Early postoperative acute myocardial infarction in kidney transplant recipients: A nested case‐control study
Bibliographic record
Abstract
INTRODUCTION: The epidemiology of early acute myocardial infarctions after kidney transplantation has not been well characterized. This study sought to examine the incidence, risk factors, and clinical outcomes of early acute myocardial infarctions or EAMI in kidney transplant recipients. METHODS: A total of 1976 patients who underwent kidney transplantation at our center from Jan 1, 2000, to Sept 30, 2016, were included. A nested case-control design was used to study EAMI risk factors using a conditional logistic regression model. A Cox proportional hazards model was used to assess the association of EAMI with death-censored graft failure, death with graft function, and total graft failure. RESULTS: Seventy four patients had an EAMI within 3 months post-transplant. Based on univariable analyses, risk factors for EAMI included age and recipient history of diabetes mellitus or coronary artery disease. After adjustment, recipient history of coronary artery disease was the only independent predictor for EAMI (OR 3.76, p < .001). Patients who experienced EAMI were more likely to experience death-censored graft failure, death with graft function, and total graft failure. CONCLUSION: While the incidence of EAMI in kidney transplant recipients is relatively low, these data show that EAMI has profound long-term effects on morbidity and mortality.
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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 | 0.000 |
| 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 | 0.000 |
| 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".