A Comparative Analysis of the Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Infection on the Performance of Clinical Decision-Making Algorithms for Pulmonary Embolism

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Abstract

Background/Objectives: This study aimed to compare the diagnostic accuracy of the Wells and Geneva scores using a 500 ng/mL D-dimer cutoff, as well as the age-adjusted D-dimer (AADD), YEARS, and pulmonary embolism graduated D-dimer (PEGeD) algorithms, in patients with and without COVID-19. Various D-dimer cutoffs were also evaluated. Methods: This retrospective study included emergency department patients who underwent computed tomography pulmonary angiography (CTPA) for suspected pulmonary embolism (PE). The diagnostic performances of clinical prediction algorithms were compared between COVID-19-positive and -negative groups. Results: We analyzed data from 1423 patients; the PE and COVID-19 positivity rates were 7.3% and 69.9%, respectively. In COVID-19-positive patients, the Wells score with a 500 ng/mL D-dimer cutoff demonstrated 97.22% sensitivity (95% CI: 80.53–100.00) and 4.99% specificity (95% CI: 3.58–6.39). Using AADD raised the specificity to 7.81% (95% CI: 6.08–9.54) while maintaining 97.22% sensitivity (95% CI: 93.43–100.00); similar findings were observed with the Geneva score. The YEARS algorithm had 86.11% sensitivity (95% CI: 78.12–94.10) and 32.75% specificity (95% CI: 29.73–35.78), whereas the PEGeD algorithm showed 86.11% sensitivity (95% CI: 78.12–94.10) and 34.06% specificity (95% CI: 31.00–37.12). Both algorithms demonstrated slightly improved specificity and accuracy in COVID-19-positive patients. Conclusions: The YEARS and PEGeD algorithms showed slight improvements in specificity and accuracy among COVID-19-positive patients. The Wells and Geneva scores maintained higher sensitivity but lower specificity across groups. Adjusting the D-dimer cutoffs increased the specificity but increased the risk of missed diagnoses. Overall, COVID-19 had a minimal impact on PE diagnostic algorithm performances.

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