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Curso de Atualização em Medicina Cardiovascular 2019
Reunião Anual Conjunta dos Grupos de Estudo de Cirurgia Cardíaca, Doenças Valvulares e Ecocardiografia da SPC
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07. Syncope and Bradycardia
08. Ventricular Arrhythmias and Sudden Cardiac Death (SCD)
09. Device Therapy
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Prediction of coronary artery bypass surgery indication in patients admitted for non-ST elevation myocardial infarction – the CABG-DAPE2S score.
Session:
Posters 5 - Écran 2 - Doença Coronária
Speaker:
Teresa Mota
Congress:
CPC 2019
Topic:
E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
Theme:
13. Acute Coronary Syndromes
Subtheme:
13.4 Acute Coronary Syndromes – Treatment
Session Type:
Posters
FP Number:
---
Authors:
Teresa Faria Da Mota; Pedro Oliveira De Azevedo; Raquel Menezes Fernandes; João De Sousa Bispo; João Pedro Moura Guedes; Daniela Carvalho; Dina Bento; Nuno Marques; Walter Santos; Jorge Mimoso; Ilidio Paulos De Jesus
Abstract
<p><strong>Introduction: </strong>A significant number of patients admitted for Non-ST Elevation Myocardial Infarction (NSTEMI) have multivessel complex coronary artery disease (CAD) and benefit from Coronary Artery Bypass Graft surgery (CABG). These patients frequently present high-risk surgical profiles, constituting a challenging group when it comes to balancing ischemic and haemorrhagic risk.</p> <p><strong>Objective:</strong> To develop a simple predictive risk model of referral to CABG in patients admitted for NSTEMI.</p> <p><strong>Methods:</strong> The authors present a retrospective, descriptive and correlational study including all patients admitted for NSTEMI in a Cardiology department between the 1st of October 2010 and the 1st of October 2018. Demographic profile, clinical characteristics, risk factors and hospitalization data of NSTEMI patients referred to CABG were studied, and a correlational analysis was performed with Chi-square test for categorical variables and t-Student test for continuous variables (confidence level of 95%). Independent predictors of CABG in patients with NSTEMI were identified through Binary logistic regression analysis, using a significance level of 0,05. A discriminatory function was subsequently applied, and the Wilks lambda test was used to determine the discriminant score for the studied groups. The authors used SPSS 24,0 for statistical analysis.</p> <p><strong>Results:</strong> A total of 2476 patients were included, 668 (27%) of which were female, with a mean age of 68,5±13,4 years. In the studied sample, 273 patients (11%) were proposed to CABG. The authors found a significant association between CABG and multiple clinical, laboratorial and therapeutical variables, but after multivariate analysis only male sex, previous Diabetes Mellitus, previous angina, previous Percutaneous coronary intervention, absence of a normal EKG, ST segment depression at admission, sinus rythm and brain natriuretic peptide (BNP) >100pg/mL proved to be independent predictors of referral. Using these variables, the authors developed a risk model to predict CABG referral in NSTEMI patients: -0,614 - (0,756 x female sex) + (0,305 x diabetes) + (0,631 x angina) - (1,513 x previous PCI) + (1,216 x sinus rythm) + (0,672 x ST depression) - (0,806 x normal EKG) + (0,562 x BNP>100). In this function, variables should be substituted by 1 or 0, depending on wheter the condition they specify is present or absent. The optimal discrimination cutoff was 0,23, with a 64% sensibility and 59% specificity, and a discriminant power of 60%.</p> <p><strong>Conclusion: </strong>Being able to predict referral to surgical revascularization in NSTEMI may help physicians to optimize a specific approach in each patient, in particular with regard to anti-thrombotic strategies. The authors developed a risk predicting model for CABG in NSTEMI patients based on simple clinical and laboratory variables, which will require validation in a larger cohort, before it can be applied in a clinical context.</p>
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