The Use of Biomarkers in the Patient with Heart Failure

Chowdhury, P.; Kehl, Devin W.; Choudhary, Rajiv; Maisel, Alan S.

doi:10.1007/s11886-013-0372-4

Cited by 34 publications

(17 citation statements)

References 102 publications

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“…Many cardiac biomarkers which reflect cardiac inflammation and fibrosis may also contribute to the progression of kidney disease. It is plausible that cardiovascular disease (CVD) and chronic kidney disease (CKD) are closely interrelated with each other, and patients with CKD have a strong risk of CVD [115,116]. It is well known that CKD is prevalent in patients with CVD and responsible for approximately half of all CKD-related deaths [26].…”

Section: Cardiovascular Disease and Chronic Kidney Diseasementioning

confidence: 99%

Galectin-3 as a Next-Generation Biomarker for Detecting Early Stage of Various Diseases

et al. 2020

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Galectin-3 is a β-galactoside-binding lectin which is important in numerous biological activities in various organs, including cell proliferation, apoptotic regulation, inflammation, fibrosis, and host defense. Galectin-3 is predominantly located in the cytoplasm and expressed on the cell surface, and then often secreted into biological fluids, like serum and urine. It is also released from injured cells and inflammatory cells under various pathological conditions. Many studies have revealed that galectin-3 plays an important role as a diagnostic or prognostic biomarker for certain types of heart disease, kidney disease, viral infection, autoimmune disease, neurodegenerative disorders, and tumor formation. In particular, it has been recognized that galectin-3 is extremely useful for detecting many of these diseases in their early stages. The purpose of this article is to review and summarize the recent literature focusing on the biomarker characteristics and long-term outcome predictions of galectin-3, in not only patients with various types of diseases, but associated animal models.

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Section: Cardiovascular Disease and Chronic Kidney Diseasementioning

confidence: 99%

Galectin-3 as a Next-Generation Biomarker for Detecting Early Stage of Various Diseases

et al. 2020

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“…According to the estimation of the US Centers for Disease Control and Prevention, the total cost of treatment for HF was up to ≥34 billion in 2010 2. Furthermore, mortality rates in patients with HF were even similar to the 5-year mortality rates of some most severe cancers, which were up to 50% 3…”

Section: Introductionmentioning

confidence: 99%

Prognostic role of copeptin with all-cause mortality after heart failure: a systematic review and meta-analysis

Zhang¹,

Wu²,

Li³

et al. 2017

TCRM

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BackgroundAs the C-terminal section of vasopressin precursor, copeptin has been recently suggested as a new prognostic biomarker after heart failure (HF). Thus, the aim of this study was to evaluate the prognostic value of plasma copeptin level with all-cause mortality in patients with HF.MethodsComprehensive strategies were used to search relevant studies from electronic databases. Pooled hazard ratios (HRs) and standardized mean differences (SMDs) together with their 95% confidence intervals (CIs) were calculated. Subgroup analysis and sensitivity analysis were performed to find the potential sources of heterogeneity.ResultsA total of 5,989 participants from 17 prospective studies were included in this meta-analysis. A significant association was observed between circulating copeptin levels and risk of all-cause mortality in patients with HF (categorical copeptin: HR =1.69, 95% CI =1.42–2.01; per unit copeptin: HR =1.03, 95% CI =1.00–1.07; log unit copeptin: HR =3.26, 95% CI =0.95–11.25). Pooled SMD showed that copeptin levels were significantly higher in patients with HF who died during the follow-up period than in survivors (SMD =1.19, 95% CI =0.81–1.57). Subgroup analyses also confirmed this significant association, while sensitivity analyses indicated that the overall results were stable.ConclusionThis study demonstrated that circulating copeptin seemed to be a novel biomarker to provide better prediction of all-cause mortality in patients with HF.

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“…Biomarkers are among the most promising contemporary tools to improve risk prediction and stratification in patients hospitalized with AHF. Although multiple biomarkers have been proposed for outcome prediction in AHF clinical utility remains limited. Most studies have focused on single biomarkers or small number of selected biomarkers, an approach that fails to address the multitude of complex pathophysiological mechanisms involved in heart failure .…”

Section: Introductionmentioning

confidence: 99%

Optimizing clinical use of biomarkers in high‐risk acute heart failure patients

Demissei

Valente

Cleland

et al. 2015

European J of Heart Fail

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AimThe clinical value of single biomarkers at single time-points to predict outcomes in patients with acute heart failure (AHF) is limited. We performed a multimarker, multi-time-point analysis of biomarkers for the prediction of post-discharge clinical outcomes in high-risk AHF patients. Methods and resultsA set of 48 circulating biomarkers were measured in the PROTECT trial which enrolled 2033 patients with AHF. Associations between baseline levels of biomarkers and outcomes (30-day all-cause mortality, 30-day death or rehospitalization for renal/cardiovascular causes and 180-day all-cause mortality) were evaluated. Prognostic accuracies of baseline, days 2 or 3, 7, and 14 biomarker measurements were estimated and compared utilizing a time-dependent area under the curve (AUC) analysis. Forty-four biomarkers were significantly associated with outcomes, but 42 had limited prognostic value (C-index < 0.70). However, multimarker models combining best-performing biomarkers from different clusters had a much stronger prognostic value. Combining blood urea nitrogen (BUN), chloride, interleukin (IL)-6, cTnI, sST-2 and VEGFR-1 into a clinical model yielded a 11% increase in C-index to 0.84 and 0.78 for 30-day and 180-day all-cause mortality, respectively, and cNRI of 0.86 95% . Prognostic gain was modest for the 30-day death/rehospitalization for cardiovascular or renal causes endpoint. Comparative time-dependent AUC analysis indicated that late measurements provided superior accuracy for the prediction of all-cause mortality over 180 days, with few exceptions including BUN and galectin-3. However, the predictive value of most biomarkers showed a diminishing pattern over time irrespective of moment of measurement.

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The Use of Biomarkers in the Patient with Heart Failure

Cited by 34 publications

References 102 publications

Galectin-3 as a Next-Generation Biomarker for Detecting Early Stage of Various Diseases

Galectin-3 as a Next-Generation Biomarker for Detecting Early Stage of Various Diseases

Prognostic role of copeptin with all-cause mortality after heart failure: a systematic review and meta-analysis

Optimizing clinical use of biomarkers in high‐risk acute heart failure patients

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