Multimodal data-driven prognostic model for predicting new-onset ST-elevation myocardial infarction following emergency percutaneous coronary intervention

Background : Hypertension is an important contributing factor to atherosclerotic cardiovascular disease (ASCVD), and multiple risk factors, many of which are implicated in metabolic disorders, contribute to the cause of hypertension. Despite the promise of multimodal data-driven prediction model, no such prediction model was available to predict the risk of ASCVD in Chinese individuals with new-onset hypertension and no history of ASCVD. Methods : A total of 514 patients were randomly allocated to training and verification cohorts (ratio, 7 : 3). We employed Boruta feature selection and conducted multivariate Cox regression analyses to identify variables associated with ASCVD in these patients, which were subsequently utilized for constructing the predictive model. The performance of prediction model was assessed in terms of discriminatory power (C-index), calibration (calibration curves), and clinical utility [decision curve analysis (DCA)]. Results : This model was derived from four clinical variables: 24-h SBP coefficient of variation, 24-h DBP coefficient of variation, urea nitrogen and the triglyceride–glucose (TyG) index. Bootstrapping with 500 iterations was conducted to adjust the C-indexes were C-index = 0.731, 95% confidence interval (CI) 0.620–0.794 and C-index: 0.799, 95% CI 0.677–0.892 in the training and verification cohorts, respectively. Calibration plots with 500 bootstrapping iterations exhibited a strong correlation between the predicted and observed occurrences of ASCVD in both the training and verification cohorts. DCA analysis confirmed the clinical utility of this prediction model. The constructed nomogram demonstrated significant additional prognostic utility for ASCVD, as evidenced by improvements in the C-index, net reclassification improvement, integrated discrimination improvement, and DCA compared with the overall ASCVD risk assessment. Conclusion: The developed longitudinal prediction model based on multimodal data can effectively predict ASCVD risk in individuals with an initial diagnosis of hypertension. Trial registration : The trial was registered in the Chinese Clinical Trial Registry (ChiCTR2300074392).

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Novel Insights into Myocardial Fibrosis in Patients with New Onset ST-Elevation Myocardial Infarction Following Percutaneous Coronary Intervention through Enhanced Cardiac Magnetic Resonance Imaging : A Prospective Cohort Study

Oketunbi,

Wang,

Ding

et al. 2024

Preprint

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Background Myocardial fibrosis represents a prevalent pathological hallmark observed in a diverse range of chronic and acute cardiovascular disorders. However, relevant literature currently provides limited evidence regarding the determinants of myocardial fibrosis severity in patients with new-onset ST-Elevation Myocardial Infarction (STEMI) following successful emergent percutaneous coronary intervention (PCI) utilizing contrast-enhanced cardiac magnetic resonance (CE-CMR) imaging. Methods We prospectively enrolled a cohort of 78 patients presenting with new-onset ST-segment elevation myocardial infarction, who underwent successful emergent PCI within 12 hours from the onset of symptoms. Late Gadolinium Enhanced (LGE) was quantified employing CE-CMR, and patients were categorized into two groups based on the median LGE value. Results The median LGE was 16 (IQR 12 to 24). In comparison to patients with LGE below the median (n = 37), those in the group with LGE above the median (n = 41) exhibited significantly reduced left ventricular global radial strain, global circumferential strain, and global longitudinal strain. ( all p < 0.05). The infarcted radial segment (IRS), Infarcted circumferential segment (ICS) and infarcted longitudinal segment (ILS) exhibited significant reductions in patients with greater LGE ( all p < 0.05). The occurrence of microvascular obstruction (MVO) (p<0.001) and wall motion abnormality (WMA) (p < 0.01) were significantly higher in patients with a greater extent of LGE, despite successful reperfusion therapy. The LGE exhibited a moderate negative correlation with global circumferential segment(r= -0.547, p<0.001) and a low negative correlation with both Global Radial Segment and Global Longitudinal Segment ༈r= -0.434, p<0.001;r= -0.437, p<0.001). In the multivariate linear regression analysis model comprising gensini score, MVO, GRS, GCS, IRS and ILS, Gensini score (β=0.289;p = 0.001), the presence of MVO (β=0.378;p = 0.000) and GCS(β=−0.318; p = 0.012) emerged as the robust predictors of myocardial fibrosis. Conclusion The present study establishes a correlation between cardiac pathological structures, microcirculation, and myocardial fibrosis in the context of acute myocardial infarction. Therefore, it provides theoretical evidence from a pathological perspective regarding the progression of myocardial fibrosis in patients with new-onset STEMI following successful PCI. Trial registration The trial was registered in the Chinese Clinical Trial Registry (ChiCTR2400080282).

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Multimodal data-driven prognostic model for predicting new-onset ST-elevation myocardial infarction following emergency percutaneous coronary intervention

Cited by 4 publications

References 36 publications

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Novel Insights into Myocardial Fibrosis in Patients with New Onset ST-Elevation Myocardial Infarction Following Percutaneous Coronary Intervention through Enhanced Cardiac Magnetic Resonance Imaging : A Prospective Cohort Study

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