The Problem of Ventricular Dysrhythmias and Sudden Death Mortality in Heart Failure: The Impact of Current Therapy

Cardiology ◽  
2000 ◽  
Vol 93 (1-2) ◽  
pp. 56-69 ◽  
Author(s):  
Carl V. Leier ◽  
Rene J. Alvarez ◽  
Philip F. Binkley
Keyword(s):  
Heart Failure ◽  
Sudden Death ◽  
Current Therapy ◽  
Ventricular Dysrhythmias ◽  
The Impact

What is the impact of depressive and anxious symptoms on quality of life in veterans with heart failure?

2010 ◽  
Author(s):  
J. A. Cully ◽  
L. L. Phillips ◽  
M. E. Kunik ◽  
M. A. Stanley ◽  
A. Deswal
Keyword(s):  
Quality Of Life ◽  
Heart Failure ◽  
The Impact

Artificial Intelligence as a Business Partner in Cardiovascular Precision Medicine: an Emerging Approach for Disease Detection and Treatment Optimization

2020 ◽  
Vol 28 ◽  
Author(s):  
Valeria Visco ◽  
Germano Junior Ferruzzi ◽  
Federico Nicastro ◽  
Nicola Virtuoso ◽  
Albino Carrizzo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Heart Failure ◽  
Atrial Fibrillation ◽  
Precision Medicine ◽  
Clinical Decision Making ◽  
Disease Detection ◽  
Physician Patient Relationship ◽  
Invasive Approach ◽  
Tailored Treatment ◽  
The Impact

Background: In the real world, medical practice is changing hand in hand with the development of new Artificial Intelligence (AI) systems and problems from different areas have been successfully solved using AI algorithms. Specifically, the use of AI techniques in setting up or building precision medicine is significant in terms of the accuracy of disease discovery and tailored treatment. Moreover, with the use of technology, clinical personnel can deliver a very much efficient healthcare service. Objective: This article reviews AI state-of-the-art in cardiovascular disease management, focusing on diagnostic and therapeutic improvements. Methods: To that end, we conducted a detailed PubMed search on AI application from distinct areas of cardiology: heart failure, arterial hypertension, atrial fibrillation, syncope and cardiovascular rehabilitation. Particularly, to assess the impact of these technologies in clinical decision-making, this research considers technical and medical aspects. Results: On one hand, some devices in heart failure, atrial fibrillation and cardiac rehabilitation represent an inexpensive, not invasive or not very invasive approach to long-term surveillance and management in these areas. On the other hand, the availability of large datasets (big data) is a useful tool to predict the development and outcome of many cardiovascular diseases. In summary, with this new guided therapy, the physician can supply prompt, individualised, and tailored treatment and the patients feel safe as they are continuously monitored, with a significant psychological effect. Conclusion: Soon, tailored patient care via telemonitoring can improve the clinical practice because AI-based systems support cardiologists in daily medical activities, improving disease detection and treatment. However, the physician-patient relationship remains a pivotal step.

scholarly journals Biomarkers-based personalized follow-up in chronic heart failure improves patient’s outcomes and reduces care associate cost

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Antonio Leon-Justel ◽  
Jose I. Morgado Garcia-Polavieja ◽  
Ana Isabel Alvarez-Rios ◽  
Francisco Jose Caro Fernandez ◽  
Pedro Agustin Pajaro Merino ◽  
...  
Keyword(s):  
Heart Failure ◽  
Hospital Admissions ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Secondary Outcome ◽  
Ventricular Ejection Fraction ◽  
Number Of Patients ◽  
Ed Visits ◽  
The Impact

Abstract Background Heart failure (HF) is a major and growing medical and economic problem, with high prevalence and incidence rates worldwide. Cardiac Biomarker is emerging as a novel tool for improving management of patients with HF with a reduced left ventricular ejection fraction (HFrEF). Methods This is a before and after interventional study, that assesses the impact of a personalized follow-up procedure for HF on patient’s outcomes and care associated cost, based on a clinical model of risk stratification and personalized management according to that risk. A total of 192 patients were enrolled and studied before the intervention and again after the intervention. The primary objective was the rate of readmissions, due to a HF. Secondary outcome compared the rate of ED visits and quality of life improvement assessed by the number of patients who had reduced NYHA score. A cost-analysis was also performed on these data. Results Admission rates significantly decreased by 19.8% after the intervention (from 30.2 to 10.4), the total hospital admissions were reduced by 32 (from 78 to 46) and the total length of stay was reduced by 7 days (from 15 to 9 days). The rate of ED visits was reduced by 44% (from 64 to 20). Thirty-one percent of patients had an improved functional class score after the intervention, whereas only 7.8% got worse. The overall cost saving associated with the intervention was € 72,769 per patient (from € 201,189 to € 128,420) and €139,717.65 for the whole group over 1 year. Conclusions A personalized follow-up of HF patients led to important outcome benefits and resulted in cost savings, mainly due to the reduction of patient hospitalization readmissions and a significant reduction of care-associated costs, suggesting that greater attention should be given to this high-risk cohort to minimize the risk of hospitalization readmissions.

scholarly journals Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Rameen Shakur ◽  
Juan Pablo Ochoa ◽  
Alan J. Robinson ◽  
Abhishek Niroula ◽  
Aneesh Chandran ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systems Biology ◽  
Sudden Cardiac Death ◽  
Risk Stratification ◽  
Clinical Data ◽  
Cardiac Death ◽  
Troponin T ◽  
Management Options ◽  
Familial Cardiomyopathy ◽  
The Impact

AbstractThe cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk stratification measures for the management of patients with a family history of sudden cardiac death or familial cardiomyopathy. Given the disparity in patient outcomes and therapy options, we investigated the impact of variations on the intermolecular interactions across the thin filament complex as an example of an unbiased systems biology method to better define clinical prognosis to aid future management options. We present a novel unbiased dynamic model to define and analyse the functional, structural and physico-chemical consequences of genetic variations among the troponins. This was subsequently integrated with clinical data from accessible global multi-centre systematic reviews of familial cardiomyopathy cases from 106 articles of the literature: 136 disease-causing variations pertaining to 981 global clinical cases. Troponin T variations showed distinct pathogenic hotspots for dilated and hypertrophic cardiomyopathies; considering the causes of cardiovascular death separately, there was a worse survival in terms of sudden cardiac death for patients with a variation at regions 90–129 and 130–179 when compared to amino acids 1–89 and 200–288. Our data support variations among 90–130 as being a hotspot for sudden cardiac death and the region 131–179 for heart failure death/transplantation outcomes wherein the most common phenotype was dilated cardiomyopathy. Survival analysis into regions of high risk (regions 90–129 and 130–180) and low risk (regions 1–89 and 200–288) was significant for sudden cardiac death (p = 0.011) and for heart failure death/transplant (p = 0.028). Our integrative genomic, structural, model from genotype to clinical data integration has implications for enhancing clinical genomics methodologies to improve risk stratification.

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