Validating the HFA‐PEFF score – or how to define a disease?

Coats, Andrew J.S.

doi:10.1002/ejhf.1770

Cited by 4 publications

(6 citation statements)

References 11 publications

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“…These scores, however, are not without controversy, with criticisms ranging from over-simplification of the diagnostic challenges to over-complicating the diagnostic process by requiring expensive tests or the scores largely disagree. 35 , 36 In addition, misclassification has been reported, especially in those patients with low HFpEF scores, potentially due to the fact that both scores use resting parameters in a phenotype in which physiological abnormalities augment during exercise. 33 , 37 Nevertheless, both scores have been shown to have prognostic utility in human patients, 38 , 39 suggesting that they capture key pathophysiologic components that determine outcomes in HFpEF.…”

Section: Hfpef: a Heterogeneous Disease With Multiple Disease Mechanismsmentioning

confidence: 99%

Heart failure with preserved ejection fraction in humans and mice: embracing clinical complexity in mouse models

Withaar

Lam

Schiattarella

et al. 2021

European Heart Journal

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Heart failure (HF) with preserved ejection fraction (HFpEF) is a multifactorial disease accounting for a large and increasing proportion of all clinical HF presentations. As a clinical syndrome, HFpEF is characterized by typical signs and symptoms of HF, a distinct cardiac phenotype and raised natriuretic peptides. Non-cardiac comorbidities frequently co-exist and contribute to the pathophysiology of HFpEF. To date, no therapy has proven to improve outcomes in HFpEF, with drug development hampered, at least partly, by lack of consensus on appropriate standards for pre-clinical HFpEF models. Recently, two clinical algorithms (HFA-PEFF and H2FPEF scores) have been developed to improve and standardize the diagnosis of HFpEF. In this review, we evaluate the translational utility of HFpEF mouse models in the context of these HFpEF scores. We systematically recorded evidence of symptoms and signs of HF or clinical HFpEF features and included several cardiac and extra-cardiac parameters as well as age and sex for each HFpEF mouse model. We found that most of the pre-clinical HFpEF models do not meet the HFpEF clinical criteria, although some multifactorial models resemble human HFpEF to a reasonable extent. We therefore conclude that to optimize the translational value of mouse models to human HFpEF, a novel approach for the development of pre-clinical HFpEF models is needed, taking into account the complex HFpEF pathophysiology in humans.

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Section: Hfpef: a Heterogeneous Disease With Multiple Disease Mechanismsmentioning

confidence: 99%

Heart failure with preserved ejection fraction in humans and mice: embracing clinical complexity in mouse models

Withaar

Lam

Schiattarella

et al. 2021

European Heart Journal

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“…However, we believe that our findings reflect different disease stages which are also influenced by age, but the main age-depended factor influencing both serum biomarkers and cardiac constitutions is atrial fibrillation which was excluded while recruiting the subjects. Therefore, we see the data has representative for theoretical patient trajectory from healthy to suffering from HF ( 16 ).…”

Section: Discussionmentioning

confidence: 73%

CMR detects decreased myocardial deformation in asymptomatic patients at risk for heart failure

Hashemi

Doeblin

Blum

et al. 2023

Front. Cardiovasc. Med.

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AimsThe main management strategy of heart failure with preserved ejection fraction (HFpEF) is prevention since HFpEF is associated with many cardiovascular (CV) risk factors, especially since HFpEF is linked to a high risk for both mortality and recurrent heart failure (HF) hospitalizations. Therefore, there is a need for new tools to identify patients with a high risk profile early. Regional strain assessment by CMR seems to be superior in describing deformation impairment in HF. The MyoHealth score is a promising tool to identify cardiac changes early.Methods and resultsHeart failure patients irrespective of LVEF and asymptomatic controls were recruited, and CMR based measures were obtained. For this analysis the asymptomatic control group (n = 19) was divided into asymptomatic subjects without CV co-morbidities or evidence of cardiac abnormalities and (n = 12) and asymptomatic subjects with CV co-morbidities or evidence of cardiac abnormalities (n = 7) as well as patients with HFpEF (n = 19). We performed CMR scans at rest and during a stress test using isometric handgrip exercise (HG). Assessing the MyoHealth score at rest revealed preserved regional strain in 85 ± 9% of LV segments in controls, 73 ± 11% in at Risk subjects and 73 ± 8% in HFpEF patients. During stress the MyoHealth score was 84 ± 7% in controls, 83 ± 7 in at risk subjects and 74 ± 11 in HFpEF patients.ConclusionIn summary, we show for the first time that asymptomatic subjects with increased CV risk present with HFpEF like impaired myocardial deformation at rest, while they show results like controls under HG stress. The potential of preventive treatment in this group of patients merits further investigation in future.Clinical trial registration[https://drks.de/search/de/trial/DRKS00015615], identifier [DRKS00015615].

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“…Patients suffering from heart failure (HF) account for nearly 1–2% of the adult population in developed countries, rising up to ≥10% among people above 70 years of age with increasing prevalence due to demographic changes 1–4 . Patients suffering from HF with preserved ejection fraction (EF, HFpEF) account for nearly half of the HF population 5 . Despite remarkable progress in HF research, it remained controversial which criteria suffice to diagnose HFpEF additional to a preserved (>50%) left ventricular ejection fraction (LVEF).…”

Section: Introductionmentioning

confidence: 99%

“…HF, like most degenerative diseases, is a ‘numerical disease’, defined by a change in relative function 5 . Whereas ‘categorical diseases’ are defined as the presence or absence of a pathogenic condition, for example, cancer or infections, numerical diseases are not defined by their presence but by the prognostic implications of an altered function 5 . The prognostic implication is either descriptive, a threshold of alteration associated with a worse prognosis, or therapeutic, when an intervention in prespecified setting is associated with an improved prognosis.…”

Section: Introductionmentioning

confidence: 99%

“…Despite remarkable progress in HF research, it remained controversial which criteria suffice to diagnose HFpEF additional to a preserved (>50%) left ventricular ejection fraction (LVEF). HF, like most degenerative diseases, is a ‘numerical disease’, defined by a change in relative function 5 . Whereas ‘categorical diseases’ are defined as the presence or absence of a pathogenic condition, for example, cancer or infections, numerical diseases are not defined by their presence but by the prognostic implications of an altered function 5 .…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the HFA‐PEFF Score: results from the prospective DIAST‐CHF cohort

et al. 2022

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Aims Although the number of patients suffering from heart failure with preserved ejection fraction (HFpEF) increases, the routine diagnosis remains a challenge. In the absence of a pathognomonic sign for HFpEF or specific treatment strategies, a prognosis‐based characterization of suspected patients remains promising for both the risk stratification of the patients and a disease definition. The Heart Failure Association (HFA) of the European Society of Cardiology has introduced an algorithm with different levels of likelihood regarding the diagnosis of HFpEF, the HFA‐PEFF score. We aimed to evaluate the predictive value of this algorithm in a large cohort regarding mortality, symptom burden, and the functional status. Methods and results DIAST‐CHF is a multicentre, population‐based, prospective, observational study in subjects with at least one risk factor for HFpEF between the age of 50 and 85. We calculated the HFA‐PEFF score (n = 1668) and analysed the risk groups for overall mortality, cardiovascular hospitalization, and submaximal functional capacity (6‐min walk distance) at baseline and after a follow‐up period of 10 years. Patients with high HFA‐PEFF score values 5&6 showed a higher mortality than those with an intermediate score (score values 2–4) and low score values (high 21.3% vs. intermediate 10.1% vs. low 4.3%, P < 0.001). Also, the burden of MACE (death, cardiovascular hospitalization, new myocardial infarction, first diagnosis of HF) was increased in the high score values group (high 40.7% vs. intermediate 25.9% vs. low 13.9%, P < 0.001). Similarly, patients with higher scores had higher cumulative incidences of cardiovascular hospitalizations (P = 0.011). Subjects with higher scores also had lower 6‐min walk distance both at baseline and during follow‐up. Conclusions The HFA‐PEFF score provides a reliable instrument to stratify suspected HFpEF patients by their risk for mortality, symptom burden, and functional status in cohort at risk with a follow‐up period of 10 years. As high HFA‐PEFF scores are associated with worse outcome, the HFA‐PEFF algorithm describes a defining approach towards HFpEF.

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Validating the HFA‐PEFF score – or how to define a disease?

Cited by 4 publications

References 11 publications

Heart failure with preserved ejection fraction in humans and mice: embracing clinical complexity in mouse models

Heart failure with preserved ejection fraction in humans and mice: embracing clinical complexity in mouse models

CMR detects decreased myocardial deformation in asymptomatic patients at risk for heart failure

Evaluation of the HFA‐PEFF Score: results from the prospective DIAST‐CHF cohort

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