Moderated Posters session: diastolic function in clinical perspectiveP1260Coronary flow reserve in patients with chest pain but without significant coronary stenosis: the role of hypertensionP1261Diastolic bicycle exercise: normal reference values and determinantsP1262Prediction of left ventricular diastolic dysfunction in breast cancer patients after chemotherapyP1263Impaired diastolic recovery is associated with adverse events in the patients with hypertensive heart failureP1264Diastolic …
Author(s) -
Fang Fang,
Ciro Santoro,
K Hristova,
HJ Yoon,
L Abid,
A Poller,
Tamás Erdei,
Tausif Ahmed Rajput,
B Geraeli,
R Gascuena,
YiJu Li,
Ji Hyun Yang,
Thomas Bartel,
Raimund Erbel,
Ya Ye,
CM Yu,
V. Schiano Lomoriello,
Roberta Esposito,
L Casaretti,
Federica Ilardi,
Valeria Fazio,
Giovanni de Simone,
Bruno Trimarco,
Maurizio Galderisi,
R Marinov,
TZ Katova,
V. Kostova,
Iana Simova,
KH Kim,
JY Cho,
Park Jc,
S Ben Kahla,
O Bech-Hanssen,
Imran Sunderji,
Sergio SanchezMartinez,
James Edwards,
D. Braim,
Christopher Price,
B Bijnens,
AG Fraser,
LA Mohmed,
Badr Abdel-Hady,
M Abdellaha,
Adel A. Mazen,
Roya Sattarzadeh Badkoubeh,
HR Hassanbeigy,
Anahita Tavoosi,
Farnoosh Larti,
Kianoush Saberi,
Lorenzo Fácila,
Belén Terol,
Claudia GonzalezRico
Publication year - 2015
Publication title -
european heart journal - cardiovascular imaging
Language(s) - English
Resource type - Journals
eISSN - 2047-2412
pISSN - 2047-2404
DOI - 10.1093/ehjci/jev271
Subject(s) - session (web analytics) , cardiology , medicine , chest pain , stenosis , diastole , diastolic function , physical therapy , blood pressure , computer science , world wide web
International audienceBackground: The complexity of the heart failure with preserved ejection fraction (HFPEF) syndrome makes that the best approach towards diagnosis is still not fully established. According to recent studies stress echocardiography may be useful to improve the diagnosis, but its exact place in clinical practice is still unproven.Methods: Tissue Doppler velocity traces were acquired from 55 subjects at rest and during submaximal exercise (semi- supine bicycle) at the basal septum and lateral wall, and temporally aligned to a common reference for comparison. This population consisted of 19 HFPEF patients (diagnosed by the HFA of ESC criteria), 14 controls with unexplained breathlessness (EF>50%, did not fulfill HFA criteria) and 22 healthy controls. Each stage of the stress protocol was independently analyzed by an unsupervised machine learning algorithm that spread the data according to their most relevant characteristics.Results: The use of exercise data resulted in a better separation of healthy controls and HFPEF subjects than using rest data (spec=86.3% vs. spec=81.8% while the sensitivity does not substantially change). Notably, the stress protocol identified critical breathless subjects, which during exercise get close to the HFPEF subgroup while they were not differentiated from controls at rest (p-value in the figure).Conclusion: The characterization of HFPEF is significantly improved by analyzing velocities acquired during exercise. The method has strong clinical potential to identify critical breathless subjects at an early stage
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