Results 211 to 220 of about 209,031 (375)

Machine Learning‐Based Prediction of Life‐Threatening Complications During Hemodialysis in Hospitalized Patients With Poor General Conditions

Artificial Organs, EarlyView.
A machine learning model using predialysis data predicted sudden events during or after hemodialysis with high accuracy (auROC: 0.889). The key predictors included emergency hospitalization, recent surgery, high heart rate, low albumin levels, and high CRP.
Naotaka Kato, Takeshi Goto, Tomoyuki Ohira, Hirotaka Kinoshita, Kugo Kurokawa, Kouhei Naganuma, Chikako Ohminato, Junko Ogasawara, Shingo Hatakeyama, Yoshihiro Sasaki, Kazuyoshi Hirota, Chikara Ohyama   +11 more
wiley   +1 more source

Successful upgrade to cardiac resynchronization therapy for cardiac implantation-associated left subclavian vein occlusion: A case report

, 2021
Jinyan Zhong, Xiaowei Zheng, Heng-Dong Li, Longfu Jiang   +3 more
openalex   +1 more source

The anti‐fibrotic effects of novel heart failure pharmacotherapies in advanced heart failure patients

British Journal of Pharmacology, EarlyView.
Background and Purpose Novel heart failure (HF) pharmacotherapies, including angiotensin receptor‐neprilysin inhibitor (ARNI) and sodium‐glucose cotransporter 2 inhibitors (SGLT2is), may confer cardiovascular benefits by attenuating myocardial fibrosis. However, direct evidence from human failing myocardial samples is limited.
Dávid Nagy, Tamás Radovits, Tímea Bálint, Zoltán Horváth, Petra Kocsis‐Balogh, Ákos Gergely Tóth, Attila Oláh, Alex Ali Sayour, Bálint András Barta, Béla Merkely, Mihály Ruppert   +10 more
wiley   +1 more source

Sodium glucose co‐transporter 2 inhibitors versus dipeptidyl peptidase‐4 inhibitors and the risk of ventricular arrhythmia among patients with type 2 diabetes: A population‐based cohort study

Diabetes, Obesity and Metabolism, EarlyView.
Abstract Aims To determine whether sodium glucose co‐transporter 2 inhibitors (SGLT2i) use, compared with dipeptidyl peptidase‐4 inhibitors (DPP4i) use, is associated with the risk of ventricular arrhythmias (VA) among patients with type 2 diabetes. Materials and Methods We conducted a population‐based cohort study using a prevalent new‐user design and
Wang‐Choi Tang, Pauline Reynier, Antonios Douros, Oriana H. Y. Yu, Robert W. Platt, Kristian B. Filion   +5 more
wiley   +1 more source

Pharmacotherapy post-cardiac resynchronization therapy: Long walk home. [PDF]

Eur J Heart Fail
Žižek D, Cvijić M, Lainscak M.
europepmc   +1 more source

Right Ventricular Pacing and Sensing Function in High Posterior Septal and Apical Lead Placement in Cardiac Resynchronization Therapy

, 2012
Hans Morten Kristiansen, Thomas Hovstad, G. Vollan, Svein Færestrand   +3 more
openalex   +1 more source

His-Optimized Cardiac Resynchronization Therapy With Ventricular Fusion Pacing for Electrical Resynchronization in Heart Failure.

JACC Clinical Electrophysiology, 2021
A. Zweerink, S. Zubarev, E. Bakelants, D. Potyagaylo, C. Stettler, M. Chmelevsky, E. D. Lozeron, A. Hachulla, J. Vallée, H. Burri   +9 more
semanticscholar   +1 more source

Machine learning‐based prediction of atrial fibrillation in patients with atrial high‐rate episodes

European Journal of Clinical Investigation, EarlyView.
Abstract Background Given the modest performance of available predictive models in estimating the risk of atrial fibrillation (AF) in patients with atrial high‐rate episodes (AHREs) detected by cardiac implantable electronic devices (CIEDs), this study explores the potential use of machine learning (ML) algorithms in this context. Purpose To assess the
Amir Askarinejad, Tommaso Bucci, Niloofar Asgharzadeh, Zahra Amirjam, Enrico Tartaglia, Michele Rossi, Yang Chen, Yalin Zheng, Gregory Y. H. Lip, Majid Haghjoo   +9 more
wiley   +1 more source

CARDIAC RESYNCHRONIZATION THERAPY OF CHRONIC HEART FAILURE AS «BRIDGE» TO CARDIAC TRANSPLANTATION

, 2014
Д. В. Шумаков, В. В. Слободяник   +1 more
openalex   +2 more sources

Interlead electrical delays and scar tissue: Response to cardiac resynchronization therapy in patients with ischemic cardiomyopathy [PDF]

, 2019
Jasmine Borg Tahri, Thomas Fritz Hansen, Hanne Stavø Storkås, Trine K. Lauridsen, Flemming Javier Olsen, Allan Iversen, Tommi Bo Lindhardt, Niels Eske Bruun, Peter Søgaard, Niels Risum   +9 more
openalex   +1 more source