Tailoring Treatment with Biomarkers: Advancements in Heart Failure Management

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Disease Biomarker".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 1850

Special Issue Editors


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Guest Editor
Department of Cardiology, University Hospital of Larissa, Larissa, Greece
Interests: interventional cardiology; heart failure; pulmonary hypertension; echocardiography; amyloidosis; devices; arterial hypertension

E-Mail Website
Guest Editor
Department of Cardiology, University Hospital of Larissa, Larissa, Greece
Interests: heart failure; acute heart failure; chronic heart failure; LVAD; heart transplantation; amyloidosis; devices; pulmonary hypertension
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Special Issue Information

Dear Colleagues,

In recent years, the integration of biomarkers into clinical practice has revolutionized our approach to understanding, diagnosing, and managing heart failure. The nuanced insights provided by biomarkers offer a personalized avenue for optimizing therapeutic interventions, ushering in a new era of precision medicine in cardiac care. The multifaceted nature of heart failure demands a tailored approach, acknowledging the inherent heterogeneity among patients. Biomarkers serve as indispensable tools, offering a deeper understanding of disease pathophysiology and aiding clinicians in navigating the complexities of individual patient profiles. This Special Issue focuses on the role of biomarkers in heart failure diagnosis, prognosis, and treatment.

We invite researchers to submit original studies, as well as systematic reviews. State-of-the-art narrative reviews will also be considered for publication.

Prof. Dr. John S. Skoularigis
Dr. Andrew Xanthopoulos
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • biomarkers
  • heart failure
  • precision cardiology
  • risk prediction
  • outcomes
  • treatment

Published Papers (2 papers)

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Research

13 pages, 549 KiB  
Article
Age Is a Predictor of In-Hospital Outcomes for Left Ventricular Assist Device Implantation: A Nationwide Analysis
by Abdul Rahman Akkawi, Akira Yamaguchi, Junichi Shimamura, Omar Chehab, Paulino Alvarez, Toshiki Kuno and Alexandros Briasoulis
J. Pers. Med. 2024, 14(3), 236; https://doi.org/10.3390/jpm14030236 - 22 Feb 2024
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Abstract
The 2018 heart allocation system has significantly influenced heart transplantation and left ventricular assist device (LVAD) utilization. Our study aims to investigate age-related outcomes following LVAD implantation in the post-allocation era. Using the National Inpatient Sample, we analyzed data from 7375 patients who [...] Read more.
The 2018 heart allocation system has significantly influenced heart transplantation and left ventricular assist device (LVAD) utilization. Our study aims to investigate age-related outcomes following LVAD implantation in the post-allocation era. Using the National Inpatient Sample, we analyzed data from 7375 patients who underwent LVAD implantation between 2019 and 2020. The primary endpoint was in-hospital mortality following LVAD implantation, stratified by age categories. The age groups were 18–49, 50–59, 60–69, and over 70. These represented 26%, 26%, 31%, and 17% of patients, respectively. Patients aged 60–69 and those over 70 exhibited higher in-hospital mortality rates of 12% and 17%, respectively, compared to younger age groups (7% for 18–49 and 6% for 50–59). The age groups 60–69 and over 70 were independent predictors of mortality, with adjusted odds ratios of 1.99 (p = 0.02; 95% confidence interval [CI], 1.12–3.57) and 2.88 (p = 0.002; 95% CI, 1.45–5.71), respectively. Additionally, a higher Charlson Comorbidity Index was associated with increased in-hospital mortality risk (adjusted odds ratio 1.39; p = 0.02; 95% CI, 1.05–1.84). Additionally, patients above 70 experienced a statistically shorter length of stay. Nonhome discharge was found to be significantly high across all age categories. However, the difference in hospitalization cost was not statistically significant across the age groups. Our study highlights that patients aged 60 and above face an increased risk of in-hospital mortality following LVAD implantation in the post-allocation era. This study sheds light on age-related outcomes and emphasizes the importance of considering age in LVAD patient selection and management strategies. Full article
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14 pages, 1579 KiB  
Article
Analysis of the Larissa Heart Failure Risk Score: Predictive Value in 9207 Patients Hospitalized for Heart Failure from a Single Center
by Andrew Xanthopoulos, John Skoularigis, Alexandros Briasoulis, Dimitrios E. Magouliotis, Alex Zajichek, Alex Milinovich, Michael W. Kattan, Filippos Triposkiadis and Randall C. Starling
J. Pers. Med. 2023, 13(12), 1721; https://doi.org/10.3390/jpm13121721 - 17 Dec 2023
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Abstract
Early risk stratification is of outmost clinical importance in hospitalized patients with heart failure (HHF). We examined the predictive value of the Larissa Heart Failure Risk Score (LHFRS) in a large population of HHF patients from the Cleveland Clinic. A total of 13,309 [...] Read more.
Early risk stratification is of outmost clinical importance in hospitalized patients with heart failure (HHF). We examined the predictive value of the Larissa Heart Failure Risk Score (LHFRS) in a large population of HHF patients from the Cleveland Clinic. A total of 13,309 admissions for heart failure (HF) from 9207 unique patients were extracted from the Cleveland Clinic’s electronic health record system. For each admission, components of the 3-variable simple LHFRS were obtained, including hypertension history, myocardial infarction history, and red blood cell distribution width (RDW) ≥ 15%. The primary outcome was a HF readmission and/or all-cause mortality at one year, and the secondary outcome was all-cause mortality at one year of discharge. For both outcomes, all variables were statistically significant, and the Kaplan–Meier curves were well-separated and in a consistent order (Log-rank test p-value < 0.001). Higher LHFRS values were found to be strongly related to patients experiencing an event, showing a clear association of LHFRS with this study outcomes. The bootstrapped-validated area under the curve (AUC) for the logistic regression model for each outcome revealed a C-index of 0.64 both for the primary and secondary outcomes, respectively. LHFRS is a simple risk model and can be utilized as a basis for risk stratification in patients hospitalized for HF. Full article
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