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A New Diagnostic Risk Calculator for Coronary Artery Disease
Singapore researchers developed “PRECISE”, the first diagnostic risk calculator for coronary artery disease in patients presenting chest pain at primary care.

A diagnostic risk calculator called “PRECISE” (Predictive Risk scorE for Coronary Artery Disease [CAD] In Southeast Asians with chEst pain)* has been developed to support diagnosing CAD among Southeast Asian patients. The result of the research study conducted by SingHealth Polyclinics (SHP) in collaboration with National Heart Centre Singapore (NHCS), Duke-NUS Medical School (Duke-NUS), and National Healthcare Group Polyclinics (NHGP), showed that PRECISE demonstrates clinical benefits when used as a decision support tool at the primary care setting.

Risk prediction tools aid physicians to evaluate the probability of CAD among patients presenting with chest pain at the primary healthcare setting, where the actual disease prevalence is low. The three common prediction tools currently available are the Duke Clinical Score (DCS), CAD Consortium Score (CCS), and the Marburg Heart Score (MHS). However, these tools have yet to be validated for use in an Asian population and are not widely used locally to support decision making in routine clinical practice. They may also overestimate the probability of CAD in the primary care setting, which may result in increased and unnecessary cardiac investigations.

With the aim to develop and validate a diagnostic risk prediction model for CAD in Southeast Asians, more than 1,600 patients who presented with symptoms of chest pain were identified and recruited at the eight polyclinics under SingHealth for the study. The patients were clinically stable and subsequently referred to the NHCS for further cardiac evaluation. Results show that close to 160 patients were ultimately diagnosed to have CAD, while the rest were assessed as CAD negative.

Patients were then followed up after a year to capture significant actual cardiovascular events. Out of the patients identified as CAD negative, below 1 per cent developed Major Adverse Cardiovascular Events (MACE).

Using the significant predictors of CAD in the study cohort, the “PRECISE” diagnostic risk calculator was built. The clinical variables included in the “PRECISE” risk calculator are age, gender, underlying chronic conditions, smoking status, type of chest pain, pain radiating to the neck, and electrocardiographic (ECG) changes. The performance of this new algorithm was further compared against that of the three common existing risk prediction tools using statistical methods.

“PRECISE” demonstrated excellent ability to discriminate between patients with and without CAD, faring better when compared to DCS, CCS, and MHS.

“‘PRECISE’ is the first diagnostic prediction model for CAD in Southeast Asians that is designed for use in a primary care setting. The PRECISE calculator incorporates readily available clinical variables and can be a useful clinical decision support tool. PRECISE also has the flexibility to assess the CAD risk both with and without ECG information,” said Dr. Sinead Wang, Consultant, SHP-Outram. Dr. Wang is also the main author of this study.

When a person suffers from chest pain, the family doctor is often the first physician he will seek help from. Using this clinical decision support tool as a guide, family doctors will be able to make an objective and evidence-based decision on which patients require more in-depth investigation,” added Dr. Wang.

“This cardiac risk prediction tool enables primary physicians to better assess a patient’s risk for heart disease so that patients can receive appropriate and timely care at our specialist centre. This will potentially help to streamline referral processes for those who require further investigations for chest pain,” shared Clinical Associate Professor Jonathan Yap, Consultant from the Department of Cardiology, NHCS, who is also a co-author of the study.

“Patients presenting with chest pain need to be managed safely, and in a timely and objective manner. About 10 per cent of our study participants were found to have CAD. ‘PRECISE’ will be a useful tool to identify local people at risk of coronary heart disease so that they are treated promptly at the appropriate care setting,” said Clinical Associate Professor Tan Ngiap Chuan, Director of Research, SHP and Vice-chair, Research, SingHealth-Duke NUS Family Medicine Academic Clinical Programme (FM ACP).

“‘PRECISE’ was developed for application across primary care practices. We plan to incorporate it in a chatbot and look forward to scale up to the polyclinics very soon,” added Dr. Tan.

*PRECISE link: https://webapps.duke-nus.edu.sg/tools/PRECISE


Source: SingHealth Polyclinics

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