SPC365

Incorporating coronary calcification into pretest assessment of the likelihood of coronary artery disease – validation and recalibration of a new diagnostic tool

Session: CO 01 - Doença coronária
Speaker: Pedro M. Lopes

Congress: CPC 2021
Topic: E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
Theme: 12. Coronary Artery Disease (Chronic)
Subtheme: 12.3 Coronary Artery Disease – Diagnostic Methods
Session Type: Comunicações Orais
FP Number: ---
Authors: Pedro M. Lopes; João Presume; Pedro de Araújo Gonçalves; Francisco Albuquerque; Pedro Freitas; Sara Guerreiro; João Abecasis; Ana Coutinho Santos; Carla Saraiva; Miguel Mendes; Hugo Marques; António m. Ferreira

<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Background: </strong></span></span></p>

<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">A new clinical tool was recently proposed to improve the estimation of pre-test probability of obstructive coronary artery disease (CAD) by incorporating coronary artery calcium score (CACS) with clinical risk factors. This new model (Clinical+CACS) showed improved prediction when compared to the method recommended by the 2019 ESC guidelines on chronic coronary syndromes, but was never tested or adjusted for use in our population. The aim of this study was to assess the performance of this new method in a Portuguese cohort of symptomatic patients referred for coronary computed tomography angiography (CCTA), and to recalibrate it if necessary. </span></span></p>

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<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Methods: </strong></span></span></p>

<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">We conducted a two-center cross-sectional study assessing symptomatic patients who underwent CCTA for suspected CAD. Key exclusion criteria were age </span><span style="color:black">&lt; 30 years, known CAD, suspected acute coronary syndrome, or symptoms other than chest pain or dyspnea</span><span style="color:black">. Obstructive CAD was defined as any luminal stenosis </span>&ge;50% on CCTA. The Clinical+CACS prediction model was assessed for discrimination and calibration. A logistical recalibration of the model was conducted in a random sample of 50% of the patients and subsequently validated in the other half.</span></span></p>

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<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong><span style="color:black">Results:</span></strong><span style="color:black"> </span></span></span></p>

<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">A total of 1910 patients (mean age 60 </span><span style="font-family:Symbol"><span style="color:black">&plusmn;</span></span><span style="color:black"> 11 years, 60% women) were included in the analysis. Symptom</span> <span style="color:black">characteristics were: 39% non-anginal chest pain, 30% atypical angina, 19% dyspnea and 12% typical angina. The observed </span><span style="color:black">prevalence of obstructive CAD was 12.9% (n = 247). Patients with obstructive CAD were more often male, were significantly older, had higher prevalence of typical angina and cardiovascular risk factors, and higher CACS values. The new Clinical+CACS tool showed greater discriminative power than the ESC 2019 prediction model, with a C-statistic of 0.83 (CI 95% 0.81-0.86) versus 0.67 (CI 95% 0.64-0.71), respectively (p-value for comparison &lt; 0.001</span>). Before recalibration, the Clinical+CACS model underestimated the likelihood of CAD in our population across all quartiles of pretest probability (mean relative underestimation of 49%), <span style="color:black">which was subsequently corrected by the recalibration procedure - Figure.</span></span></span></p>

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<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong><span style="color:black">Conclusions: </span></strong></span></span></p>

<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="color:black">In a Portuguese cohort of symptomatic patients </span><span style="color:black">undergoing CCTA for suspected CAD, the new Clinical+CACS model showed better discrimination power than the 2019 ESC method. The underestimation of the Clinical+CACS model was corrected by recalibrating it for our population. This new tool might prove useful for guiding decisions on the need for further testing. </span></span></span></p>