2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS)

Abstract

Guidelines summarize and evaluate available evidence with the aim of assisting health professionals in proposing the best management strategies for an individual patient with a given condition. Guidelines and their recommendations should facilitate decision making of health professionals in their daily practice. However, the final decisions concerning an individual patient must be made by the responsible health professional(s) in consultation with the patient and caregiver as appropriate.

Keywords

MedicinePulmonary embolismIntensive care medicineRespiratory systemRespiratory MedicineMedical emergencyInternal medicineSurgery

MeSH Terms

Acute DiseaseAngiographyBiomarkersCardiologyEchocardiographyEuropeFibrin Fibrinogen Degradation ProductsHumansLungPrognosisPulmonary EmbolismPulmonary Medicine

Affiliated Institutions

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Publication Info

Year: 2019
Type: article
Volume: 54
Issue: 3
Pages: 1901647-1901647
Citations: 1499
Access: Closed

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APA Style

                            
                                
                                    Stavros Konstantinides, 
                                
                                    Guy Meyer, 
                                
                                    Cecilia Becattini
                                
                                et al.
                            
                            (2019). 
                            2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS). 
                            European Respiratory Journal
                            , 54
                            (3)
                            , 1901647-1901647.
                            https://doi.org/10.1183/13993003.01647-2019
                        

Identifiers

DOI: 10.1183/13993003.01647-2019
PMID: 31473594

Data Quality

Data completeness: 86%