Deep Vein Thrombosis in Pelvic Tumor Patients: Correlating Serum Coagulation Factors with Clinical Risk Profiles.
This study aimed to investigate the clinical features, coagulation, and risk factors of deep vein thrombosis (DVT) in patients with pelvic tumor and to construct a prediction model for postoperative DVT events.
Clinical data of 161 patients with pelvic tumors (preoperative DVT group n = 22, non-DVT group n = 139; postoperative DVT group n = 35, NDVT group n = 125; and one case of postoperative pulmonary thrombosis was excluded) were retrospectively analyzed. Age, BMI, disease type, FIGO stage, and coagulation parameters (prothrombin time, PT; activated partial thromboplastin time, APTT; fibrinogen, FIB; D-dimer, D-D; plasminogen activator inhibitor-1, PAI-1) were compared. The key variables were screened using principal component analysis. The prediction model for postoperative DVT was built through logistic regression, and its efficacy was tested using a ROC curve.
PT, D-D, and PAI-1 were significantly higher in the preoperative DVT group than in the non-DVT group (p < 0.001), and APTT was significantly shorter (p = 0.002). The postoperative DVT group was characterized by advanced age (p = 0.032), a higher proportion of ovarian and endometrial cancers, a greater percentage of advanced FIGO stages (p = 0.002), longer postoperative bedtime of more than 72 hours (p = 0.028), and higher levels of PT, FIB, D-D, and PAI-1 (p < 0.001). Principal component analysis showed age and D-D as the main contributing factors. The logistic regression model showed that age (OR = 1.02, p = 0.05), elevated D-D (OR = 1.02, p = 0.001), FIGO stages III and IV (OR = 3.60, p = 0.048), absence of thrombolytic prophylaxis in the postoperative period (OR = 2.85, p = 0.049), and the presence of adjuvant therapy in the postoperative period (OR = 1.02, p = 0.038) were independent risk factors for postoperative DVT, and the AUC of the model reached 0.865 (p < 0.001).
Age, preoperative DVT, D-D level, and tumor stage are independent predictors of postoperative DVT in pelvic tumors. The constructed prediction model has high clinical value.
Clinical data of 161 patients with pelvic tumors (preoperative DVT group n = 22, non-DVT group n = 139; postoperative DVT group n = 35, NDVT group n = 125; and one case of postoperative pulmonary thrombosis was excluded) were retrospectively analyzed. Age, BMI, disease type, FIGO stage, and coagulation parameters (prothrombin time, PT; activated partial thromboplastin time, APTT; fibrinogen, FIB; D-dimer, D-D; plasminogen activator inhibitor-1, PAI-1) were compared. The key variables were screened using principal component analysis. The prediction model for postoperative DVT was built through logistic regression, and its efficacy was tested using a ROC curve.
PT, D-D, and PAI-1 were significantly higher in the preoperative DVT group than in the non-DVT group (p < 0.001), and APTT was significantly shorter (p = 0.002). The postoperative DVT group was characterized by advanced age (p = 0.032), a higher proportion of ovarian and endometrial cancers, a greater percentage of advanced FIGO stages (p = 0.002), longer postoperative bedtime of more than 72 hours (p = 0.028), and higher levels of PT, FIB, D-D, and PAI-1 (p < 0.001). Principal component analysis showed age and D-D as the main contributing factors. The logistic regression model showed that age (OR = 1.02, p = 0.05), elevated D-D (OR = 1.02, p = 0.001), FIGO stages III and IV (OR = 3.60, p = 0.048), absence of thrombolytic prophylaxis in the postoperative period (OR = 2.85, p = 0.049), and the presence of adjuvant therapy in the postoperative period (OR = 1.02, p = 0.038) were independent risk factors for postoperative DVT, and the AUC of the model reached 0.865 (p < 0.001).
Age, preoperative DVT, D-D level, and tumor stage are independent predictors of postoperative DVT in pelvic tumors. The constructed prediction model has high clinical value.