International journal of cardiology. Cardiovascular risk and prevention · 2024
Analysis of risk factors for post-thrombotic syndrome after thrombolysis therapy for acute deep venous thrombosis of lower extremities.
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Zheng Yi, Cao Chunli, Chen Gang, Li Siming, Ye Maolin, Deng Liang, Li Qiyi
Аннотация
OBJECTIVE: The purpose of the research is to explore post-thrombotic syndrome (PTS) after catheter-directed thrombolysis (CDT) treatment for acute lower extremity deep vein thrombosis (DVT) risk factors.
METHODS: We retrospectively selected 171 patients with acute lower extremity DVT undergoing CDT treatment, collected clinical data of the patients, grouped them according to the follow-up results of 1 year after treatment, and included patients with PTS into the concurrent group and patients who did not develop PTS assigned to the unconcurrent group. Univariate analysis and Logistic regression were applied to analyze the risk factors of PTS after catheterization and thrombolytic therapy for acute lower extremity DVT. We applied R4.2.3 software to build three hybrid machine-learning models, including a nomogram, decision tree, and random forest with independent influencing factors as predictive variables.
RESULTS: The incidence of PTS after CDT in acute lower extremity DVT was 36.84 %. BMI >24.33 kg/m2, disease time >7 d, mixed DVT, varicose vein history, stress treatment time>6.5 months, and filter category were independent risk factors for PTS after CDT treatment for acute lower extremity DVT. The AUC value predicted by the random forest model was higher than that of the nomogram model (Z = -2.337, P = 0.019) and the decision tree model (Z = -2.995, P = 0.003).
CONCLUSION: The occurrence of PTS after CDT treatment of acute lower extremity DVT is closely related to many factors, and the established random forest model had the best effect in predicting PTS complicated with PTS.
METHODS: We retrospectively selected 171 patients with acute lower extremity DVT undergoing CDT treatment, collected clinical data of the patients, grouped them according to the follow-up results of 1 year after treatment, and included patients with PTS into the concurrent group and patients who did not develop PTS assigned to the unconcurrent group. Univariate analysis and Logistic regression were applied to analyze the risk factors of PTS after catheterization and thrombolytic therapy for acute lower extremity DVT. We applied R4.2.3 software to build three hybrid machine-learning models, including a nomogram, decision tree, and random forest with independent influencing factors as predictive variables.
RESULTS: The incidence of PTS after CDT in acute lower extremity DVT was 36.84 %. BMI >24.33 kg/m2, disease time >7 d, mixed DVT, varicose vein history, stress treatment time>6.5 months, and filter category were independent risk factors for PTS after CDT treatment for acute lower extremity DVT. The AUC value predicted by the random forest model was higher than that of the nomogram model (Z = -2.337, P = 0.019) and the decision tree model (Z = -2.995, P = 0.003).
CONCLUSION: The occurrence of PTS after CDT treatment of acute lower extremity DVT is closely related to many factors, and the established random forest model had the best effect in predicting PTS complicated with PTS.