Login
Search
Search
0 Dates
2024
2023
2022
2021
2020
2019
2018
0 Events
CPC 2018
CPC 2019
Curso de Atualização em Medicina Cardiovascular 2019
Reunião Anual Conjunta dos Grupos de Estudo de Cirurgia Cardíaca, Doenças Valvulares e Ecocardiografia da SPC
CPC 2020
CPC 2021
CPC 2022
CPC 2023
CPC 2024
0 Topics
A. Basics
B. Imaging
C. Arrhythmias and Device Therapy
D. Heart Failure
E. Coronary Artery Disease, Acute Coronary Syndromes, Acute Cardiac Care
F. Valvular, Myocardial, Pericardial, Pulmonary, Congenital Heart Disease
G. Aortic Disease, Peripheral Vascular Disease, Stroke
H. Interventional Cardiology and Cardiovascular Surgery
I. Hypertension
J. Preventive Cardiology
K. Cardiovascular Disease In Special Populations
L. Cardiovascular Pharmacology
M. Cardiovascular Nursing
N. E-Cardiology / Digital Health, Public Health, Health Economics, Research Methodology
O. Basic Science
P. Other
0 Themes
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
37. Miscellanea
0 Resources
Abstract
Slides
Vídeo
Report
CLEAR FILTERS
Can we predict accurate in-hospital mortality risk in our Acute Coronary Syndromes patients?
Session:
Posters 2 - Écran 9 - 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 Pedro Moura Guedes; Daniela Carvalho; Raquel Menezes Fernandes; João De Sousa Bispo; Pedro Oliveira De Azevedo; Dina Bento; Nuno Marques; Walter Santos; Jorge Mimoso; Ilidio Paulos De Jesus
Abstract
<p><strong>Introduction: </strong>Patients admitted for Acute Coronary Syndromes (ACS) have a varied in-hospital clinical course depending on previous conditions and risk factors. In-hospital mortality (ihM) in ACS has been decreasing over the years, but it still represents an important contributor to the global burden of coronary artery disease.</p> <p><strong>Objective:</strong> To develop a simple predictive score for assessment of in-hospital mortality risk 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 2018. Two groups were defined, taking into account patients’ vital status at discharge (survival vs. death). The two groups were compared in terms of risk factors, clinical profile and hospitalization data, using correlational tools such as Chi-square test for categorical variables and t-Student test for continuous variables. Independent predictors of ihM were determined applying a Binary logistic regression model, with a predefined significance level of 0,05. With recource to a discriminatory function and the Wilks lambda test the authors determined a discriminant score for the studied groups. SPSS 24,0 was employed for statistical analysis. </p> <p><strong>Results:</strong> A total of 4458 patients were included with a mean age of 65,6±13,2 years, comprising 1120 (25,1%) females. There were 160 (3,6%) patients who died during hospital stay, with higher rates of ihM ocurring in women and patients older than 65 years. IhM was significantly associated with several cardiovascular risk factors and previous conditions, as well as ambulatory prescribed therapies. However, a multivariate analysis restricted independent predictors of ihM to age > 65 years [p<0,001], STEMI [p<0,001], valvular disease (VD) [p<0,001], cardiogenic shock (CC) [p<0,001], non-sinus rythm (SR) [p<0,001], brain natriuretic peptide (BNP) > 100pg/mL [p= 0,007], left ventricular ejection fraction (LVEF) < 30% [p<0,001] and LVEF <50% [p<0,001]. Using these factors, the authors constructed a Predictive Score to assess ihM risk in patients admitted for ACS with the following formula = 0,505 + (0,582 x Age > 65yo) + (0,323 x STEMI) + (1,803 x VD) + (4,286 x CC) - (0,888 x SR) + (0,141 x BNP>100) + (2,123 x LVEF < 30%) - (0,614 x LVEF > 50%). In this function, variables should be substituted by 1 or 0, depending on wheter the condition they specify is present or not. The optimal discrimination cutoff was 0,96, with a 91,5% sensibility and 59% specificity, and a discriminant power of 90,4%.</p> <p><strong>Conclusion: </strong>The present score is an useful instrument to assess ihM risk in ACS patients, demonstrating a very good discriminant power, based on simple clinical, imaging and laboratory variables. Appliance to clinical contexts will require appropriate validation in a different cohort of ACS patients.</p>
Slides
Our mission: To reduce the burden of cardiovascular disease
Visit our site