Physiopathology and Diagnosis of Congestive Heart Failure: Consolidated Certainties and New Perspectives

Franca, Eluisa La; Manno, Girolamo; Ajello, Laura; Gesaro, Gabriele Di; Minà, Chiara; Visconti, Claudia; Bellavia, Diego; Falletta, Calogero; Romano, Giuseppe; Oglio, Sonia Dell'; Licata, Pamela; Caronia, Alessandra; Gallo, Michele; Clemenza, Francesco

doi:10.1016/j.cpcardiol.2020.100691

Cited by 11 publications

(4 citation statements)

References 48 publications

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“…This study recognised respiratory rate as a risk factor for AHF in patients with AF, similar to the results in some previous studies [37]. Input and output volumes are important for evaluating the degree of heart failure [38,39]; reductions in output and input are termed fluid management. Our model 1 showed that greater fluid management increases the risk of AHF.…”

Section: Discussionsupporting

confidence: 83%

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Wu,

Qiao,

Yan

et al. 2023

Preprint

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AimThis study developed two nomograms to predict the incidence of acute heart failure (AHF) in patients of atrial fibrillation (AF) and evaluated the predictive value of the nomograms.Method18179 patients of AF from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analysed. The patients were randomly divided into two groups in a seven-to-three ratio to form a training cohort (n = 12725) and a validation cohort (n = 5454). Least absolute shrinkage and selection operator (LASSO) regression analyses were used to identify associated risk variables. Two nomograms were established to predict the rate of AHF in patients of AF for use by patients and clinicians, respectively. The new models were assessed in terms of the concordance index (C-index), the area under the curve (AUC) of receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA).ResultsLeast absolute shrinkage and selection operator (LASSO) regression analysis identified seven potential predictors of acute heart failure in nomogram 1 and three potential predictors in nomogram 2. Multivariate logistic regression analysis was used to evaluate the effects of these predictors and create final models. The concordance index values were 0.768 and 0.696, respectively. The areas under the curves for the training and validation sets in nomogram 1 were 0.768 and 0.763, respectively. The areas under the curves for the training and validation sets in nomogram 2 were 0.696 and 0.692, respectively.ConclusionThe age, respiratory rate, fluid management, mean corpuscular hemoglobin concentration (MCHC), bicarbonate, blood urea nitrogen (BUN) and chloride were identified as predictors of the development of acute heart failure in patients with atrial fibrillation in nomogram 1. The charlson score, lods score and sapsII score were identified as predictors of the development of acute heart failure in nomogram 2. Our nomograms are reliable convenient approaches for predicting acute heart failure in patients with atrial fibrillation.

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Section: Discussionsupporting

confidence: 83%

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Wu,

Qiao,

Yan

et al. 2023

Preprint

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“…Heart failure is a progressive and largely intractable clinical syndrome characterized by an overall decline in the pumping function of the heart. Heart failure can be subdivided clinically into heart failure with persevered ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) (4)(5)(6). HFpEF is just as common as HFrEF and results from poor myocardial muscle relaxation leading to inadequate filling and increased pressures in the left ventricular (LV) chamber, indicating marked diastolic dysfunction (7).…”

Section: Introductionmentioning

confidence: 99%

Myofilament-based physiological regulatory compensation preserves diastolic function in failing hearts with severe Ca2+ handling deficits

Heinis,

Thompson,

Gulati

et al. 2024

JCI Insight

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Severe dysfunction in cardiac muscle intracellular Ca 2+ handling is a common pathway underlying heart failure. Here we used an inducible genetic model of severe Ca 2+ cycling dysfunction by the targeted temporal gene ablation of the cardiac Ca 2+ ATPase, SERCA2, in otherwise normal adult mice. In this model, in vivo heart performance was minimally affected initially, even though Serca2a protein was markedly reduced. The mechanism underlying the sustained in vivo heart performance in the weeks prior to complete heart pump failure and death is not clear and is important to understand. Studies were primarily focused on understanding how in vivo diastolic function could be relatively normal under conditions of marked Serca2a deficiency. Interestingly, data show increased cardiac troponin I (cTnI) serine 23/24 phosphorylation content in hearts upon Serca2a ablation in vivo. We report that hearts isolated from the Serca2-deficient mice retained near normal heart pump functional responses to β-adrenergic stimulation. Unexpectedly, using genetic complementation models, in concert with inducible Serca2 ablation, data show that Serca2a-deficient hearts that also lacked the central β-adrenergic signaling–dependent Serca2a negative regulator, phospholamban (PLN), had severe diastolic dysfunction that could still be corrected by β-adrenergic stimulation. Notably, integrating a serines 23/24–to–alanine PKA-refractory sarcomere incorporated cTnI molecular switch complex in mice deficient in Serca2 showed blunting of β-adrenergic stimulation–mediated enhanced diastolic heart performance. Taken together, these data provide evidence of a compensatory regulatory role of the myofilaments as a critical physiological bridging mechanism to aid in preserving heart diastolic performance in failing hearts with severe Ca 2+ handling deficits.

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“…In view of the great burden of chronic HF to society, we need a deeper understanding of its pathophysiological mechanism, not only in terms of mortality but also in terms of the incidence rate related to repeated and long-term hospitalization, which merits accelerated research ( 3 ). The occurrence of HF is associated with cardiovascular aging ( 4 ), and risk factors include old age, hypertension, diabetes, dyslipidemia, obesity ( 5 ), volume overload, fluid congestion, hereditary cardiomyopathy, etc ( 6 ). Based on the ongoing exploration of the pathophysiological mechanisms of HF and the publication of clinical evidence-based research, inflammation and immunity, including autoimmune and infection-mediated mechanisms, are now considered other possible mechanisms of HF ( 7 – 9 ).…”

Section: Introductionmentioning

confidence: 99%

Identification CCL2,CXCR2,S100A9 of the immune-related gene markers and immune infiltration characteristics of inflammatory bowel disease and heart failure via bioinformatics analysis and machine learning

Luo,

Wang,

Zhang

et al. 2023

Front. Cardiovasc. Med.

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BackgroundRecently, heart failure (HF) and inflammatory bowel disease (IBD) have been considered to be related diseases with increasing incidence rates; both diseases are related to immunity. This study aims to analyze and identify immune-related gene (IRG) markers of HF and IBD through bioinformatics and machine learning (ML) methods and to explore their immune infiltration characteristics.MethodsThis study used gene expressiondata (GSE120895, GSE21610, GSE4183) from the Gene Expression Omnibus (GEO) database to screen differentially expressed genes (DEGs) and compare them with IRGs from the ImmPort database to obtain differentially expressed immune-related genes (DIRGs). Functional enrichment analysis of IRGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, three machine models and protein–protein interactions (PPIs) were established to identify diagnostic biomarkers. The receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic value of the candidate biomarkersin the validation set (GSE1145, GSE36807) and obtain their correlations with immune cells through the Spearman algorithm. Finally, the CIBERSORT algorithm was used to evaluate the immune cell infiltration of the two diseases.ResultsThirty-four DIRGs were screened and GO and KEGG analysis results showed that these genes are mainly related to inflammatory and immune responses. CCL2, CXCR2 and S100A9 were identified as biomarkers.The immune correlation results indicated in both diseases that CCL2 is positively correlated with mast cell activation, CXCR2 is positively correlated with neutrophils and S100A9 is positively correlated with neutrophils and mast cell activation. Analysis of immune characteristics showed that macrophages M2, macrophages M0 and neutrophils were present in both diseases.ConclusionsCCL2, CXCR2 and S100A9 are promising biomarkers that will become potential immunogenetic biomarkers for diagnosing comorbidities of HF and IBD. macrophages M2, macrophages M0, neutrophil-mediated inflammation and immune regulation play important roles in the development of HF and IBD and may become diagnostic and therapeutic targets.

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Physiopathology and Diagnosis of Congestive Heart Failure: Consolidated Certainties and New Perspectives

Cited by 11 publications

References 48 publications

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Myofilament-based physiological regulatory compensation preserves diastolic function in failing hearts with severe Ca2+ handling deficits

Identification CCL2,CXCR2,S100A9 of the immune-related gene markers and immune infiltration characteristics of inflammatory bowel disease and heart failure via bioinformatics analysis and machine learning

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