How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores

Thrombosis Journal

Research

Clemens Scherer¹  Ujjwal Mukund Mahajan²  Julia Mayerle²  Hans Christian Stubbe³  Jakob Vielhauer³  Anna-Lena Johlke³  Anna Pernpruner³  Christian Schulz³  Christopher Benesch³  Johannes Christian Hellmuth⁴  Bastian Sabel⁵  Nicola Fink⁵  Maximilian Muenchhoff⁶ 

[1] COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany;Department of Medicine I, University Hospital LMU Munich, Munich, Germany;Department of Medicine II, University Hospital LMU Munich, Munich, Germany;Department of Medicine II, University Hospital LMU Munich, Munich, Germany;German Center for Infection Research, Partner Site Munich, Munich, Germany;Department of Medicine III, University Hospital LMU Munich, Munich, Germany;COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany;Department of Radiology, Hospital of the LMU Munich, Munich, Germany;German Center for Infection Research, Partner Site Munich, Munich, Germany;COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany;Max von Pettenkofer Institute and Gene Center, National Reference Center for Retroviruses, Ludwig Maximilian University (LMU) of Munich, Virology, Munich, Germany;

关键词: Pulmonary embolism;    COVID-19;    Computed tomography pulmonary angiography;    ventilation/perfusion scintigraphy;    d-dimer;   

DOI  :  10.1186/s12959-023-00492-5

 received in 2022-12-17, accepted in 2023-04-12,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundPulmonary embolism (PE) is an important complication of Coronavirus disease 2019 (COVID-19). COVID-19 is associated with respiratory impairment and a pro-coagulative state, rendering PE more likely and difficult to recognize. Several decision algorithms relying on clinical features and D-dimer have been established. High prevalence of PE and elevated Ddimer in patients with COVID-19 might impair the performance of common decision algorithms. Here, we aimed to validate and compare five common decision algorithms implementing age adjusted Ddimer, the GENEVA, and Wells scores as well as the PEGeD- and YEARS-algorithms in patients hospitalized with COVID-19.MethodsIn this single center study, we included patients who were admitted to our tertiary care hospital in the COVID-19 Registry of the LMU Munich. We retrospectively selected patients who received a computed tomography pulmonary angiogram (CTPA) or pulmonary ventilation/perfusion scintigraphy (V/Q) for suspected PE. The performances of five commonly used diagnostic algorithms (age-adjusted D-dimer, GENEVA score, PEGeD-algorithm, Wells score, and YEARS-algorithm) were compared.ResultsWe identified 413 patients with suspected PE who received a CTPA or V/Q confirming 62 PEs (15%). Among them, 358 patients with 48 PEs (13%) could be evaluated for performance of all algorithms. Patients with PE were older and their overall outcome was worse compared to patients without PE. Of the above five diagnostic algorithms, the PEGeD- and YEARS-algorithms performed best, reducing diagnostic imaging by 14% and 15% respectively with a sensitivity of 95.7% and 95.6%. The GENEVA score was able to reduce CTPA or V/Q by 32.2% but suffered from a low sensitivity (78.6%). Age-adjusted D-dimer and Wells score could not significantly reduce diagnostic imaging.ConclusionThe PEGeD- and YEARS-algorithms outperformed other tested decision algorithms and worked well in patients admitted with COVID-19. These findings need independent validation in a prospective study.

【 授权许可】

CC BY   
© The Author(s) 2023

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