0.66, respectively). These associations were consistently seen in patients with diabetes mellitus, heart failure, low baseline eGFR, and albuminuria; 952 participants died during subsequent follow-up after hospital discharge (mean=3.1 years). The use of each class of cardiovascular medication was associated with lower mortality, including among those who had experienced AKI. CONCLUSIONS: Strategies to optimize the use of cardiac medications in people with AKI after coronary angiography might improve care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".