News Release

A nomogram to predict patients with obstructive coronary artery disease

Peer-Reviewed Publication

Compuscript Ltd

In a new publication from Cardiovascular Innovations and Applications; DOI https://doi.org/10.15212/CVIA.2021.0001, Zesen Han, Lihong Lai, Zhaokun Pu and Lan Yang from The People's Hospital of Hua County, Henan, China and Henan University of Science and Technology, Henan, China consider the use of nomograms to predict patients with obstructive coronary artery disease.

The authors developed and validated clinical prediction models for the development of a nomogram to estimate the probability of patients having coronary artery disease (CAD).

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.

###

Citation information: A Nomogram to Predict Patients with Obstructive Coronary Artery Disease: Development and Validation, Zesen Han, Lihong Lai, Zhaokun Pu and Lan Yang, Cardiovasc. Innov. App., 2021,
https://doi.org/10.15212/CVIA.2021.0001

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

CVIA is available on the IngentaConnect platform and at Cardiovascular Innovations and Applications. Submissions may be made using ScholarOne Manuscripts. There are no author submission or article processing fees. CVIA is indexed in the EMBASE, ESCI, OCLC, Primo Central (Ex Libris), Sherpa Romeo, NISC (National Information Services Corporation), DOAJ and Index Copernicus Databases. Follow CVIA on Twitter @CVIA_Journal; or Facebook.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.