The Impact of Admission Serum Creatinine on Major Adverse Clinical Events in ST-Segment Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention
Bibliographic record
Abstract
Background: Impaired renal function has been shown in previous studies to be an independent predictor of cardiovascular adverse events amongst patients admitted for percutaneous coronary intervention (PCI) following ST-segment elevation myocardial infarction (STEMI). This study investigates the impact of admission serum creatinine (SCr) on major cardiovascular outcomes among STEMI patients undergoing PCI. Methods: A retrospective study of patients admitted for PCI following STEMI was conducted using the National Cardiovascular Database Action Registry (NCDR) at Cleveland Clinic Akron General (CCAG) Hospital. The primary outcome was a composite of major clinical events: cardiogenic shock, atrial fibrillation, ventricular tachycardia/fibrillation, heart failure, bleeding and mechanical ventilation. SCr was an independent and continuous variable. Results: A total of 656 patients included in the study with the diagnosis of STEMI who subsequently underwent primary PCI. Patients with eGFR < 60 mL/min/1.73 m 2 on admission had an increased incidence of cardiogenic shock (P = 0.001), bleeding (P < 0.001), heart failure (P < 0.0005) and higher mortality rates (P = 0.0005). Furthermore, in the setting of STEMI, elevated SCr was also associated with an increased risk of developing major adverse events like cardiogenic shock (P = 0.05), bleeding (P = 0.05), and heart failure (P = 0.005). Conclusions: In the setting of STEMI, elevated SCr and eGFR < 60 mL/min/1.73 m 2 was associated with an increased risk of developing major adverse events including cardiogenic shock, bleeding and heart failure. Cardiol Res. 2018;9(2):94-98 doi: https://doi.org/10.14740/cr689w Â
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".