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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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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
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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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Validation of a heart failure risk score in a remote monitoring cohort
Session:
Painel 1 -Insuficiencia cardiaca 3
Speaker:
Isabel Cardoso
Congress:
CPC 2020
Topic:
D. Heart Failure
Theme:
10. Chronic Heart Failure
Subtheme:
10.5 Chronic Heart Failure – Prevention
Session Type:
Posters
FP Number:
---
Authors:
Isabel Gonçalves Machado Cardoso; Madalena Coutinho Cruz; Guilherme Portugal; António Valentim Gonçalves; Ana Sofia Delgado; André Grazina; Pedro Silva Cunha; Bruno Tereno Valente; Ana Lousinha; Mário Martins Oliveira; Rui Cruz Ferreira
Abstract
<p>Background:</p> <p>Patients (P) submitted to cardiac ressynchronization therapy (CRT) are at high risk of heart failure (HF) events during follow-up. Continuous analysis of various physiological parameters, as reported by remote monitoring (RM), can contribute to point out incident HF admissions. Tailored evaluation, including multi-parameter modelling, may further increase the accuracy of such algorithms.</p> <p>Aim:</p> <p>Independent external validation of a commercially available algorithm ("Heart Failure Risk Status" HFRS, Medtronic, MN USA) in a cohort submitted to CRT implantation in a tertiary center.</p> <p>Methods:</p> <p>Consecutive P submitted to CRT implantation between January 2013 and September 2019 who had regular RM transmissions were included. The HFRS algorithm includes OptiVol (Medtronic Plc., MN, USA), patient activity, night heart rate (NHR), heart rate variability (HRV), percentage of CRT pacing, atrial tachycardia/atrial fibrillation (AT/AF) burden, ventricular rate during AT/AF (VRAF), and detected arrhythmia episodes/therapy delivered. P were classified as low, medium or high risk. Hospital admissions were systematically assessed by use of a national database ("Plataforma de Dados de Saúde"). Accuracy of the HFRS algorithm was evaluated by random effects logistic regression for the outcome of unplanned hospital admission for HF in the 30 days following each transmission episode.</p> <p>Results:</p> <p>1108 transmissions of 35 CRT P, corresponding to 94 patient-years were assessed. Mean follow-up was 2.7 yrs. At implant, age was 67.6 +/- 9.8 yrs, left ventricular ejection fraction 28 +/-7.8%, BNP 156.6+/- 292.8 and NYHA class>II in 46% of the P. Hospital admissions for HF were observed within 30 days in 9 transmissions. Stepwise increase in HFRS was significantly associated with higher risk of HF admission (odds ratio 12.7, CI 3.2-51.5; graph 1). HFRS had good discrimination for HF events with receiving-operator curve AUC 0.812.</p> <p>Conclusions:</p> <p>HFRS was significantly associated with incident HF admissions in a high-risk cohort. Prospective use of this algorithm may help guide HF therapy in CRT recipients.</p>
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