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Review
. 2022 Feb;191(1):213-227.
doi: 10.1007/s11845-020-02477-z. Epub 2021 Feb 17.

Role of confirmed and potential predictors of an unfavorable outcome in heart failure in everyday clinical practice

Affiliations
Review

Role of confirmed and potential predictors of an unfavorable outcome in heart failure in everyday clinical practice

Anna Chuda et al. Ir J Med Sci. 2022 Feb.

Abstract

Heart failure (HF) is the only cardiovascular disease with an ever increasing incidence. HF, through reduced functional capacity, frequent exacerbations of disease, and repeated hospitalizations, results in poorer quality of life, decreased work productivity, and significantly increased costs of the public health system. The main challenge in the treatment of HF is the availability of reliable prognostic models that would allow patients and doctors to develop realistic expectations about the prognosis and to choose the appropriate therapy and monitoring method. At this moment, there is a lack of universal parameters or scales on the basis of which we could easily capture the moment of deterioration of HF patients' condition. Hence, it is crucial to identify such factors which at the same time will be widely available, cheap, and easy to use. We can find many studies showing different predictors of unfavorable outcome in HF patients: thorough assessment with echocardiography imaging, exercise testing (e.g., 6-min walk test, cardiopulmonary exercise testing), and biomarkers (e.g., N-terminal pro-brain type natriuretic peptide, high-sensitivity troponin T, galectin-3, high-sensitivity C-reactive protein). Some of them are very promising, but more research is needed to create a specific panel on the basis of which we will be able to assess HF patients. At this moment despite identification of many markers of adverse outcomes, clinical decision-making in HF is still predominantly based on a few basic parameters, such as the presence of HF symptoms (NYHA class), left ventricular ejection fraction, and QRS complex duration and morphology.

Keywords: Biomarker(s); Heart failure; Prognosis; Risk factor(s); Risk models; Risk prediction.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Pathophysiological interplay between AF-HF cycle and HF–AF cycle (according to [18], modified). Abbreviations: DT, deceleration time of the E-wave; GLS, global longitudinal strain; LA, left atrial; LV, left ventricular; LVEF, left ventricular ejection fraction; RV, right ventricle; TAPSE, tricuspid annular plane systolic excursion; TDI, tissue Doppler imaging
Fig. 2
Fig. 2
Reference value for the 6MWT distance corrected by anthropometric variables in a group of healthy subjects (according to [99, 104], modified). Abbreviations: BMI, body mass index
Fig. 3
Fig. 3
Selected risk models for the assessment of prognosis in heart failure

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