Development and Internal Validation of a Practical Model to Identify Observe Patients of the European Society of Cardiology 0/1-h Algorithm at Low Risk of a Coronary Diagnosis

Abstract

<b><i>Background:</i></b> Patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) assigned to the “observe” zone of the European Society of Cardiology (ESC) 0/1-h algorithm form a heterogeneous group known to have an unfavourable prognosis. We aim to elucidate the clinical characteristics and management of these patients and generate a model that is predictive of a coronary diagnosis at index visit to the emergency department (ED). <b><i>Methods:</i></b> A retrospective observational cohort study, including adult patients presenting to the ED with suspected NSTE-ACS assigned to the “observe” zone of the ESC 0/1-h algorithm. Multivariable logistic regression analysis was performed for the prediction of a coronary diagnosis. Internal validation was performed using bootstrap resampling. <b><i>Results:</i></b> A total of 750 patients were included; mean age 66 ± 13 years, 35% women, 50% with prior history of coronary artery disease (CAD). In 372 (50%) patients a diagnosis was established within 30 days of index presentation, of whom 169 (45%) patients had a coronary-related event. Multivariable logistic regression analysis generated a 12-point risk score incorporating 5 variables for the prediction of such event, including type of angina, chest pain occurring during inspiration, prior history of CAD, ST-segment deviation on electrocardiogram, and estimated glomerular filtration rate &#x3c;60. The final model had an optimism-corrected c-statistic of 0.78 (95% confidence interval [CI]: 0.74–0.82). A score &#x3c;6 ruled out a coronary event in 276 (37%) patients, with a sensitivity and negative predictive value of 90% (95% CI: 84–94) and 94% (91–96), respectively. <b><i>Conclusion:</i></b> A score &#x3c;6 identifies patients at low risk of a coronary diagnosis and can guide clinical decision-making in choosing the appropriate diagnostic test.