showing 2 related works from this author
Supervised Analysis for Phenotype Identification: The Case of Heart Failure Ejection Fraction Class
2021
Artificial Intelligence is creating a paradigm shift in health care, with phenotyping patients through clustering techniques being one of the areas of interest. Objective: To develop a predictive model to classify heart failure (HF) patients according to their left ventricular ejection fraction (LVEF), by using available data from Electronic Health Records (EHR). Subjects and methods: 2854 subjects over 25 years old with a diagnosis of HF and LVEF, measured by echocardiography, were selected to develop an algorithm to predict patients with reduced EF using supervised analysis. The performance of the developed algorithm was tested in heart failure patients from Primary Care. To select the mo…
Real-World Data of Anticoagulant Treatment in Non-valvular Atrial Fibrillation
2022
AimsTo assess the impact of anticoagulant treatment on risk for stroke and all-cause mortality of patients with atrial fibrillation using real-world data (RWD).MethodsPatients with prevalent or incident atrial fibrillation were selected throughout a study period of 5 years. Stroke, transitory ischemic attack, hemorrhagic stroke, and all-cause mortality were identified in the claims of the electronic health records (EHRs). Subjects were classified according to the anticoagulant treatment in four groups: untreated, vitamin K antagonists (VKAs), New Oral Anticoagulants (NOACs), and antiplatelet (AP). Risk of events and protection with anticoagulant therapy were calculated by Cox proportional h…