Derivation and Validation of a COPD-specific Pulmonary Embolism Diagnostic Strategy

作者
Vicky Mai,David Jiménez,Dean A. Fergusson,Olivier Sanchez,Raquel Morillo,Pierre‐Marie Roy,Carmen Rodríguez,Frédéric Gagnadoux,Pedro Ruiz‐Artacho,Jeannot Schmidt,Eva María Tabernero,Laurent Bertoletti,Cécile Tromeur,Philippe Girard,Ranjeeta Mallick,Grégoire Le Gal,Françis Couturaud
出处
期刊:Thrombosis and Haemostasis [Thieme Medical Publishers (Germany)]
卷期号:126 (05): 509-517 被引量:2
标识
DOI:10.1055/a-2645-3594
摘要

Introduction: Diagnosing pulmonary embolism (PE) in patients with chronic obstructive pulmonary disease (COPD) exacerbation is challenging due to similarities in clinical symptoms. The aim of this study was to evaluate predictors of PE and to derive and validate a COPD-specific PE diagnostic strategy. Methods: A post-hoc analysis of the PEP trial, a prospective multicenter study of patients with COPD hospitalized with acutely worsening respiratory symptoms, was conducted. The outcome predicted was PE at admission. Univariable and multivariable analyses were conducted to evaluate predictors of PE. Receiver operating characteristic curves were computed to determine the most discriminant D-dimer cut-offs. The COPD-specific PE diagnostic strategy was externally validated in the independent SLICE trial cohort. Results: A total of 734 patients were included. At admission, the prevalence of PE and/or proximal deep venous thrombosis (DVT) was 6.5% (95%CI 5.0-8.6%). A COPD-specific PE diagnostic strategy consisting of a 3-item score (type of COPD exacerbation, alternative diagnosis less likely than PE, and clinical signs of DVT) combined with D-dimer at specific cut-offs (1,000 μg/L if 0 score item and 500 μg/L if 1 or 2 score items) was derived. The overall diagnostic failure rate was 0.9% (95%CI 0.4-1.9%) and 392 patients (53.4%) would need imaging to rule out PE. The external validation showed comparable results. Conclusion: A COPD-specific PE diagnostic strategy was derived specifically for patients with COPD and acutely worsening respiratory symptoms. Further prospective validation of this diagnostic algorithm is needed prior to integrating it in clinical practice.

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