Early Diagnosis of Anastomotic Leakage After Gastric Cancer Surgery Via Analysis of Inflammatory Factors in Abdominal Drainage

Background Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage. Methods We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort. Results Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort. Conclusions Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs.

Automated summary

This study aimed to develop clinically tools for early detection of anastomotic leakage (AL) by analyzing inflammatory factors (IFs) in abdominal drainage. The research proposed an Anastomotic Score system (AScore-POD3) based on IFs with high diagnostic efficacy, which was validated in an independent cohort. A nomogram combining AScore-POD3 with other clinical risk factors showed high C-index, suggesting the potential for early diagnosis of AL after gastric cancer surgery.