Prediction of significant coronary artery disease in acute chest pain without infarction in emergency department: MAPAC Cardio-PreTest model

Borja M. Fernandez-Felix, Jesús Corres, Pilar Estelles Lerga, Eunate Arana-Arri, Gorka Arenaza Choperena, Miguel Castillo, Inés Pecharromán, Diego San José-Saras, Rosa Piqueras Olmeda, Aitor García De Vicuña, Virginia Gómez Usabiaga, Agustina Vicente, Javier Zamora*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Acute nontraumatic chest pain is a frequent reaso n for consultation in emergency departments and represents a diagnostic challenge. The objective is to estimate the risk of significant coronary artery disease (CAD) in patients with cardiogenic acute chest pain for whom the diagnosis of infarction was ruled out in the emergency department with a nondiagnostic ECG and negative high-sensitivity troponins. We prospectively recruited 1625 patients from emergency departments of seven Spanish hospitals. The outcome was presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests. In this study, we developed a predictive model and evaluated its performance and clinical utility. The prevalence of significant CAD was 14% [227/1625; 95% confidence interval (CI), 12-16]. MAPAC Cardio-PreTest model included seven predictors: age, sex, smoking, history of hypertension, family history of CAD, history of hyperuricaemia, and type of chest pain. The optimism-adjusted model discrimination was C-statistic 0.654 (95% CI, 0.618-0.693). Calibration plot showed good agreement between the predicted and observed risks, and calibration slope was 0.880 (95% CI, 0.731-1.108) and calibration-in-the-large -0.001 (95% CI, -0.141 to 0.132). The model increased net benefit and improved risk classification over the recommended approach by the European Society of Cardiology [Net Reclassification Index (NRI) of events = 5.3%, NRI of nonevents = 7.0%]. MAPAC Cardio-PreTest model is an online prediction tool to estimate the individualised probability of significant CAD in patients with acute chest pain without a diagnosis of infarction in emergency department. The model was more useful than the current alternatives in helping patients and clinicians make individually tailored choices about the intensity of monitoring or additional coronary tests.

Original languageEnglish
Pages (from-to)40-46
Number of pages7
JournalEuropean Journal of Emergency Medicine
Volume30
Issue number1
Early online date19 Dec 2022
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.

Keywords

  • coronary artery disease
  • emergency department
  • predictive model

ASJC Scopus subject areas

  • General Medicine

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