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Open Access A Nomogram to Predict Patients with Obstructive Coronary Artery Disease: Development and Validation

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This article is Open Access under the terms of the Creative Commons CC BY-NC licence.

Objective: To develop and validate clinical prediction models for the development of a nomogram to estimate the probability of patients having coronary artery disease (CAD).

Methods and Results: A total of 1,025 patients referred for coronary angiography were included in a retrospective, single-center study. Randomly, 720 patients (70%) were selected as the development group and the other patients were selected as the validation group. Multivariate logistic regression analysis showed that the seven risk factors age, sex, systolic blood pressure, lipoprotein-associated phospholipase A2, type of angina, hypertension, and diabetes were significant for diagnosis of CAD, from which we established model A. We established model B with the risk factors age, sex, height, systolic blood pressure, low-density lipoprotein cholesterol, lipoprotein-associated phospholipase A2, type of angina, hypertension, and diabetes via the Akaike information criterion. The risk factors from the original Framingham Risk Score were used for model C. From comparison of the areas under the receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement of models A, B, and C, we chose model B to develop the nomogram because of its fitness in discrimination, calibration, and clinical efficiency. The nomogram for diagnosis of CAD could be used easily and conveniently.

Conclusion: An individualized clinical prediction model for patients with CAD allowed an accurate estimation in Chinese populations. The Akaike information criterion is a better method in screening risk factors. The net reclassification improvement and integrated discrimination improvement are better than the area under the receiver operating characteristic curve in discrimination. Decision curve analysis can be used to evaluate the efficiency of clinical prediction models.

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Keywords: Coronary artery disease; clinical decision rules; nomogram; risk factors

Document Type: Research Article

Affiliations: 1: The People’s Hospital of Hua County, Anyang, 456400 Henan, China 2: The First Affiliated Hospital and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003 Henan, China

Publication date: May 1, 2021

This article was made available online on February 2, 2021 as a Fast Track article with title: "A Nomogram to Predict Patients with Obstructive Coronary Artery Disease: Development and Validation".

More about this publication?
  • Cardiovascular Innovations and Applications (CVIA) publishes focused articles and original clinical research that explore novel developments in cardiovascular disease, effective control and rehabilitation in cardiovascular disease, and promote cardiovascular innovations and applications for the betterment of public health globally. The journal publishes basic research that has clinical applicability in order to promote timely communication of the latest insights relating to coronary artery disease, heart failure, hypertension, cardiac arrhythmia, prevention of cardiovascular disease with a heavy emphasis on risk factor modification. Cardiovascular Innovations and Applications is the official journal of the Great Wall International Congress of Cardiology (GW-ICC). It aims to continue the work of the GW-ICC by providing a global scientific communication platform for cardiologists that bridges East and West.

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