Development and Empirical Study of a Lower Extremity Deep Vein Thrombosis Prevention Protocol for Patients Undergoing Gynecologic Laparoscopic Surgery.

Objective

This study investigates risk factors for lower extremity deep vein thrombosis (LEDVT) after gynecologic laparoscopy and develops a predictive model.

Methods

The Delphi method was used in expert opinion to identify risk factors for LEDVT. Patients undergoing gynecologic laparoscopic surgery from January 2018 to June 2023 were divided into LEDVT and non-LEDVT groups and matched as a ratio of 1:3. A nomogram model for LEDVT was established and compared to Caprini and G-Caprini scores.

Results

A total of 191 patients with LEDVT and 573 matched patients without LEDVT were included. Multivariate logistic regression analysis showed that older age (OR = 1.146, P < 0.001), history of varicose veins (OR = 6.721, P = 0.011), gynecological malignancies (OR = 8.053, P < 0.001), longer operation time (OR = 1.010, P < 0.001), longer postoperative bed rest time (OR = 99.406, P < 0.001), without postoperative anticoagulation (OR = 0.282, P = 0.042), higher D-dimer (OR = 1.145, P = 0.015), lower direct bilirubin (OR = 0.715, P = 0.006) and lower hemoglobin (OR = 0.982, P = 0.016) are independent risk factors for LEDVT in patients undergoing gynecologic laparoscopic surgery. A nomogram model was established with an area under the receiver operating characteristic curve of 0.839, sensitivity of 78.0%, and specificity of 76.1%. Validation set showed that this predictive model had an ROC of 0.954, sensitivity of 92.6% and specificity of 96.7%.

Conclusion

A nomogram model that includes age, history of varicose veins, gynecologic malignancies, operation time, postoperative bed rest time, postoperative anticoagulation, D-dimer, direct bilirubin, and hemoglobin could effectively predict the risk of LEDVT in patients undergoing gynecologic laparoscopic surgery. The current nomogram model potentially helps to reduce the incidence of LEDVT and improve the quality of life.