ArticleArquivos brasileiros de cardiologia2025
Cardiac CT-Detected Vulnerable Plaques and Risk of Future Acute Myocardial Infarction: Predictive Value of CAC Scores and Inflammatory Burden Index.
Article in Arquivos brasileiros de cardiologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Improving Risk Stratification Beyond Coronary Calcium - Adding the Inflammatory Burden Index to Find the Vulnerable Patient.Arquivos brasileiros de cardiologia · 2026Article
- Prognostic Value of the Inflammatory Burden Index (IBI) in Coronary EventsReply.Arquivos brasileiros de cardiologia · 2026Article
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Abstract
backgroundComputed Tomography (CT) angiography is widely used as a basic non-invasive modality to evaluate coronary artery disease. Inflammatory burden index (IBI) is a systemic inflammation indicator reflecting the inflammatory status. It is still difficult to determine the high risk of future acute myocardial infarction (MI) in patients with plaque detected by CT angiography.
objectiveThis study aimed to evaluate the effectiveness of CAC scores and IBI in predicting MI risk among patients undergoing CT angiography for chest pain. We sought to assess the individual and combined predictive value of these indices, determine their optimal cut-off values, and compare MI risk across patient groups with varying CAC and IBI scores. We also aimed to evaluate the potential role of these markers in identifying 'vulnerable patients' at high risk for future cardiovascular events.
methodsThis retrospective study included 1235 patients who underwent CT angiography due to chest pain and were followed for 3 years (2.8-3.4). Patients were categorized into three models based on their CAC and IBI scores. The primary outcome was the occurrence of MI during the follow-up period. Statistical significance was established at p < 0.05 for all analyses.
resultsPatients who experienced MI had significantly higher IBI and CAC scores compared to those without MI. Logistic regression analysis identified CAC score and IBI as independent predictors of MI. ROC analysis determined optimal cut-off values for IBI (128) and CAC (102) in predicting MI. Kaplan-Meier analysis revealed a significant gradient in MI risk across the three models, with the highest risk observed in patients with both high IBI and CAC scores.
conclusionThe combination of IBI and CAC scores provides improved risk stratification for the prediction of future MI (vulnerable plaque) in patients with plaque detected by CT angiography. This approach may facilitate more specific treatment strategies for high-risk patients.
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