
Adjusting D-dimer to Lung Disease Extent to Exclude Pulmonary Embolism in COVID-19 Patients (Co-LEAD)
Author(s) -
Benjamin Planquette,
Lina Khider,
Alice Le Berre,
S. Soudet,
Gilles Pernod,
Raphaël Le Mao,
Matthieu Besutti,
Nicolas Gendron,
Alexandra Yannoutsos,
David M. Smadja,
Guillaume Goudot,
Salma Al Kahf,
Nassim Mohammedi,
Antoine Al Hamoud,
Aurélien Philippe,
Laure Fournier,
Bastien Rance,
JeanLuc Diehl,
Tristan Mirault,
Emmanuel Messas,
Joseph Emmerich,
Richard Chocron,
Francis Couturaud,
Gilbert Ferreti,
MarieAntoinette SevestrePietri,
Nicolas Meneveau,
Gilles Châtellier,
Olivier Sanchez
Publication year - 2022
Publication title -
thrombosis and haemostasis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.97
H-Index - 188
eISSN - 2567-689X
pISSN - 0340-6245
DOI - 10.1055/a-1768-4371
Subject(s) - medicine , confidence interval , receiver operating characteristic , d dimer , pulmonary embolism , covid-19 , area under the curve , retrospective cohort study , lung , cohort , nuclear medicine , gastroenterology , disease , infectious disease (medical specialty)
D-dimer measurement is a safe tool to exclude pulmonary embolism (PE) but its specificity decreases in COVID-19. Our aim was to derive a new algorithm with specific D-dimer threshold in COVID-19 patients.Methods: We conducted a French multicenter, retrospective cohort study among 774 COVID-19 patients with suspected PE. D-dimer threshold adjusted to computed tomography (CT) extent of lung damage was derived in a patient set (n=337), and its safety assessed in an independent validation set (n=337). Results: According to ROC curves, in the derivation set D-dimer safely excluded PE, with one false negative when using a 900 ng/mL threshold when lung damage extent was <50% and 1700 ng/mL when lung damage extent was ≥50%. In the derivation set, the algorithm sensitivity was 98.2% (95% CI: 94.7–100.0) and its specificity 28.4% (95% CI: 24.1–32.3). The negative likelihood ratio (NLR) was 0.06 (95% CI: 0.01–0.44) and the area under the curve (AUC) was 0.63 (95% CI: 0.60–0.67). In the validation set, sensitivity and specificity were 96.7% (95% CI: 88.7–99.6) and 39.2% (95% CI: 32.2–46.1), respectively. The NLR was 0.08 (95% CI; 0.02–0.33) and the AUC did not differed from that of the derivation set (0.68 ,95% CI: 0.64–0.72, P = 0.097). Using the Co-LEAD algorithm, 76/250 (30.4%) COVID-19 patients with suspected PE could have been managed without CT pulmonary angiography (CTPA).Conclusion: The Co-LEAD algorithm safely excludes PE, and allows reducing the use of CTPA among COVID-19 patients. Further prospective studies are necessary to validate this strategy.