PT  - JOURNAL ARTICLE
AU  - Sha Dou
AU  - Junchen Chen
AU  - Yuanfen Wang
AU  - Chongyuan Zhu
AU  - Heng Cui
AU  - Yi Li
TI  - Risk factors of major intraoperative blood loss at primary debulking surgery for ovarian cancer
AID  - 10.1016/j.gocm.2022.01.004
DP  - 2022 Mar 01
TA  - Gynecology and Obstetrics Clinical Medicine
PG  - 9--13
VI  - 2
IP  - 1
4099  - http://gocm.bmj.com/content/2/1/9.short
4100  - http://gocm.bmj.com/content/2/1/9.full
SO  - gocm2022 Mar 01; 2
AB  - Objective The goal of this study was to find the risk factors for major intraoperative blood loss (MBL) of primary debulking surgery (PDS) for ovarian cancer.Methods Patients with ovarian cancer who underwent PDS in our hospital, from 2010 to 2017, were enrolled. The association between risk factors and MBL was modeled with the use of logistic regression. Receiver operating characteristic (ROC) curve analysis was used to determine the predictive value of the logistic regression model.Results A total of 346 patients met the inclusion criteria. There were 150 patients with MBL. Tumor stage 3/4 (P ​< ​0.001), American Society of Anesthesiologists (ASA) score ≥3 (P ​= ​0.044), ascites volume ≥500 ​ml ​(P ​= ​0.002), radical or ultra-radical surgery (P ​= ​0.002), and diabetes (P ​= ​0.035) were independent risk factors for MBL in patients with ovarian cancer. The logistic regression combined model of these five factors is more reliable in the prediction of MBL with an area under the ROC curve of 0.729 than the tumor stage (ROC curve ​= ​0.645) and surgical complexity (ROC curve ​= ​0.568).Conclusion In patients with ovarian cancer, five risk factors for major intraoperative bleeding were identified. Planned surgical procedures and preoperative risk factors can be used to predict perioperative blood requirements.Our study first demonstrated the risk factors for major intraoperative bleeding in EOC patients undergoing PDS.The occurrence of intraoperative blood loss of at least 1000ml was associated with tumor stage, surgical complexity, ascites, ASA score, and diabetes.The ROC curves indicated that integrating these predictors into a single prediction system, logistic regression was more reliably predicted than tumor stage and surgical complexity.