Cargando…

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

BACKGROUND: Pulmonary 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Vielhauer, Jakob, Benesch, Christopher, Pernpruner, Anna, Johlke, Anna-Lena, Hellmuth, Johannes Christian, Muenchhoff, Maximilian, Scherer, Clemens, Fink, Nicola, Sabel, Bastian, Schulz, Christian, Mayerle, Julia, Mahajan, Ujjwal Mukund, Stubbe, Hans Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153021/
https://www.ncbi.nlm.nih.gov/pubmed/37131204
http://dx.doi.org/10.1186/s12959-023-00492-5
_version_ 1785035856010018816
author Vielhauer, Jakob
Benesch, Christopher
Pernpruner, Anna
Johlke, Anna-Lena
Hellmuth, Johannes Christian
Muenchhoff, Maximilian
Scherer, Clemens
Fink, Nicola
Sabel, Bastian
Schulz, Christian
Mayerle, Julia
Mahajan, Ujjwal Mukund
Stubbe, Hans Christian
author_facet Vielhauer, Jakob
Benesch, Christopher
Pernpruner, Anna
Johlke, Anna-Lena
Hellmuth, Johannes Christian
Muenchhoff, Maximilian
Scherer, Clemens
Fink, Nicola
Sabel, Bastian
Schulz, Christian
Mayerle, Julia
Mahajan, Ujjwal Mukund
Stubbe, Hans Christian
author_sort Vielhauer, Jakob
collection PubMed
description BACKGROUND: Pulmonary 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. METHODS: In 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. RESULTS: We 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. CONCLUSION: The 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12959-023-00492-5.
format Online
Article
Text
id pubmed-10153021
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-101530212023-05-03 How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores Vielhauer, Jakob Benesch, Christopher Pernpruner, Anna Johlke, Anna-Lena Hellmuth, Johannes Christian Muenchhoff, Maximilian Scherer, Clemens Fink, Nicola Sabel, Bastian Schulz, Christian Mayerle, Julia Mahajan, Ujjwal Mukund Stubbe, Hans Christian Thromb J Research BACKGROUND: Pulmonary 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. METHODS: In 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. RESULTS: We 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. CONCLUSION: The 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12959-023-00492-5. BioMed Central 2023-05-02 /pmc/articles/PMC10153021/ /pubmed/37131204 http://dx.doi.org/10.1186/s12959-023-00492-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Vielhauer, Jakob
Benesch, Christopher
Pernpruner, Anna
Johlke, Anna-Lena
Hellmuth, Johannes Christian
Muenchhoff, Maximilian
Scherer, Clemens
Fink, Nicola
Sabel, Bastian
Schulz, Christian
Mayerle, Julia
Mahajan, Ujjwal Mukund
Stubbe, Hans Christian
How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title_full How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title_fullStr How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title_full_unstemmed How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title_short How to exclude pulmonary embolism in patients hospitalized with COVID-19: a comparison of predictive scores
title_sort how to exclude pulmonary embolism in patients hospitalized with covid-19: a comparison of predictive scores
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153021/
https://www.ncbi.nlm.nih.gov/pubmed/37131204
http://dx.doi.org/10.1186/s12959-023-00492-5
work_keys_str_mv AT vielhauerjakob howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT beneschchristopher howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT pernpruneranna howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT johlkeannalena howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT hellmuthjohanneschristian howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT muenchhoffmaximilian howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT schererclemens howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT finknicola howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT sabelbastian howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT schulzchristian howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT mayerlejulia howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT mahajanujjwalmukund howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores
AT stubbehanschristian howtoexcludepulmonaryembolisminpatientshospitalizedwithcovid19acomparisonofpredictivescores