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Clavien–Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer

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Abstract

Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien–Dindo classification (CDC) has been applied in a variety of surgical fields. This study is designed to evaluate the complications after robot-assisted radical hysterectomy (RRH) for cervical cancer using CDC and further establish a prediction model. This is a study on the development of prediction model based on retrospective data. Patients with cervical cancer who received RRH treatment in our hospital from January 2016 to April 2019 were invited to participate in the study. The demographic data, laboratory and imaging examination results and postoperative complications were collected, and the logistic regression model was applied to analyze the risk factors possibly related to complications to establish a prediction model. 753 patients received RRH. The overall incidence of complications was 32.7%, most of which were grade I and grade II (accounting for 30.6%). The results of multivariate analysis showed that the preoperative neoadjuvant chemotherapy (OR = 1.693, 95%CI: 1.210–2.370, P = 0.002), preoperative ALT (OR = 1.028, 95%CI: 1.017–1.039, P < 0.001), preoperative urea nitrogen (OR = 0.868, 95%CI: 0.773–0.974, P = 0.016), preoperative total bilirubin (OR = 0.958, 95%CI: 0.925–0.993, P = 0.0.018), and preoperative albumin (OR = 0.937, 95%CI: 0.898–0.979, P = 0.003) were related to the occurrence of postoperative complications. The area under the curve (AUC) of receiver-operating characteristic (ROC) in the prediction model of RRH postoperative complications established based on these five factors was 0.827 with 95% CI of 0.794–0.860. In patients undergoing robot-assisted radical hysterectomy for cervical cancer, preoperative ALT level, urea nitrogen level, total bilirubin level, albumin level, and neoadjuvant chemotherapy were significantly related to the occurrence of postoperative complications. The regression prediction model established on this basis showed good prediction performance with certain clinical promotion and reference value.

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Authors and Affiliations

  1. The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, People’s Republic of China

    Hao Ling, Guohui Wang, Bo Yi, Zheng Li & Shaihong Zhu

  2. College of Mechanical and Electrical Engineering, Central South University, Changsha, 410082, Hunan, People’s Republic of China

    Hao Ling

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by HL, GW, BY and ZL. The first draft of the manuscript was written by HL and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Shaihong Zhu.

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Conflict of interest

Dr. Hao Ling is a key opinion leader for this study. Guohui Wang, Bo Yi, Zheng Li, and Shaihong Zhu have no conflicts of interest to disclose.

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This research study was conducted retrospectively from data obtained for clinical purposes. This study has been approved by the research ethics committee of the Third Xiangya Hospital, Central South University.

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Ling, H., Wang, G., Yi, B. et al. Clavien–Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer. J Robotic Surg 17, 527–536 (2023). https://doi.org/10.1007/s11701-022-01450-5

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