Contrast-Induced Acute Kidney Injury and Risk of Adverse Clinical Outcomes After Coronary Angiography
Bibliographic record
Abstract
BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) has been associated with mortality, although it has been suggested this association may be attributable to confounding. We performed a systematic review and meta-analysis to characterize the associations between CI-AKI and subsequent clinical outcomes. METHODS AND RESULTS: We identified studies using MEDLINE (1950 to June 2011) and Embase (1980 to June 2011), manual bibliographic searches, and contact with experts. We included observational studies that characterized outcomes among patients with and without AKI (based on changes in serum creatinine) after coronary angiography. Eligible studies reported at least 1 of mortality, cardiovascular events, end-stage renal disease, or length of hospital stay. Thirty-nine observational studies met inclusion criteria. Of 34 studies reporting mortality (including 139 603 participants), 33 reported an increased risk of death in those with CI-AKI, although the effect size varied between studies (I(2)=93.5%). Between-study heterogeneity was partially explained by whether adjustment for confounding features was performed (11 studies without adjustment; pooled crude risk ratio, 8.19; 95% confidence interval, 4.30-15.60; I(2)=77.3% versus 23 studies with adjustment; pooled adjusted risk ratio, 2.39; 95% confidence interval, 1.98-2.90; I(2)=88.3%). CI-AKI was consistently associated with an increased risk of cardiovascular events in 14 studies, end-stage renal disease in 3 studies, and prolonged hospitalization in 11 studies. CONCLUSIONS: CI-AKI is associated with an increased risk of mortality, cardiovascular events, renal failure, and prolonged hospitalization. However, the association between CI-AKI and mortality is strongly confounded by baseline clinical characteristics that simultaneously predispose to both kidney injury and mortality, and the risk attributable to CI-AKI is much lower than that reported from unadjusted studies.
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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 | 0.017 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 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".