Introduction And Objectives: Little is known about the impact of networks for ST-segment elevation myocardial infarction (STEMI) care on the population. The objective of this study was to determine whether the PROGALIAM (Programa Gallego de Atención al Infarto Agudo de Miocardio) improved survival in northern Galicia.
Methods: We collected all events coded as STEMI between 2001 and 2013. A total of 6783 patients were identified and divided into 2 groups: pre-PROGALIAM (2001-2005), with 2878 patients, and PROGALIAM (2006-2013), with 3905 patients.
Results: In the pre-PROGALIAM period, 5-year adjusted mortality was higher both in the total population (HR, 1.22, 95%CI, 1.14-1.29; P <.001) and in each area (A Coruña: HR, 1.12; 95%CI, 1.02-1.23; P=.02; Lugo: HR, 1.34; 95%CI, 1.2-1.49; P <.001 and Ferrol: HR, 1.23; 95%CI, 1.1-1.4; P=.001). Before PROGALIAM, 5-year adjusted mortality was higher in the areas of Lugo (HR, 1.25; 95%CI, 1.05-1.49; P=.02) and Ferrol (HR, 1.32; 95%CI, 1.13-1.55; P=.001) than in A Coruña. These differences disappeared after the creation of the STEMI network (Lugo vs A Coruña: HR, 0.88; 95%CI, 0.72-1.06; P=.18, Ferrol vs A Coruña: HR, 1.04; 95%CI, 0.89-1.22; P=.58.
Conclusions: For patients with STEMI, the creation of PROGALIAM in northern Galicia decreased mortality and increased equity in terms of survival both overall and in each of the areas where it was implemented. This study was registered at ClinicalTrials.gov (Identifier: NCT02501070).
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http://dx.doi.org/10.1016/j.rec.2019.09.031 | DOI Listing |
Acute coronary syndrome (ACS) is an acute heart disease that often evolves rapidly. In ACS patients presenting with no-ST-segment elevation (NSTE-ACS), the timing of symptom onset pre-hospital may inform the disease stage and prognosis. We pilot-tested two off-the-shelf natural language processing (NLP) pipelines, namely and ( ), to extract date and time (DateTime) information of patient-reported chest pain symptoms from electronic health records (EHR) clinical notes.
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Division of Cardiology Lifespan Cardiovascular Institute, Warren Alpert Medical School of Brown University, Providence, RI (J.D.A.).
Background: In-hospital mortality risk prediction is an important tool for benchmarking quality and patient prognostication. Given changes in patient characteristics and treatments over time, a contemporary risk model for patients with acute myocardial infarction (MI) is needed.
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Curr Probl Cardiol
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Division of Cardiology and the McAllister Heart Institute, University of North Carolina, Chapel Hill, NC. Electronic address:
Background: The development of ST-segment elevation myocardial infarction (STEMI) in patients hospitalized for non-cardiac indications carries a high mortality rate.
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JACC Cardiovasc Imaging
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Department of Radiology and Imaging Sciences and Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA. Electronic address:
Background: Hemorrhagic myocardial infarction (hMI) can rapidly diminish the benefits of reperfusion therapy and direct the heart toward chronic heart failure. T2∗ cardiac magnetic resonance (CMR) is the reference standard for detecting hMI. However, the lack of clarity around the earliest time point for detection, time-dependent changes in hemorrhage volume, and the optimal methods for detection can limit the development of strategies to manage hMI.
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January 2025
12th Cardiology Department, Hippokration Hospital, Medical School, Aristotle University of Thessaloniki, Greece.
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