The continuous data are reported as the means ± SD, and the differences between the groups were analyzed using t-tests. The categorical data are presented as the proportion and percentage, analyzed using the chi-square test or Fisher’s exact test. The variables in the models reaching P < 0.05 in the univariate analysis were subsequently included in a multivariate binary logistic regression model. The variables that remained significant in the multivariate analysis were used to construct a scoring system to classify patients into groups based on their risk for laparoscopic hemostasis. The results of the multivariate analyses are expressed as odds ratios (ORs) with corresponding 95% confidence intervals (95%CIs). A goodness-of-fit test was conducted to assess how well the model could discriminate between patients with and without No. 10 LN metastasis. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses were used to determine the adequacy of the prediction models. Values of 0.7 and higher were considered clinically significant . The model calibration, or the degree to which the observed outcomes were similar to the outcomes predicted by the model across patients, was examined by comparing the observed averages with the predicted averages within each subgroup, arranged in increasing order of patient risk. Values of P < 0.05 were considered statistically significant. The statistical analyses were performed using SPSS version 18.0 (SPSS, Chicago, IL, USA).