Researchers assess the use of nomograms to predict obstructive coronary artery disease

In a new publication from Cardiovascular Innovations and Applications, 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.