A novel preoperative scoring system to predict technical difficulty in laparoscopic splenectomy for non-traumatic diseases

Laparoscopic splenectomy (LS) has been proven to be a safe and advantageous procedure. To ensure that resections of appropriate difficulty are selected, an objective preoperative grading of difficulty is required. We aimed to develop a predictive difficulty grading of LS based on intraoperative complications.

A total of 272 non-traumatic patients who underwent LS were identified from a regional medical center. Patients were randomized into a training cohort (n = 222) and a validation cohort (n = 50). Data on demographics, medical and surgical history, operative and pathological characteristics, and postoperative outcome details were collected. Univariate and multivariate analyses of risk factors for intraoperative complications were performed to develop a difficulty scoring system. The Spearman correlation coefficient was used to evaluate the relationship between the difficulty grading score and intraoperative outcomes. Receiver operating characteristic (ROC) curve was used to evaluate the discriminatory power of this scoring system.

Three preoperative factors (spleen weight, esophagogastric varices, and INR) had a significant effect on operative time, bleeding, and conversion to open surgery. We created a difficulty grading score with three levels of difficulty: low (≤ 4 points), medium (5–6 points), and high (≥ 7 points), based on the three preoperative parameters. The correlation was highly significant (P < 0.01) according to Spearman’s correlation. The area under the ROC curve was 0.695 (95% CI 0.630–0.755). The external validation showed significant correlations with the present model, with an AUC of 0.725 (95% CI 0.580–0.842). The comparison between our difficulty score and the previous grading system in the 272-patient cohort presented a significant difference in the AUC (0.701, 95% CI 0.643–0.755 vs. 0.644, 95% CI 0.584–0.701, P = 0.0452).

The present difficulty scoring system, based on preoperative factors, has good performance in predicting the risk of intraoperative complications of LS and could be helpful for enabling appropriate case selection with respect to the current experience of a surgeon.