ArticleFrontiers in surgery2023
Development and validation of a predictive nomogram for lower extremity deep vein thrombosis dislodgement in orthopedic patients.
Article in Frontiers in surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To analyze the risk factors of lower extremity deep venous thrombosis (DVT) detachment in orthopedic patients, and to establish a risk nomogram prediction model. Methods: The clinical data of 334 patients with orthopedic DVT admitted to the Third Hospital of Hebei Medical University from January 2020 to July 2021 were retrospectively analyzed. General statistics included gender, age, BMI, thrombus detachment, inferior vena cava filter window type, filter implantation time, medical history, trauma history, operation, use of tourniquet, thrombectomy, anesthesia mode, anesthesia grade, operative position, blood loss during operation, blood transfusion, immobilization, use of anticoagulants, thrombus side, thrombus range, D-dimer content before filter implantation and during removal of inferior vena cava filter. Logistic regression was used to perform univariate and multivariate analysis on the possible factors of thrombosis detachment, screen out independent risk factors, establish a risk nomogram prediction model by variables, and internally verify the predictability and accuracy of the model. Results: Binary logistic regression analysis showed that Short time window filter (OR = 5.401, 95% CI = 2.338-12.478), lower extremity operation (OR = 3.565, 95% CI = 1.553-8.184), use of tourniquet (OR = 3.871, 95% CI = 1.733-8.651), non-strict immobilization (OR = 3.207, 95% CI = 1.387-7.413), non-standardized anticoagulation (OR = 4.406, 95% CI = 1.868-10.390), distal deep vein thrombosis (OR = 2.212, 95% CI = 1.047-4.671) were independent risk factors for lower extremity DVT detachment in orthopedic patients ( Conclusion: The nomogram risk prediction model based on six clinical factors, including filter window type, operation condition, tourniquet use, braking condition, anticoagulation condition, and thrombosis range, has good predictive performance.
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