Comparative symptom biochemistry between moderate and advanced heart failure

Lee, Christopher S.; Denfeld, Quin E.; Aouizerat, Bradley E.; Jurgens, Corrine Y.; Chien, Christopher; Aarons, Emily; Gelow, Jill M.; Hiatt, Shirin O.; Mudd, James O.

doi:10.1016/j.hrtlng.2018.09.002

Cited by 10 publications

(12 citation statements)

References 45 publications

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“…The absence of symptoms also does not necessarily confer the absence of change in underlying pathogenesis, particularly in advanced CVD. 15 Nevertheless, symptoms have relevance in CVD, particularly in acute coronary syndrome (ACS), heart failure (HF), valvular disorders, stroke, rhythm disorders, and peripheral vascular disease.…”

Section: Symptom Traits and Caveats In Cvdmentioning

confidence: 99%

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

Jurgens¹,

Lee²,

Aycock³

et al. 2022

Circulation

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Symptoms of cardiovascular disease drive health care use and are a major contributor to quality of life. Symptoms are of fundamental significance not only to the diagnosis of cardiovascular disease and appraisal of response to medical therapy but also directly to patients’ daily lives. The primary purpose of this scientific statement is to present the state of the science and relevance of symptoms associated with cardiovascular disease. Symptoms as patient-reported outcomes are reviewed in terms of the genesis, manifestation, and similarities or differences between diagnoses. Specifically, symptoms associated with acute coronary syndrome, heart failure, valvular disorders, stroke, rhythm disorders, and peripheral vascular disease are reviewed. Secondary aims include (1) describing symptom measurement methods in research and application in clinical practice and (2) describing the importance of cardiovascular disease symptoms in terms of clinical events and other patient-reported outcomes as applicable.

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Section: Symptom Traits and Caveats In Cvdmentioning

confidence: 99%

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

Jurgens¹,

Lee²,

Aycock³

et al. 2022

Circulation

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“…For example, a cohort study found that increased myocardial stress, systemic inflammation, and endothelial dysfunction were linked to increased physical symptoms (eg, dyspnea, fatigue, and pain) among individuals with moderate HF. 83 Furthermore, highquality research evidence shows that physical symptoms (eg, dyspnea and/or fatigue) can lead to exercise intolerance; this decrease in exercise capacity is a sign of patients with HF and is strongly associated with reduced QoL. 84 In contrast, anxiety symptoms are linked to elevated levels of C-reactive protein, interleukin (IL-1, IL-6), and interferon-γ.…”

Section: Discussionmentioning

confidence: 99%

“…Physiological factors may also play a key role in the association between HF symptoms and adverse outcomes 81 ; some studies have found evidence for links between symptoms and inflammation. For example, a cohort study found that increased myocardial stress, systemic inflammation, and endothelial dysfunction were linked to increased physical symptoms (eg, dyspnea, fatigue, and pain) among individuals with moderate HF 83 . Furthermore, high-quality research evidence shows that physical symptoms (eg, dyspnea and/or fatigue) can lead to exercise intolerance; this decrease in exercise capacity is a sign of patients with HF and is strongly associated with reduced QoL 84 .…”

Section: Methodsmentioning

confidence: 99%

The Heterogeneity of Physical and Anxiety Symptoms and Quality of Life Among Patients With Heart Failure

Mei

Zhang

et al. 2021

J Cardiovasc Nurs

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Background: Patients with heart failure (HF) experience a severe burden of symptoms and reduced quality of life (QoL). However, little is known about the heterogeneity of these symptoms and the association with QoL. Objectives: The aims of this study were to conduct a latent class analysis on co-occurring physical and anxiety symptoms and to determine whether the underlying subgroups differ regarding the QoL among patients with HF. Methods: The authors of this cross-sectional study recruited 329 patients with HF from 2 hospitals. Patients' symptoms and QoL were selfreported, and data were analyzed using latent class analysis, χ 2 test, analysis of variance, and hierarchical linear regression analysis. Results: Three latent classes (all low, all high, and high physical-partial anxiety) were identified based on the occurrence of patients' physical and anxiety symptoms. Patients with a lower body mass index, a worse New York Heart Association class, and a longer disease duration were more likely to belong to the all-high class. Hierarchical linear regression analysis showed that distinct subgroups (all low vs all high: β = −0.299, P < .001; all low vs high physicalpartial anxiety: β = −0.228, P < .001) were significantly associated with the physical summary component score for QoL. Likewise, distinct subgroups (all low vs all high: β = −0.509, P < .001; all low vs high physical-partial anxiety: β = −0.128, P = .012) were significantly associated with the mental summary component score for QoL. Conclusions: Patients with HF showed heterogeneity in physical and anxiety symptoms; the subgroup with severe symptoms exhibited a poor QoL. The associations between symptom subgroups and QoL require targeted symptom-based interventions.

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“…12 This analysis provides insight on how 3 commonly measured biomarkers in HF (NTproBNP, sTNFαR1, and E-selectin) may elucidate a specific group of those with HF who are at higher risk of adverse events associated with HF, such as fluid volume overload and neurohormonal activation. [6][7][8]18 The other 3 biomarkers that were not included in the final model (soluble ST2, adiponectin, and P-selectin) are still of importance to our understating of HF pathogenesis and also were significantly different between classes with medium to large effect sizes. Hence, although our parsimonious approach to modeling entailed using 3 biomarkers, our solution differentiated patients with respect to 6 underlying and intricately related pathogenic mechanisms.…”

Section: Discussionmentioning

confidence: 99%

“…This was a secondary data analysis of 2 studies whose methods have been described elsewhere. [17][18][19] The participants from each study were combined into 1 single cohort for data analysis. All participants had a confirmed HF diagnosis made by physical examination, were at least 21 years of age, did not have a significant hearing or cognitive disability, were able to comprehend fifth grade English, had not had a mechanical circulatory device or heart transplant, and did not have any other terminal disease that would prevent them from participating in the study.…”

Section: Methodsmentioning

confidence: 99%

A Multibiomarker Latent Class Analysis in Moderate to Advanced Heart Failure

2020

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Background: Biomarker science in heart failure (HF) is advancing quickly in our ability to diagnosis and treat patients with this complex syndrome. Researchers are urged to not use single-marker strategies, but instead evaluate biomarkers in patterns to better understand their relationship to one another, as well as disease progression. Latent class mixture modeling allows researchers to determine novel associations between biomarkers. Objective: The objectives of this study were to identify and compare latent classes of cardiovascular biomarkers among patients with moderate to advanced HF. Methods: This was a cross-sectional study of 96 participants with moderate to advanced HF. Latent class mixture modeling was used to identify unique classes of biomarkers and their associations to sociodemographic and clinical variables. Results: The average age of the sample was 54 years, with most of the sample being men (77%) and having an average ejection fraction of 23%. Two unique classes of biomarkers were identified. Latent class 1 had higher levels of all biomarkers, whereas latent class 2 had lower levels. The higher biomarker class had, on average, more neurohormonal activation and fluid retention; however, the higher levels of biomarker class were not more likely to be diagnosed with advanced HF or have more comorbidities. Conclusion: By identifying classes of biomarkers, providers may be better able to identify patients who are at risk of progressing into advanced HF quicker or those who are more likely to have more severe complications, such as fluid overload or renal disease.

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Comparative symptom biochemistry between moderate and advanced heart failure

Cited by 10 publications

References 45 publications

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

The Heterogeneity of Physical and Anxiety Symptoms and Quality of Life Among Patients With Heart Failure

A Multibiomarker Latent Class Analysis in Moderate to Advanced Heart Failure

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