Association between age and readmission after percutaneous coronary intervention for acute myocardial infarction
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the association between age and the risk of 30-day unplanned readmission among adult patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI). METHODS: This retrospective analysis included patients from the Nationwide Readmissions Database with AMI who underwent PCI during 2013-2014. We used multivariable logistic regression model to calculate adjusted odds ratios (AORs) for risk of readmission. To examine potential non-linear association, we performed logistic regression with restricted cubic splines (RCS). RESULTS: Of the 492 550 patients with AMI aged above 18 years undergoing PCI during the index hospitalisation, 48 630 (9.87%) were readmitted within 30 days. Although the crude readmission rate of younger patients (aged 18-54 years) was the lowest (7.27%), younger patients had higher risk of readmission compared with patients aged 55-64 years for all-causes (AOR 1.06 (1.01 to 1.11), p=0.0129) and specific causes, such as AMI and chest pain (both cardiac and non-specific) after adjusted for covariates. Patients aged 65-74 years were at lower risk of all-cause readmission. Older patients (age ≥75 years) had higher risk of readmission for heart failure (AOR 1.50 (1.29 to 1.74)) and infection (AOR 1.44 (1.16 to 1.79)), but lower risk for chest pain. RCS analyses showed a U-shaped relationship between age and readmission risk. CONCLUSIONS: Our results suggest higher risk of readmission in younger patients for all-cause unplanned readmission after adjusted for covariates. The trends of readmission risk along with age were different for specific causes. Age-targeted initiatives are warranted to reduce preventable readmissions in patients with AMI undergoing PCI.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".