Journals / Turkish Journal of Clinics and Laboratory / 2025 / Cilt: 16 Sayı: 4

Inflammatory Biomarkers in Venous Thromboembolism: Distinguishing Proximal and Distal DVT Subtypes and Assessing Pulmonary Embolism Risk

Venöz Tromboembolizmde Enflamatuar Biyobelirteçler: Proksimal ve Distal DVT Alt Tiplerini Ayırt Etme ve Pulmoner Emboli Riskini Değerlendirme

Murat Yücel(ANKARA BİLKENT ŞEHİR HASTANESİ)0000-0002-9182-0690
Muhammet Fethi Sağlam(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0003-0744-0001
Kemal Erdoğan(YILDIRIM BEYAZIT ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0002-2684-7256
Op. Dr. Onur Karahasanoğlu(Ankara Bilkent Şehir Hastanesi, Kardiyovasküler Cerrahi Kliniği)0000-0002-1699-5095
Serdar Günaydın(Ankara Bilkent Şehir Hastanesi, Kardiyovasküler Cerrahi Kliniği)0000-0002-9717-9793
Pages
662–670
Publication Date
2026-01-01
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

For PE, D-dimer showed the highest accuracy (AUC 0.827, sensitivity 95.6%, specificity 61.8%), while NLR provided moderate discriminatory power (AUC 0.669).

📌 3 Key Takeaways

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Objective & Hypothesis:Abstract Background: Deep vein thrombosis (DVT) is a major cause of morbidity and mortality.
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Key Findings & Data:Methods: In this retrospective case-control study, 750 patients (2019–2025) with suspected lower extremity DVT were classified into proximal DVT (n=250), distal DVT (n=250), and Doppler-negative control group (n=250).
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Conclusion & Impact:For PE, D-dimer showed the highest accuracy (AUC 0.827, sensitivity 95.6%, specificity 61.8%), while NLR provided moderate discriminatory power (AUC 0.669).
🔬Design:Modeling & Simulation
📍Scope:2019–2025 Verileri
⚙️Variables:deriven trombozu · pulmoner emboli · inflamatuar indeksler

Abstract

Abstract Background: Deep vein thrombosis (DVT) is a major cause of morbidity and mortality. Proximal DVT carries a higher risk of pulmonary embolism (PE), but the distinct inflammatory profiles of proximal and distal DVT remain unclear. Objectives: This study aims to compare the distribution of next-generation systemic inflammatory indices (SII, SIRI, AISI, NLR, PLR, MLR) and conventional biomarkers (CRP, D-dimer) and to evaluate the diagnostic and prognostic value of these parameters in predicting PE. Additionally, the effects of demographic and etiological differences between groups on the systemic inflammatory response were analyzed; the findings were validated using logistic regression models and ROC curve metrics to identify independent predictive markers. Methods: In this retrospective case-control study, 750 patients (2019–2025) with suspected lower extremity DVT were classified into proximal DVT (n=250), distal DVT (n=250), and Doppler-negative control group (n=250). Inflammatory indices [SII, SIRI, AISI, NLR, PLR, MLR], conventional biomarkers (CRP, D-dimer), and biochemical parameters were evaluated. Group differences were tested using ANOVA/Kruskal–Wallis, while logistic regression and ROC analyses identified predictors of proximal DVT and PE. Results: Patients with proximal DVT had significantly higher inflammatory indices, CRP, and D-dimer values compared to those with distal DVT and controls (all p<0.001). Distal DVT showed no significant difference from controls except for high SIRI (p<0.001). Proximal DVT was also associated with higher creatinine and LDH (Lactate Dehydrogenase) and lower sodium levels (all p<0.001). In multivariate regression, NLR (aOR 1.24, p=0.042) and D-dimer (aOR 1.43, p<0.001) independently predicted proximal DVT. For PE, D-dimer showed the highest accuracy (AUC 0.827, sensitivity 95.6%, specificity 61.8%), while NLR provided moderate discriminatory power (AUC 0.669).

Özet

Özet Arka plan: Derin ven trombozu (DVT), dünya çapında morbidite ve mortalitenin önemli bir nedenidir. Proksimal DVT, pulmoner emboli (PE) riski daha yüksektir; ancak, proksimal ve distal DVT'nin farklı inflamatuar profilleri hala belirsizdir. Amaçlar: Bu çalışmanın amacı, yeni nesil sistemik inflamatuar indekslerin (SII, SIRI, AISI, NLR, PLR, MLR) ve geleneksel biyobelirteçlerin (CRP, D-dimer) dağılımını karşılaştırmak ve bu parametrelerin PE'yi öngörmedeki tanısal ve prognostik değerini değerlendirmektir. Ek olarak, gruplar arasındaki demografik ve etiyolojik farklılıkların sistemik inflamatuar yanıt üzerindeki etkileri analiz edildi ve bulgular, bağımsız prediktif belirteçleri tanımlamak için lojistik regresyon modelleri ve ROC eğrisi metrikleri kullanılarak doğrulandı. Yöntemler: Bu retrospektif vaka kontrol çalışmasında, alt ekstremite DVT şüphesi olan 750 hasta (2019–2025) proksimal DVT (n=250), distal DVT (n=250) ve Doppler negatif kontrol (n=250) gruplarına sınıflandırılmıştır. Enflamatuar indeksler (SII, SIRI, AISI, NLR, PLR ve MLR), konvansiyonel biyobelirteçler (CRP ve D-dimer) ve biyokimyasal parametreler değerlendirildi. Grup farklılıkları ANOVA/Kruskal–Wallis kullanılarak test edilirken, proksimal DVT ve PE'nin öngörücüleri belirlemek için lojistik regresyon ve ROC analizleri kullanıldı. Sonuçlar: Proksimal DVT'li hastalar, distal DVT'li hastalar ve kontrollere göre anlamlı olarak daha yüksek inflamatuar belirteçler, CRP ve D-dimer düzeylerine sahipti (tümü p < 0,001). Distal DVT, yüksek SIRI (p<0,001) dışında kontrollere göre anlamlı bir fark göstermedi. Proksimal DVT ayrıca daha yüksek kreatinin ve LDH (laktat dehidrojenaz) ve daha düşük sodyum düzeyleri ile ilişkiliydi (tümü p<0,001). Çok değişkenli regresyonda, NLR (OR 1,24, p=0,042) ve D-dimer (OR 1,43, p<0,001) proksimal DVT'yi bağımsız olarak öngördü. PE için, D-dimer en yüksek doğruluğu gösterdi (AUC 0,827, duyarlılık %95,6, özgüllük %61,8), NLR ise orta düzeyde ayırt edici güç gösterdi (AUC 0,669).

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Cite This Article

Yücel, M., Sağlam, M. F., Erdoğan, K., Karahasanoğlu, O. D. O., Günaydın, S. (2026). Inflammatory Biomarkers in Venous Thromboembolism: Distinguishing Proximal and Distal DVT Subtypes and Assessing Pulmonary Embolism Risk. Turkish Journal of Clinics and Laboratory, Cilt: 16 Sayı: 4, 662–670. https://doi.org/10.18663/tjcl.1785597

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References (22)

  1. Navarrete S, Figueroa B, Fuentes J, Palomo I, Alarcon M. Pathophysiology of deep vein thrombosis. Clin Exp Med 2022; 23: 645-54.
  2. MacDougall D, Feliu AL, Briesacher BA, Elder MA, Walker PC. Economic burden of deep-vein thrombosis, pulmonary embolism, and post-thrombotic syndrome. Am J Health Syst Pharm 2006; 63: 20.
  3. Stubbs MJ, Mouyis M, Thomas M. Deep vein thrombosis. BMJ 2018; 360: k351.
  4. Bikdeli B, Jimenez D, Hawkins M, Orue MT, Fernandez-Capitan C, Jara-Palomares L et al. Clinical Presentation and Short- and Long-term Outcomes in Patients With Isolated Distal Deep Vein Thrombosis vs Proximal Deep Vein Thrombosis in the RIETE Registry. JAMA Cardiol 2022; 7: 1-10.
  5. Chang J. Pathogenesis of Two Faces of DVT: New Identity of Venous Thromboembolism as Combined Micro-Macrothrombosis. Life 2022; 12: 1256.
  6. Kirkilesis G, Kakkos SK, Tsolani E, Gerotasiafas GT. Treatment of distal deep vein thrombosis. Cochrane Database Syst Rev 2019; 4: CD013322.
  7. Yao M, Wang L, Du J, Wu G, Shi Y, Li M et al. Neutrophil extracellular traps mediate deep vein thrombosis: from mechanism to therapy. Front Immunol 2023; 14: 1144244.
  8. Kuplay H, Erdem K, Arslan S, Gunes Y, Celik SE, Ozer S et al. The neutrophil-lymphocyte ratio and the platelet-lymphocyte ratio correlate with thrombus burden in deep venous thrombosis. J Vasc Surg Venous Lymphat Disord 2020; 8: 100-7.
  9. Bozkurt AK, Alpagut U, Aykut K, Besir Y, Erer D, Goncu T et al. National guidelines on the management of venous thromboembolism: Joint guideline of the Turkish Society of Cardiovascular Surgery. Turk Gogus Kalp Damar Cerrahisi Derg 2021; 29: 562-76.
  10. Stevens SM, Woller SC, Kreuziger LB, Bounameaux H, Doerschug K, Geersing GJ et al. Antithrombotic Therapy for VTE Disease: Second Update of the CHEST Guideline and Expert Panel Report. Chest 2021; 160: e545-e608.
  11. Kearon C. Natural History of Venous Thromboembolism. Circulation 2003; 107: I22-I30.
  12. Liu H, Luo B, Long L, Li D, Fu H, Zhang S et al. High systemic inflammation response index level is associated with an increased risk of lower extremity deep venous thrombosis. Ann Med 2023; 55: 2195444.
  13. Theofilis P, Sagris M, Oikonomou E, Antonopoulos AS, Siasos G, Tsioufis C et al. Inflammatory Mechanisms Contributing to Endothelial Dysfunction. Biomedicines 2021; 9: 781.
  14. Branchford B, Carpenter S. The Role of Inflammation in Venous Thromboembolism. Front Pediatr 2018; 6: 142.
  15. Mukhopadhyay S, Johnsonashman K, Brzoska T, Gumaa MM, Karunakaran D, Antithrombotic S et al. Fibrinolysis and Inflammation in Venous Thrombus Resolution. Front Immunol 2019; 10: 712.
  16. Bakirci E, Degirmenci H, Hamur H, Kalkan K, Inci S, Gokhan S et al. The Role of Nonspecific Inflammatory Markers in Determining the Anatomic Extent of Venous Thromboembolism. Clin Appl Thromb Hemost 2013; 21: 181-5.
  17. Xia Y, Xia C, Wu L, Li Z, Li H, Xia J et al. Systemic Immune Inflammation Index (SII), System Inflammation Response Index (SIRI) and Risk of All-Cause Mortality and Cardiovascular Mortality. J Clin Med 2023; 12: 4425.
  18. Schellong S, Goldhaber SZ, Weitz JI, Ageno W, Bounameaux H, Turpie AGG et al. Isolated Distal Deep Vein Thrombosis: Perspectives from the GARFIELD-VTE Registry. Thromb Haemost 2019; 119: 1675-85.
  19. Chan F, Moriwaki K, De Rosa M. Detection of necrosis by release of lactate dehydrogenase activity. Methods Mol Biol 2013; 979: 65-70.
  20. Barco S, Klok FA, Mahé I, Marchena JJ, Ballaz A, Rubio-Caballero M et al. Impact of sex, age, and risk factors for venous thromboembolism on the initial presentation of first isolated symptomatic acute deep vein thrombosis. Thromb Res 2019; 173: 166-71.
  21. Galanaud JP, Quenet S, Rivron-Guillot K, Quere I, Sanchez CP, Brazeau-Frigon S et al. Comparative study on risk factors and early outcome of symptomatic distal versus proximal deep vein thrombosis: results from the OPTIMEV study. Thromb Haemost 2009; 102: 493-500.
  22. Kyrle P, Eischer L, Šinkovec M, Eichinger S. The Vienna Prediction Model for identifying patients at low risk of recurrent venous thromboembolism. Eur Heart J 2023; 45: 45-53.