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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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A. Basics
B. Imaging
C. Arrhythmias and Device Therapy
D. Heart Failure
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01. History of Cardiology
02. Clinical Skills
03. Imaging
04. Arrhythmias, General
05. Atrial Fibrillation
06. Supraventricular Tachycardia (non-AF)
07. Syncope and Bradycardia
08. Ventricular Arrhythmias and Sudden Cardiac Death (SCD)
09. Device Therapy
10. Chronic Heart Failure
11. Acute Heart Failure
12. Coronary Artery Disease (Chronic)
13. Acute Coronary Syndromes
14. Acute Cardiac Care
15. Valvular Heart Disease
16. Infective Endocarditis
17. Myocardial Disease
18. Pericardial Disease
19. Tumors of the Heart
20. Congenital Heart Disease and Pediatric Cardiology
21. Pulmonary Circulation, Pulmonary Embolism, Right Heart Failure
22. Aortic Disease
23. Peripheral Vascular and Cerebrovascular Disease
24. Stroke
25. Interventional Cardiology
26. Cardiovascular Surgery
27. Hypertension
28. Risk Factors and Prevention
29. Rehabilitation and Sports Cardiology
30. Cardiovascular Disease in Special Populations
31. Pharmacology and Pharmacotherapy
32. Cardiovascular Nursing
33. e-Cardiology / Digital Health
34. Public Health and Health Economics
35. Research Methodology
36. Basic Science
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NAS2H score – a novel predictive score of 1-year all cause mortality in acute coronary syndromes.
Session:
Posters 5 - Écran 1 - 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:
13.2 Acute Coronary Syndromes – Epidemiology, Prognosis, Outcome
Session Type:
Posters
FP Number:
---
Authors:
Teresa Faria Da Mota; João De Sousa Bispo; Pedro Oliveira De Azevedo; Raquel Menezes Fernandes; Daniela Carvalho; João Pedro Moura Guedes; Dina Bento; Walter Santos; Nuno Marques; Jorge Mimoso; Ilidio Paulos De Jesus
Abstract
<p><strong>Introduction: </strong>In patients admitted for Acute Coronary Syndromes (ACS), mortality is influenced by several clinical and therapeutical factors, and management of these patients should be guided by an estimate of individual risk.</p> <p><strong>Objective:</strong> To develop a simple predictive model of 1-year mortality in patients admitted for ACS.</p> <p><strong>Methods:</strong> The authors present a retrospective, descriptive and correlational study including all patients admitted for Acute Coronary Syndrome (ACS) in a Cardiology department between the 1st of October 2010 and the 1st of October 2017. A 1-year (1y) follow-up was made through registry consultation and phone call by a Cardiologist. Patients with 1y mortality (1yM) events were studied regarding baseline demographic and clinical characteristics, risk factors and hospitalization data, and a correlational analysis with Chi-square test for categorical variables and t-Student test for continuous variables (confidence level of 95%) was performed. Independent predictors of 1yM were identified through binary logistic regression analysis, using a significance level of 0,05. A discriminatory function was 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 3251 patients were included, 826 (25,4%) of which were female, with a mean age of 65,5±13,4 years. In the studied sample, 268 patients (8,2%) died in the year following hospital discharge; this group had a mean age of 65,6±13,2 years, and 80 (29,9%) were female patients. There was a significant association between 1yM and multiple clinical, therapeutical and laboratorial variables, but after multivariate analysis only age greater than 65 years old (yo) [p=0,001], previous stroke [p=0,005], haemoglobin (Hb) <10mg/dL [p<0,001], brain natriuretic peptide (BNP) >100pg/mL [p=0,001], and left ventricular ejection fraction (LVEF) <50% [p <0,001] proved to be independent predictors of the studied outcome. Using these variables, the authors developed a scoring model to predict 1yM in patients admitted for ACS with the following formula = 0,002 + (0,736 x Age > 65yo) + (0,91 x previous stroke) + (2,562 x Hb <10) + (0,63 x BNP >100) - (1,207 x FEVE >50%). In this function, variables should be substituted by 1 or 0, depending on wheter they are present or not. The discrimination cutoff was 0,57, with a 70,6% sensibility and 75,9% specificity, and a discriminant power of 75,4%.</p> <p><strong>Conclusion: </strong>Defining the mortality risk of ACS patients after discharge represents a real challenge and demands a careful evaluation of multiple factors in an attempt to achieve an accurate estimation of risk. The authors developed a predicting model for 1yM in ACS patients, with a good discriminant power, based on simple variables. The present score will require validation in a larger cohort of ACS patients before it can be applied in a clinical context.</p>
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