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Updated: Sep 11, 2025

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
Published on: June 2, 2015
Combined assessment of Caprini score, D-dimer, and thromboelastography for predicting deep venous thrombosis in lung
Jianhui Sheng1, Xiao Han1, Hui Zheng2
1Yantaishan Hospital Yantai, Shandong, China.
Objective:
To evaluate the predictive value of Caprini score, D-dimer levels, and thromboelastography parameters for deep venous thrombosis (DVT) in patients with lung cancer.
Methods:
A retrospective analysis was conducted on 90 lung cancer patients admitted to Yantaishan Hospital between September 2020 and August 2024. The observation group comprised 50 patients with DVT, while 40 patients without DVT formed the control group. Caprini scores, D-dimer levels, and thromboelastography parameters including coagulation angle (α angle) and maximum amplitude (MA) were compared between groups. Pearson correlation assessed associations with Villalta scores. Logistic regression identified independent risk factors for DVT. Receiver operating characteristic (ROC) curves evaluated the predictive efficacy of single and combined indicators.
Results:
Compared to controls, the observation group showed significantly higher Caprini scores (P=0.008), D-dimer levels (P<0.001), α angle (P<0.001), and MA (P<0.001). Within severity subgroups, these parameters were elevated in the moderate group compared to the mild group (all P<0.001). Pearson analysis demonstrated positive correlations of Caprini score (P=0.024), D-dimer levels (P=0.029), α angle (P=0.037), and MA (P=0.030) with Villalta scores. Logistic regression revealed these four parameters as independent risk factors for DVT in lung cancer patients. The combined index yielded an AUC of 0.861, outperforming individual indicators (Caprini score 0.771, D-dimer 0.789, α angle 0.747, MA 0.725) in predicting DVT.
Conclusions:
Caprini score, D-dimer levels, α angle, and MA are independently associated with DVT occurrence and severity in lung cancer patients. Combined assessment enhances predictive accuracy, providing valuable guidance for early identification and clinical management of DVT.
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