Development of a nomogram for the early prediction of PACU VAS in patients undergoing laparoscopic radical resection of colorectal cancer with fentanyl

INTRODUCTION: To make early predictions of PACU VAS before surgery, we created a novel nomogram for the early prediction of PACU VAS in patients having laparoscopic radical excision of colorectal cancer with fentanyl. METHODS: From July 2018 to December 2020, a total of 101 patients in Zhongshan Hospital Affiliated to Fudan University who underwent laparoscopic radical resection of colorectal cancer were enrolled in this study. For feature selection, a stepwise regression model was utilized. Multivariable logistic regression analysis was used to establish a prediction model. We incorporated age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype, and this was presented with a nomogram. The nomogram's performance was evaluated in terms of discrimination and clinical utility. RESULTS: The signature, which comprised of seven carefully chosen characteristics, was linked to the PACU VAS for the development dataset. Predictors contained in the individualized prediction nomogram included age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype. With an area under the ROC curve of 0.877 (95% CI, 0.6874–1.0000), the model showed good discrimination. The nomogram still had good discrimination. Decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSIONS: The nomogram presented in this study incorporates age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype and can be conveniently used to facilitate the individualized prediction of PACU VAS in patients undergoing laparoscopic radical resection of colorectal cancer with fentanyl.