Jiang Xiao-Xiang, Li Xiao-Yan, Zhang Jun, Wang Xiao-Xiao, Lin Chao-Qin
Department of Obstetrics and Gynecology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Int J Gynaecol Obstet. 2022 Sep;158(3):689-699. doi: 10.1002/ijgo.14061. Epub 2021 Dec 23.
To explore independent factors influencing the risk of lower extremity deep vein thrombosis during the postoperative period in patients with gynecological malignancies by constructing a predictive model.
In our study, we collected 573 patients with gynecological malignancies in the postoperative period between September 2016 and September 2020, who were divided into a modeling (n = 402) and verification group (n = 171) according to a ratio of 7:3. Univariate and multivariate regression analyses were used to determine independent factors influencing deep vein thrombosis (DVT). A nomogram model was created and a risk score was calculated.
Multivariate regression analysis showed that the independent factors affecting DVT among these patients included age, hyperlipidemia, abnormal uterine bleeding, degree of anemia, D-dimer, operation time, and intraoperative blood loss. By incorporating these factors into a nomogram, we determined that the C-index and calibration curve of the two groups both showed that the model distinguishes and fits well. Further comparing between the high- and low-risk groups, we found that the model has favorable predictive performance.
The predictive nomogram for the risk of DVT in patients with gynecological malignancies in the postoperative period demonstrated good calibration and recognition accuracy. Further independent research is necessary to verify our results.
通过构建预测模型，探讨影响妇科恶性肿瘤患者术后下肢深静脉血栓形成风险的独立因素。
本研究收集了2016年9月至2020年9月期间573例妇科恶性肿瘤术后患者，按照7:3的比例分为建模组（n = 402）和验证组（n = 171）。采用单因素和多因素回归分析确定影响深静脉血栓形成（DVT）的独立因素。创建列线图模型并计算风险评分。
多因素回归分析显示，这些患者中影响DVT的独立因素包括年龄、高脂血症、子宫异常出血、贫血程度、D-二聚体、手术时间和术中失血量。通过将这些因素纳入列线图，我们确定两组的C指数和校准曲线均表明该模型具有良好的区分度和拟合度。进一步比较高风险组和低风险组，我们发现该模型具有良好的预测性能。
妇科恶性肿瘤患者术后DVT风险预测列线图显示出良好的校准度和识别准确性。需要进一步的独立研究来验证我们的结果。
