scholarly journals Determinants of submaximal exercise capacity in patients at risk for heart failure with preserved ejection fraction-results from the DIAST-CHF study

2015 ◽  
Vol 2 (2) ◽  
pp. 76-84 ◽  
Author(s):  
Raoul Stahrenberg ◽  
André Duvinage ◽  
Meinhard Mende ◽  
Götz Gelbrich ◽  
Wiebke auf der Heide ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Ejection Fraction ◽  
Exercise Capacity ◽  
Submaximal Exercise ◽  
Preserved Ejection Fraction ◽  
Patients At Risk

scholarly journals Deep learning detects heart failure with preserved ejection fraction using a baseline electrocardiogram

2021 ◽  
Author(s):  
Matthias Unterhuber ◽  
Karl-Philipp Rommel ◽  
Karl-Patrik Kresoja ◽  
Julia Lurz ◽  
Jelena Kornej ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Deep Learning ◽  
Ejection Fraction ◽  
Predictive Value ◽  
Validation Cohort ◽  
External Validation ◽  
Preserved Ejection Fraction ◽  
Derivation Cohort ◽  
Patients At Risk

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a rapidly growing global health problem. To date, diagnosis of HFpEF is based on clinical, invasive and laboratory examinations. Electrocardiographic findings may vary, and there are no known typical ECG features for HFpEF. Methods This study included two patient cohorts. In the derivation cohort, we included n = 1884 patients who presented with exertional dyspnea or equivalent and preserved ejection fraction (≥50%) and clinical suspicion for coronary artery disease. The ECGs were divided in segments, yielding a total of 77.558 samples. We trained a convolutional neural network (CNN) to classify HFpEF and control patients according to ESC criteria. An external group of 203 volunteers in a prospective heart failure screening program served as validation cohort of the CNN. Results The external validation of the CNN yielded an AUC of 0.80 (95% CI 0.74–0.86) for detection of HFpEF according to ESC criteria, with a sensitivity of 0.99 (CI 0.98–0.99) and a specificity of 0.60 (95% CI 0.56–0.64), with a positive predictive value of 0.68 (95%CI 0.64–0.72) and a negative predictive value of 0.98 (95% CI 0.95–0.99). Conclusion In this study, we report the first deep learning-enabled CNN for identifying patients with HFpEF according to ESC criteria including NT-proBNP measurements in the diagnostic algorithm among patients at risk. The suitability of the CNN was validated on an external validation cohort of patients at risk for developing heart failure, showing a convincing screening performance.

scholarly journals The diagnostic and prognostic value of galectin‐3 in patients at risk for heart failure with preserved ejection fraction: results from the DIAST‐CHF study

2021 ◽  
Vol 8 (2) ◽  
pp. 829-841
Author(s):  
Tobias Daniel Trippel ◽  
Meinhard Mende ◽  
Hans‐Dirk Düngen ◽  
Djawid Hashemi ◽  
Johannes Petutschnigg ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Ejection Fraction ◽  
Prognostic Value ◽  
Preserved Ejection Fraction ◽  
Galectin 3 ◽  
Patients At Risk ◽  
Diagnostic And Prognostic Value

P2610Increase in comfortable walking speed during hospitalization predicts the readmission due to decompensated heart failure in heart failure patients with preserved ejection fraction

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Tabata ◽  
M Kato ◽  
N Hamazaki ◽  
T Masuda
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Ejection Fraction ◽  
Exercise Capacity ◽  
Walking Speed ◽  
Decompensated Heart Failure ◽  
Preserved Ejection Fraction ◽  
Functional Classification ◽  
Multivariate Logistic Regression ◽  
Heart Failure Patients

Abstract Background Heart failure patients with preserved ejection fraction (HFpEF) have reduced exercise capacity and poor prognosis as well as those with reduced ejection fraction (HFrEF). Both cardiac function and exercise capacity have been known as prognostic factors for patients with HFrEF. However, few reports documented the relations of comfortable walking speed (CWS) during hospitalization to exercise capacity and prognosis. is used as a clinical measure to assess their exercise capacity and prognosis. However, few reports documented the correlations of CWS with exercise capacity and prognosis in patients with HFpEF. Purpose This study aimed to investigate whether CWS at hospital discharge and the increase in CWS during hospitalization predicted the readmission due to decompensated heart failure in patients with HFpEF and HFrEF. Methods Patients who were hospitalized due to heart failure with New York Heart Association (NYHA) Functional Classification III or IV were prospectively followed up for 3 years after hospital discharge. Consequently, 264 patients, 173 males and 92 females, aged 73.2±6.8 years were studied. Patients were divided into 3 groups based on their ejection fraction (EF): HFpEF group (EF≥50%; n=98), HFrEF group (EF<40%; n=138) and heart failure with mid-range ejection fraction (HFmrEF) group (40%≤EF≤49%; n=28). We assessed clinical characteristics including age, gender, height, NYHA functional classification, etiology of CHF, plasma brain natriuretic peptide and left ventricular ejection fraction (LVEF) on admission, and measured CWS several days after admission and at discharge. We determined significant factors affecting the readmission and their cut-off values using univariate and multivariate logistic regression analyses and the area under the receiver operating characteristics curves in the three groups. Results Forty patients (40.8%), 54 (39.1%) and 6 (21.4%) were readmitted in the HFpEF, HFrEF and HFmrEF groups, respectively, within 3 years after the discharge. Univariate logistic regression analysis detected the age, LVEF, CWS at discharge and the CWS increase during hospitalization as significant limiting factors for readmission in the HFpEF and HFrEF groups (P<0.05, respectively). The multivariate logistic regression analysis detected the CWS increase during hospitalization as significant limiting factor for readmission in the HFpEF and HFrEF groups (P<0.001 and P<0.05, respectively). The odds ratios of readmission were 1.86 (P<0.01) and 1.44 (P<0.001) with each 5-meter decrease of CWS increase during hospitalization and predictive cut-off values of the CWS increase were 7.5 and 8.5 meters/min in the HFpEF and HFrEF groups, respectively. Conclusion This study demonstrated that the CWS increase during hospitalization was a strong predictor for readmission due to decompensated heart failure in patients not only with HFrEF but also with HFpEF and each predictive the cut-off value was 7.5 and 8.5 meters/min.

scholarly journals Fibroblast‐growth‐factor‐23 in heart failure with preserved ejection fraction: relation to exercise capacity and outcomes

2020 ◽  
Vol 7 (6) ◽  
pp. 4089-4099
Author(s):  
Prathap Kanagala ◽  
Jayanth R. Arnold ◽  
Jamal N. Khan ◽  
Anvesha Singh ◽  
Gaurav S. Gulsin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Growth Factor ◽  
Ejection Fraction ◽  
Fibroblast Growth Factor ◽  
Exercise Capacity ◽  
Fibroblast Growth Factor 23 ◽  
Fibroblast Growth ◽  
Preserved Ejection Fraction
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