Family history does not predict angiographic localization or severity of coronary artery disease

A Simple Modified Framingham Scoring System to Predict Obstructive Coronary Artery Disease

Development of simple non-invasive risk prediction model would help in early prediction of coronary artery disease (CAD) reducing the burden on public health. This paper demonstrates a risk prediction scoring system to predict obstructive coronary artery disease (OCAD) in CAD patients. A total of 13,082 patients, referred for coronary angiography (CAG) in TRUST trial, were included in the development of a multivariable diagnostic prediction model. External validation of the model used 1009 patients from PRECOMIN study. The occurrence of OCAD was observed in 73.1% and 75.1% patients in TRUST (development) and PRECOMIN study (validation) cohorts, respectively. Good discrimination and calibration were obtained in both development and validation datasets (C-statistics 0.686 and 0.677; Hosmer-Lemeshow χ² = 5.19, p = 0.74 and χ² = 8.60, p = 0.38, respectively). The simple risk prediction model and risk scoring system developed on the basis of routine clinical variables showed good performance for estimation of OCAD in relative high-risk patients with suspected CAD.

A computational framework to characterize and compare the geometry of coronary networks

This work presents a computational framework to perform a systematic and comprehensive assessment of the morphometry of coronary arteries from in vivo medical images. The methodology embraces image segmentation, arterial vessel representation, characterization and comparison, data storage, and finally analysis. Validation is performed using a sample of 48 patients. Data mining of morphometric information of several coronary arteries is presented. Results agree to medical reports in terms of basic geometric and anatomical variables. Concerning geometric descriptors, inter-artery and intra-artery correlations are studied. Data reported here can be useful for the construction and setup of blood flow models of the coronary circulation. Finally, as an application example, similarity criterion to assess vasculature likelihood based on geometric features is presented and used to test geometric similarity among sibling patients. Results indicate that likelihood, measured through geometric descriptors, is stronger between siblings compared with non-relative patients. Copyright © 2016 John Wiley & Sons, Ltd.