Nomogram for Predicting Infectious Complications Following Curative Gastrectomy Using Clinical and Laboratory Parameters.

Abstract

Postoperative infectious complications are prevalent and significantly impact the prognosis and hospital stay duration after curative gastrectomy. This study aimed to identify predictive factors and develop a nomogram for predicting infectious complications prior to patient discharge. Between April 2019 and December 2023, clinicopathological data of 237 patients with gastric cancer who underwent curative gastrectomy at the Eunpyeong St. Mary's Hospital were retrospectively reviewed. C-reactive protein (CRP), white blood cell (WBC) count, neutrophil-lymphocyte ratio (NLR), and procalcitonin (PCT) levels were analyzed. Overall, 58 patients experienced postoperative complications, with 33 patients developing infectious complications. Univariate analysis revealed that the open approach, esophagus involving resection, advanced stage, and operation time were risk factors for infectious complications among clinicopathologic characteristics. Significant associations with laboratory parameters and body temperature (BT) were observed from postoperative day (POD) 1 to 5, with the highest area under the curve (AUC) observed for POD 5 data in receiver operating characteristic (ROC) analysis. Multivariate analysis incorporating clinicopathologic features and laboratory parameters on POD 5 identified age (OR=2.98), approach (OR=4.05), operation time (OR=2.74), WBC count (OR=4.09), NLR (OR=9.74), and CRP (OR=2.62) as selected factors. The developed nomogram stratified patients into low-risk (<10%), intermediate-risk (10~50%), and high-risk (≥50%) groups, corresponding to actual infectious complication rates of 1.84%, 28.3%, and 71.43%, respectively. This study presents a novel estimating model for infectious complications following curative gastrectomy. The utilization of this model in patient discharge planning can aid in identifying individuals who require additional treatment, thereby minimizing unexpected readmissions.