Literature DB >> 31819981

Derivation and validation of a mortality risk prediction model using global longitudinal strain in patients with acute heart failure.

In-Chang Hwang1,2, Goo-Yeong Cho1,2, Hong-Mi Choi3, Yeonyee E Yoon1,2, Jin Joo Park1,2, Jun-Bean Park2,4, Jae-Hyeong Park5, Seung-Pyo Lee2,4, Hyung-Kwan Kim2,4, Yong-Jin Kim2,4, Dae-Won Sohn2,4.   

Abstract

AIMS: To develop a mortality risk prediction model in patients with acute heart failure (AHF), using left ventricular (LV) function parameters with clinical factors. METHODS AND
RESULTS: In total, 4312 patients admitted for AHF were retrospectively identified from three tertiary centres, and echocardiographic parameters including LV ejection fraction (LV-EF) and LV global longitudinal strain (LV-GLS) were measured in a core laboratory. The full set of risk factors was available in 3248 patients. Using Cox proportional hazards model, we developed a mortality risk prediction model in 1859 patients from two centres (derivation cohort) and validated the model in 1389 patients from one centre (validation cohort). During 32 (interquartile range 13-54) months of follow-up, 1285 patients (39.6%) died. Significant predictors for mortality were age, diabetes, diastolic blood pressure, body mass index, natriuretic peptide, glomerular filtration rate, failure to prescribe beta-blockers, failure to prescribe renin-angiotensin system blockers, and LV-GLS; however, LV-EF was not a significant predictor. Final model including these predictors to estimate individual probabilities of mortality had C-statistics of 0.75 [95% confidence interval (CI) 0.73-0.78; P < 0.001] in the derivation cohort and 0.78 (95% CI 0.75-0.80; P < 0.001) in the validation cohort. The prediction model had good performance in both heart failure (HF) with reduced EF, HF with mid-range EF, and HF with preserved EF.
CONCLUSION: We developed a mortality risk prediction model for patients with AHF incorporating LV-GLS as the LV function parameter, and other clinical factors. Our model provides an accurate prediction of mortality and may provide reliable risk stratification in AHF patients. Published on behalf of the European Society of Cardiology. All rights reserved.
© The Author(s) 2019. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  acute heart failure; global longitudinal strain; mortality; prediction model

Mesh:

Year:  2020        PMID: 31819981     DOI: 10.1093/ehjci/jez300

Source DB:  PubMed          Journal:  Eur Heart J Cardiovasc Imaging        ISSN: 2047-2404            Impact factor:   6.875


  4 in total

1.  Body Mass Index, Muscle Mass, and All-Cause Mortality in Patients With Acute Heart Failure: The Obesity Paradox Revisited.

Authors:  In-Chang Hwang; Hong-Mi Choi; Yeonyee E Yoon; Jin Joo Park; Jun-Bean Park; Jae-Hyeong Park; Seung-Pyo Lee; Hyung-Kwan Kim; Yong-Jin Kim; Goo-Yeong Cho
Journal:  Int J Heart Fail       Date:  2022-04-04

2.  Reverse remodelling by sacubitril/valsartan predicts the prognosis in heart failure with reduced ejection fraction.

Authors:  Mi-Gil Moon; In-Chang Hwang; Wonsuk Choi; Goo-Yeong Cho; Yeonyee E Yoon; Jun-Bean Park; Seung-Pyo Lee; Hyung-Kwan Kim; Yong-Jin Kim
Journal:  ESC Heart Fail       Date:  2021-03-07

3.  Global longitudinal strain for prediction of ventricular arrhythmia in patients with heart failure.

Authors:  Mohammad Hossein Nikoo; Razieh Naeemi; Alireza Moaref; Armin Attar
Journal:  ESC Heart Fail       Date:  2020-07-25

4.  Expected and observed in-hospital mortality in heart failure patients before and during the COVID-19 pandemic: Introduction of the machine learning-based standardized mortality ratio at Helios hospitals.

Authors:  Sebastian König; Vincent Pellissier; Johannes Leiner; Sven Hohenstein; Laura Ueberham; Andreas Meier-Hellmann; Ralf Kuhlen; Gerhard Hindricks; Andreas Bollmann
Journal:  Clin Cardiol       Date:  2021-12-23       Impact factor: 2.882

  4 in total

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