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A. Basics
B. Imaging
C. Arrhythmias and Device Therapy
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01. History of Cardiology
02. Clinical Skills
03. Imaging
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05. Atrial Fibrillation
06. Supraventricular Tachycardia (non-AF)
07. Syncope and Bradycardia
08. Ventricular Arrhythmias and Sudden Cardiac Death (SCD)
09. Device Therapy
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20. Congenital Heart Disease and Pediatric Cardiology
21. Pulmonary Circulation, Pulmonary Embolism, Right Heart Failure
22. Aortic Disease
23. Peripheral Vascular and Cerebrovascular Disease
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25. Interventional Cardiology
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28. Risk Factors and Prevention
29. Rehabilitation and Sports Cardiology
30. Cardiovascular Disease in Special Populations
31. Pharmacology and Pharmacotherapy
32. Cardiovascular Nursing
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34. Public Health and Health Economics
35. Research Methodology
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Predicting non-invasive ventilation failure in acute heart failure patients presenting in the emergency department
Session:
Painel 1 - Insuficiência Cardíaca 9
Speaker:
Daniel Faria
Congress:
CPC 2020
Topic:
D. Heart Failure
Theme:
11. Acute Heart Failure
Subtheme:
11.2 Acute Heart Failure – Epidemiology, Prognosis, Outcome
Session Type:
Posters
FP Number:
---
Authors:
Daniel Candeias Faria; David Cabrita Roque; João Baltazar Ferreira; Marco Beringuilho; Inês Fialho; João Bicho Augusto; Ana Oliveira Soares; Carlos Sequeira De Morais
Abstract
<p>Background: The majority of patients with acute heart failure (AHF) present with some degree of respiratory insufficiency due to pulmonary congestion. Non-invasive ventilation can avoid the need for invasive mechanical ventilation (IMV) in some settings. However, it can also delay the time to orotracheal intubation and IMV, which worsens the short-term prognosis. <br /> <br /> Purpose: To provide a sumple and easy-to-perfom score base on clinical and analytical parameters quickly obtainable at admission and to access its performance to predict NIV failure. <br /> <br /> Methods: In a retrospective, observational, single-center study, a total of 516 patients were admitted for AHF in the emergency room of a large urban hospital. All patients had data collected regarding demographics, clinical and laboratorial markers at admission. We followed-up patients to access NIV failure and in-hospital mortality. Multivariate analysis was performed to identify predictors of NIV failure. Discriminative power was accessed by receiver operating characteristic (ROC) curve. <br /> <br /> Results: A total of 516 patients were included in the final analysis. Of those, 134 patients (25.9%) were treated with NIV and 16 of those (11.9%) had NIV failure with progression to IMV. In-hospital mortality was 8.9% (n=46). Univariate and multivariate analysis are illustrated in Table 1.Stratified analysis was based on the approximate cut-off value for the last quartile. Based on the similar beta coefficient values for each variable, we attributed 1 point in the presence of each following conditions: arterial lactate concentration>2.5 mmol/L, PaO2/FiO2<250, blood pH<7.30, heart rate >140 bpm, with a total score range 0-4. Our model yielded a good performance in predicting NIV failure using ROC analysis (AUC 0.802, 95% CI, 0.754-0.833, p<0.001). A score of 1 or above had a sensitivity of 94% and a specificity of 53% in predicting NIV failure. <br /> <br /> Conclusions: Our predictive model proved to be a simple and accessible tool with good to predict NIV failure in patients admitted for AHF.</p>
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