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首页> 外文期刊>Journal of International Medical Research >Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment
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Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment

机译：防止膀胱癌治疗期间术后深静脉血栓形成的有效预测模型

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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.
机译：目的首先要预防深静脉血栓形成（DVT）在创新的术语中被称为肱骨体内的腹腔镜新玻璃，我们探讨了影响手术后患者的因素，目的是构建预测DVT发生的模型。方法包括该回顾性研究包括151例膀胱癌患者，患有体内腹腔镜重建的癫痫素内囊性。收集和分析描述一般临床特征和其他常见参数的数据。此后，我们生成了模型评估曲线，最后交叉验证了它们的外推。结果年龄和体重指数是DVT的危险因素，而术后使用止血剂和术后被动肌肉按摩是显着的保护性因素。模型评估曲线表明，该模型具有高精度和小偏差。交叉验证肯定了模型的准确性。结论本文构建的预测模型非常准确，偏差小;因此，它可用于预测手术后显影DVT的可能性。

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