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Observational Study
. 2022;147(3):251-260.
doi: 10.1159/000523718. Epub 2022 Feb 23.

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

Murat Arslan  1   2 , Eric Boersma  1 , Admir Dedic  1   2 , Eric A Dubois  1   3
Affiliations
Observational Study

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

Murat Arslan et al. Cardiology. 2022.

Abstract

Background: 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).

Methods: 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.

Results: 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 <60. The final model had an optimism-corrected c-statistic of 0.78 (95% confidence interval [CI]: 0.74-0.82). A score <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.

Conclusion: A score <6 identifies patients at low risk of a coronary diagnosis and can guide clinical decision-making in choosing the appropriate diagnostic test.

Keywords: Acute chest pain; Non-ST-elevation acute coronary syndrome; Observe group; Risk score.

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Conflict of interest statement

The authors declare that there is no conflict of interest.

Figures

Fig. 1
Fig. 1
Flow chart of the study population. NSTE-ACS, non-ST-elevation acute coronary syndrome.
Fig. 2
Fig. 2
Figure depicting the proportion of patients with an established diagnosis related to index visit, based on all available clinical data with their corresponding diagnostic categories.
Fig. 3
Fig. 3
ROC curves of risk scores for the prediction of a coronary diagnosis. AUC, area under the curve; HEART score, history, ECG, age, risk factors, and troponin score; PEKT score, prior history, ECG, kidney function, and type of chest pain score; ROC, receiver-operating characteristic.
Fig. 4
Fig. 4
One-year Kaplan-Meier survival curves in patients assigned to the “observe zone” of the ESC 0 h/1 h algorithm stratified based on diagnostic categories.
See this image and copyright information in PMC

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