| A Diagnostic Roadmap for Venous Thromboembolism: Pulmonary Embolism and Deep Vein Thrombosis |
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Jong Shin Woo |
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Division of Cardiovascular, Department of Internal Medicine, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Korea |
| 호흡 곤란과 실신으로 내원한 환자에서 정맥혈전색전증의 진단 |
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우종신 |
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경희대학교 의과대학 경희대학교병원 심장내과 |
Correspondence:
Jong Shin Woo, Tel: +82-2-958-8170, Fax: +82-2-958-8160, Email: cardiodrwoo@gmail.com
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Received: 22 June 2026 • Revised: 23 August 2026 • Accepted: 21 September 2026 |
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| Abstract |
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Venous thromboembolism (VTE), encompassing pulmonary embolism (PE) and deep vein thrombosis (DVT), requires a structured diagnostic roadmap to prevent delayed diagnosis and unnecessary imaging. This review outlines a step-by-step approach from clinical suspicion to objective confirmation and early risk stratification. For suspected PE, hemodynamic stability is the initial branch point. Hemodynamically stable patients are evaluated using pretest probability tools and validated D-dimer strategies, including age-adjusted thresholds, YEARS, or clinical-probability-adjusted approaches such as PEGeD, followed by computed tomography pulmonary angiography when indicated. Pregnancy-adapted YEARS can reduce thoracic imaging in selected pregnant patients. For suspected DVT, the Wells score, D-dimer, and compression ultrasonography are applied sequentially. Once PE is confirmed, risk assessment should integrate clinical severity, right ventricular dysfunction, cardiac biomarkers, hemodynamic and respiratory compromise to guide management decisions. The final diagnosis should specify thrombus location and extent, risk category, provoking factors, and remaining diagnostic uncertainty. Standardizing this roadmap may reduce diagnostic delay and unnecessary imaging while linking diagnosis to appropriate disposition, monitoring, and follow-up. |
| Key Words:
Venous thromboembolism; Pulmonary embolism; Deep vein thrombosis; D-dimer; Diagnostic algorithm; Clinical probability |
| 주제어:
정맥혈전색전증; 폐색전증; 심부정맥혈전증; D-이합체 검사; 진단 알고리즘; 임상 가능성 |
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