Nomogram for predicting difficult total laparoscopic hysterectomy: A multi-institutional, retrospective model development and validation study

Abstract

Background: Total laparoscopic hysterectomy (TLH) is the most commonly performed gynecological surgery. However, the difficulty of the operation varies depending on the patient and surgeon. Subsequently, patient’s outcomes and surgical efficiency are affected. We aimed to develop and validate a pre-operative nomogram to predict the operative difficulty in patients undergoing TLH. Methods: This retrospective study included 663 patients with TLH from XXX Hospital and 102 patients from YYY Hospital in Chongqing, China. A multivariate logistic regression analysis was used to identify the independent predictors of operative difficulty, and a nomogram was constructed. The performance of the nomogram was validated internally and externally. Results: The uterine weight, history of pelvic surgery, presence of adenomyosis, surgeon’s years of practice, and annual hysterectomy volume were identified as significant independent predictors of operative difficulty. The nomogram demonstrated good discrimination in the training dataset (area under the receiver operating characteristic curve [AUC], 0.827 (95% confidence interval [CI], 0.783–0.872), internal validation dataset (AUC, 0.793 [95% CI, 0.714–0.872]), and external validation dataset (AUC, 0.756 [95% CI, 0.658–0.854]). The calibration curves showed good agreement between the predictions and observations for both internal and external validations. Conclusion: The developed nomogram accurately predicted the operative difficulty of TLH, facilitated pre-operative planning and patient counseling, and optimized surgical training. Further prospective multicenter clinical studies are required to optimize and validate this model.