Alternative Echocardiographic Algorithm for Left Ventricular Filling Pressure in Patients With Heart Failure With Preserved Ejection Fraction.
Journal
The American journal of cardiology
ISSN: 1879-1913
Titre abrégé: Am J Cardiol
Pays: United States
ID NLM: 0207277
Informations de publication
Date de publication:
15 03 2021
15 03 2021
Historique:
received:
12
08
2020
revised:
06
12
2020
accepted:
08
12
2020
pubmed:
29
12
2020
medline:
7
4
2021
entrez:
28
12
2020
Statut:
ppublish
Résumé
The American Society of Echocardiography and/or the European Association of Cardiovascular Imaging recommend a conventional algorithm for estimating left ventricular (LV) filling pressure in heart failure. However, several patients are classed as "indeterminate" due to their LV filling pressures being impossible to calculate. We investigated whether our new echocardiographic algorithm can predict clinical outcomes in patients with heart failure with preserved ejection fraction (HFpEF). We enrolled 754 consecutive patients from the PURSUIT-HFpEF registry. We used the new algorithm to divide them into 2 groups; a normal LV filling pressure group (N group) and a high LV filling pressure group (H group). The H group consisted of 342 patients. Over a mean follow-up of 342 days, 185 patients reached the primary composite end point (157 readmissions for worsening heart failure and 43 cardiovascular deaths). In a multivariable Cox analysis, being in the H group was significantly associated with an increased rate of cardiac events compared with the N group (hazard ratio: 1.71; 95% confidence interval: 1.17 to 2.50, p = 0.006). There were 56 patients (7%) who were assigned to "indeterminate" with the conventional algorithm. Using the new algorithm, we reclassified 16 patients (29%) into the H group and 40 patients (71%) into the N group. The Kaplan-Meier curves showed the reclassified H group had a significantly higher incidence of cardiac events than those assigned to the N group (p < 0.01). In conclusion, the present study demonstrated LV filling pressure assessed by our algorithm can predict clinical outcomes in patients with HFpEF.
Identifiants
pubmed: 33359198
pii: S0002-9149(20)31363-1
doi: 10.1016/j.amjcard.2020.12.035
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
80-88Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.