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Introduction: Cardiac Resynchronization Therapy (CRT) is an effective treatment for heart failure (HF) in approximately two-thirds of recipients, with a third remaining CRT 'non-responders.' There is an increasing body of evidence exploring the reasons behind non-response, as well as ways to preempt or counteract it.
Areas Covered: This review will examine the most recent evidence regarding optimizing outcomes from CRT, as well as explore whether traditional CRT indeed remains the best first-line therapy for electrical resynchronization in HF. We will start by discussing methods of preempting non-response, such as refining patient selection and procedural technique, before reviewing how responses can be optimized post-implantation. For the purpose of this review, evidence was gathered from electronic literature searches (via PubMed and GoogleScholar), with a particular focus on primary evidence published in the last 5 years.
Expert Opinion: Ever-expanding research in the field of device therapy has armed physicians with more tools than ever to treat dyssynchronous HF. Newer developments, such as artificial intelligence (AI) guided device programming and conduction system pacing (CSP) are particularly exciting, and we will discuss how they could eventually lead to truly personalized care by maximizing outcomes from CRT.
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http://dx.doi.org/10.1080/14779072.2024.2445246 | DOI Listing |
JAMA Dermatol
September 2025
Department of Population Health, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
Importance: Increasingly, strategies to systematically detect melanomas invoke targeted approaches, whereby those at highest risk are prioritized for skin screening. Many tools exist to predict future melanoma risk, but most have limited accuracy and are potentially biased.
Objectives: To develop an improved melanoma risk prediction tool for invasive melanoma.
JAMA Netw Open
September 2025
Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla.
Importance: Janus kinase (JAK) inhibitors are highly effective medications for several immune-mediated inflammatory diseases (IMIDs). However, safety concerns have led to regulatory restrictions.
Objective: To compare the risk of adverse events with JAK inhibitors vs tumor necrosis factor (TNF) antagonists in patients with IMIDs in head-to-head comparative effectiveness studies.
J Oncol Pharm Pract
September 2025
Hematology/Oncology, Scripps Clinic, La Jolla, USA.
IntroductionDaratumumab is a therapeutic cornerstone of the management of multiple myeloma, exerting its anti-myeloma activity through targeting of the cell surface glycoprotein CD38 on plasma cells. While originally given intravenously, the subcutaneous formulation, daratumumab hyaluronidase injection (Dara SC), has been associated with non-inferior efficacy and lower infusion-related reaction rates (IRRs) in the treatment of multiple myeloma and light chain amyloidosis. A noted benefit of Dara SC is a short administration time; however, the optimal observation time post injection to ensure patient safety is unclear from the drug labeling.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Radiotherapy and Radiation Oncology, Philipps- Universität Marburg, Marburg, Germany.
Background: Pituitary adenomas are relatively common benign intracranial tumors that may cause significant hormonal imbalances and visual impairments. Radiotherapy (RT) remains an important treatment option, particularly for patients with residual tumor after surgery, recurrent disease, or ongoing hormonal hypersecretion. This study summarizes long-term clinical outcomes and radiation-associated toxicities in patients with pituitary adenomas treated with contemporary radiotherapy techniques at a single institution.
View Article and Find Full Text PDFDrugs Aging
September 2025
Dalla Lana School of Public Health, University of Toronto, V1 06, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.
View Article and Find Full Text PDF