Statin Use and Survival After Acute Kidney Injury
Bibliographic record
Abstract
<h3>Introduction</h3> The incidence of acute kidney injury (AKI) in hospitalized patients is rising, and survivors are at high risk for cardiovascular events and mortality. Effective strategies that improve long-term outcomes of AKI are unknown. <h3>Methods</h3> A retrospective cohort study was performed between 2008 and 2011. All subjects were followed until 31 March 2013, with a minimum follow-up of 2 years. Participants were adults 18 years of age or older, who developed AKI during a hospitalization and had chronic kidney disease (CKD) following discharge (n = 19,707 mean age 69.9 years, mean postdischarge estimated glomerular filtration rate (eGFR) 43.0 ml/min/1.73 m<sup>2</sup>). Exposure to statins was examined prior to the index hospitalization as well as within 2 years following hospital discharge. The primary outcome was mortality; secondary outcomes included all-cause re-hospitalization and cardiovascular events. <h3>Results</h3> Within 2 years of discharge, only 38.3% of the participants were prescribed a statin. After adjustment for comorbidities, statin use prior to admission, demographics, baseline kidney function, and a number of other factors, statin use was associated with lower mortality (hazard ratio, 0.74; 95% confidence interval, 0.69, 0.79) in AKI survivors with CKD. Patients who received a statin also had a lower risk of all cause rehospitalization (adjusted hazarad ratio, 0.90; 95% confidence interval, 0.85, 0.94). Statin use was not associated with a reduction in cardiovascular events. <h3>Discussion</h3> Among AKI survivors with CKD, statin use was associated with a lower risk of mortality and rehospitalization rates. This finding suggests that there is an opportunity to improve postdischarge care in AKI survivors.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".