Prediction models as gatekeepers for diagnostic testing in angina patients with suspected chronic coronary syndrome
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Prediction models as gatekeepers for diagnostic testing in angina patients with suspected chronic coronary syndrome. / Bjerking, Louise Hougesen; Winther, Simon; Hansen, Kim Wadt; Galatius, Søren; Böttcher, Morten; Prescott, Eva.
In: European Heart Journal - Quality of Care and Clinical Outcomes, Vol. 8, No. 6, 2022, p. 630-639.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Prediction models as gatekeepers for diagnostic testing in angina patients with suspected chronic coronary syndrome
AU - Bjerking, Louise Hougesen
AU - Winther, Simon
AU - Hansen, Kim Wadt
AU - Galatius, Søren
AU - Böttcher, Morten
AU - Prescott, Eva
PY - 2022
Y1 - 2022
N2 - Aims Assessment of pre-test probability (PTP) is an important gatekeeper when selecting patients for diagnostic testing for coronary artery disease (CAD). The 2019 European Society of Cardiology (ESC) guidelines recommend upgrading PTP based on clinical risk factors but provide no estimates of how these affect PTP. We aimed to validate two published PTP models in a contemporary low-CAD-prevalence cohort and compare with the ESC 2019 PTP. Methods and results Previously published basic and clinical prediction models and the ESC 2019 PTP were validated in 42 328 patients (54% women) >= 30 years old without previous CAD referred for cardiac computed tomography angiography in a region of Denmark from 2008 to 2017. Obstructive CAD prevalence was 8.8%. The ESC 2019 PTP and basic model included angina symptoms, sex, and age, while the clinical model added diabetes mellitus family history of CAD, and dyslipidaemia. Discrimination was good for all three models [area under the receiver operating curve (AUC) 0.76, 95% confidence interval (CI) (0.75-0.77), 0.74 (0.73-0.75), and 0.76 (0.75-0.76), respectively]. Using the clinically relevant low predicted probability
AB - Aims Assessment of pre-test probability (PTP) is an important gatekeeper when selecting patients for diagnostic testing for coronary artery disease (CAD). The 2019 European Society of Cardiology (ESC) guidelines recommend upgrading PTP based on clinical risk factors but provide no estimates of how these affect PTP. We aimed to validate two published PTP models in a contemporary low-CAD-prevalence cohort and compare with the ESC 2019 PTP. Methods and results Previously published basic and clinical prediction models and the ESC 2019 PTP were validated in 42 328 patients (54% women) >= 30 years old without previous CAD referred for cardiac computed tomography angiography in a region of Denmark from 2008 to 2017. Obstructive CAD prevalence was 8.8%. The ESC 2019 PTP and basic model included angina symptoms, sex, and age, while the clinical model added diabetes mellitus family history of CAD, and dyslipidaemia. Discrimination was good for all three models [area under the receiver operating curve (AUC) 0.76, 95% confidence interval (CI) (0.75-0.77), 0.74 (0.73-0.75), and 0.76 (0.75-0.76), respectively]. Using the clinically relevant low predicted probability
KW - Pre-test probability
KW - Risk stratification
KW - Prediction model
KW - Chronic coronary syndrome
KW - External validation
KW - ARTERY CALCIUM
KW - ESC GUIDELINES
KW - PROBABILITY
KW - VALIDATION
KW - MANAGEMENT
KW - OUTCOMES
KW - PROMISE
KW - SOCIETY
KW - CURVE
U2 - 10.1093/ehjqcco/qcac025
DO - 10.1093/ehjqcco/qcac025
M3 - Journal article
C2 - 35575616
VL - 8
SP - 630
EP - 639
JO - European Heart Journal - Quality of Care and Clinical Outcomes
JF - European Heart Journal - Quality of Care and Clinical Outcomes
SN - 2058-5225
IS - 6
ER -
ID: 328443488