Publications by authors named "Paula Madalina Lupu"
: we aimed to highlight the state of the art in terms of pediatric population adherence to insulin pumps. This study intends to underline the significance of identifying and minimizing, to the greatest extent feasible, the factors that adversely affect the juvenile population's adherence to insulin pump therapy. : articles from PubMed, Embase, and Science Direct databases were evaluated using the following search terms: adherence, pump insulin therapy, children, pediatric population, and type 1 diabetes, in combination with several synonyms such as compliance, treatment adherence, pump adherence, patient dropouts, and treatment refusal.
View Article and Find Full Text PDFBackground: The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used?
Methods: We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively.
Introduction: Including healthcare professionals dealing with cardiovascular diseases, Heart Team is a concept/structure designed for selecting diagnostic strategies, facilitating therapeutic decisions, and improving cardiovascular outcomes in patients with complex heart pathologies, requiring input from different subspecialties and the necessity of a multidisciplinary approach. The aim of this narrative review is to search for and to summarize current evidence regarding Heart Team and to underline the future directions for the development of this concept.
Methods: We searched the electronic database of PubMed, SCOPUS, and Cochrane CENTRAL for studies including Heart Team.