Effective Prediction Model for Preventing Postoperative Deep Vein Thrombosis During Bladder Cancer Treatment

Overview

Journal J Int Med Res

Publisher Sage Publications

Specialty General Medicine

Date 2022 Jan 6

PMID 34986677

Citations 1

Authors

Xing Liu

Abai Xu

JingWen Huang

Haiyan Shen

Yazhen Liu

Affiliations

Soon will be listed here.

Abstract

Objective: To begin to understand how to prevent deep vein thrombosis (DVT) after an innovative operation termed intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder, we explored the factors that influence DVT following surgery, with the aim of constructing a model for predicting DVT occurrence.

Methods: This retrospective study included 151 bladder cancer patients who underwent intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder. Data describing general clinical characteristics and other common parameters were collected and analyzed. Thereafter, we generated model evaluation curves and finally cross-validated their extrapolations.

Results: Age and body mass index were risk factors for DVT, whereas postoperative use of hemostatic agents and postoperative passive muscle massage were significant protective factors. Model evaluation curves showed that the model had high accuracy and little bias. Cross-validation affirmed the accuracy of our model.

Conclusion: The prediction model constructed herein was highly accurate and had little bias; thus, it can be used to predict the likelihood of developing DVT after surgery.

Citing Articles

Developing and validating risk predicting models to assess venous thromboembolism risk after radical cystectomy.

Lai C, Ji J, Wang M, Hu H, Xu T, Hu H Transl Androl Urol. 2024; 13(9):1823-1834.

PMID: 39434743 PMC: 11491220. DOI: 10.21037/tau-24-194.

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