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Published on: February 16, 2011
A risk score model for predicting cardiac rupture after acute myocardial infarction
Yuan Fu1, Kui-Bao Li, Xin-Chun Yang
1Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.
Insights
A new risk score model accurately predicts cardiac rupture (CR) after acute myocardial infarction (AMI). This simple tool aids clinicians in identifying high-risk patients, improving patient outcomes and reducing mortality.
Area of Science:
- Cardiology
- Medical Risk Prediction
- Acute Myocardial Infarction Complications
Background:
- Cardiac rupture (CR) is a life-threatening complication of acute myocardial infarction (AMI).
- Existing risk stratification models for CR post-AMI are lacking.
- This study aimed to develop a simple, clinically applicable risk score for CR after AMI.
Observation:
- A retrospective case-control study included 53 CR patients and 524 controls from 7985 AMI patients (2010-2017).
- The incidence of CR was 0.67%, with significantly higher hospital mortality (92.5%) compared to non-CR patients (4.01%).
Findings:
- Independent predictors of CR included older age, female gender, elevated heart rate, lower BMI (<25 kg/m²), reduced left ventricular ejection fraction (LVEF), and absence of primary percutaneous coronary intervention (pPCI).
- The developed risk score model demonstrated excellent discrimination (AUC=0.895, optimism-corrected AUC=0.821).
Implications:
- The novel risk score offers a simple and accurate method for predicting CR in AMI patients.
- Early identification of high-risk individuals can facilitate timely interventions and potentially improve survival rates.
- This tool can be easily integrated into routine clinical practice for enhanced patient management.
Background:
Cardiac rupture (CR) is a major lethal complication of acute myocardial infarction (AMI). However, no valid risk score model was found to predict CR after AMI in previous researches. This study aimed to establish a simple model to assess risk of CR after AMI, which could be easily used in a clinical environment.
Methods:
This was a retrospective case-control study that included 53 consecutive patients with CR after AMI during a period from January 1, 2010 to December 31, 2017. The controls included 524 patients who were selected randomly from 7932 AMI patients without CR at a 1:10 ratio. Risk factors for CR were identified using univariate analysis and multivariate logistic regression. Risk score model was developed based on multiple regression coefficients. Performance of risk model was evaluated using receiver-operating characteristic (ROC) curves and internal validity was explored using bootstrap analysis.
Results:
Among all 7985 AMI patients, 53 (0.67%) had CR (free wall rupture, n = 39; ventricular septal rupture, n = 14). Hospital mortalities were 92.5% and 4.01% in patients with and without CR (P < 0.001). Independent variables associated with CR included: older age, female gender, higher heart rate at admission, body mass index (BMI) <25 kg/m, lower left ventricular ejection fraction (LVEF) and no primary percutaneous coronary intervention (pPCI) treatment. In ROC analysis, our CR risk assess model demonstrated a very good discriminate power (area under the curve [AUC] = 0.895, 95% confidence interval: 0.845-0.944, optimism-corrected AUC = 0.821, P < 0.001).
Conclusion:
This study developed a novel risk score model to help predict CR after AMI, which had high accuracy and was very simple to use.
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