Personalized Treatment for Heart Failure

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

Deadline for manuscript submissions: 31 July 2026 | Viewed by 2766

Special Issue Editor


E-Mail Website
Guest Editor
Department of Cardiovascular Medicine, Toho University Faculty of Medicine, 6-11-1 Omorinishi, Ota-ku, Tokyo 143-8541, Japan
Interests: heart failure; prevention

Special Issue Information

Dear Colleagues,

Heart failure (HF) is classified into three types based on left ventricular contractility (ejection fraction (EF)). HF-reduced EF has been established to be treated with many cardioprotective medications, including the fantastic four. On the other hand, cardioprotective medications that have evidence of HF mildly reduced EF (HFmrEF) and HF-preserved EF (HFpEF) are sodium/glucose cotransporter 2 inhibitors only, and their treatment is often difficult. However, in an aging society, HFmrEF and HFpEF are on the rise. Therefore, especially in these types of HF, it is also important to suppress their progression to the symptomatic HF stage (stage C HF). Hypertension (HT) is a major cause of decreased cardiac diastolic function in HFpEF, and blood pressure control is possible to suppress symptomatic HF; however, the mechanism behind this is poorly understood.

The aim of this Special Issue is to bring new inspiration to daily clinical practice by discussing the mechanisms that induce HF in patients with HT.

In this Special Issue, we are broadly soliciting reports on epidemiological studies and original research on HT and HF. Reviews are also welcome. We look forward to receiving your contributions.

Dr. Shunsuke Kiuchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hypertension
  • heart failure
  • prevention
  • left ventricular contractility
  • cardiovascular outcomes
  • cardiology

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

12 pages, 546 KB  
Article
Combination of SGLT2 Inhibitors and Loop Diuretics in the Treatment of Heart Failure
by Yoshiki Murakami, Shunsuke Kiuchi, Shinji Hisatake and Takanori Ikeda
J. Pers. Med. 2025, 15(3), 99; https://doi.org/10.3390/jpm15030099 - 3 Mar 2025
Viewed by 1596
Abstract
Background: Administration of SGLT2 inhibitors leads to a reduction in the dosage of loop diuretics in heart failure (HF) patients; however, it is unclear in what patients the dosage can be reduced. We investigated the factors related to the reduction in loop diuretics [...] Read more.
Background: Administration of SGLT2 inhibitors leads to a reduction in the dosage of loop diuretics in heart failure (HF) patients; however, it is unclear in what patients the dosage can be reduced. We investigated the factors related to the reduction in loop diuretics in patients who have started receiving dapagliflozin, an SGLT2 inhibitor. Methods: In total, 126 consecutive patients with HF who received dapagliflozin for HF at our institution between December 2020 and March 2022 were enrolled. We investigated the change in the dosage of diuretics at the time of dapagliflozin administration and after 6 months and evaluated factors at the time of dapagliflozin initiation that were associated with the dosage of loop diuretic reduction. Results: The median of loop diuretics dosage (oral furosemide equivalent) at the time of dapagliflozin administration was 20 mg/day (the mean dosage; 29.5 ± 26.5 mg/day), and after 6 months it decreased to 10 mg/day (the mean dosage; 14.5 ± 15.9 mg/day) (p < 0.001). Multivariate analysis showed that the three factors of in-hospital start of dapagliflozin, % patients on β-blockers, and the dosage of loop diuretics independently predicted the reduction in loop diuretic dosage. Even in analyses excluding patients who initiated dapagliflozin during hospitalization, loop diuretic dosage independently predicted loop diuretic reduction in multivariate analysis. The receiver operating characteristic curve for predicting reduced loop diuretic showed that the cut-off value for loop diuretic at the time of administration of dapagliflozin was 20 mg/day of oral furosemide equivalent. Conclusions: The dosage of loop diuretic used when dapagliflozin was started is a factor that predicts a subsequent reduction in the dose of loop diuretics. Full article
(This article belongs to the Special Issue Personalized Treatment for Heart Failure)
Show Figures

Figure 1

Review

Jump to: Research

21 pages, 360 KB  
Review
Prognostic Models in Heart Failure: Hope or Hype?
by Spyridon Skoularigkis, Christos Kourek, Andrew Xanthopoulos, Alexandros Briasoulis, Vasiliki Androutsopoulou, Dimitrios Magouliotis, Thanos Athanasiou and John Skoularigis
J. Pers. Med. 2025, 15(8), 345; https://doi.org/10.3390/jpm15080345 - 1 Aug 2025
Viewed by 613
Abstract
Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more [...] Read more.
Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article
(This article belongs to the Special Issue Personalized Treatment for Heart Failure)
Back to TopTop