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We explored the predictive value of various inflammatory-nutritional indicators for postoperative quality of life (QoL) in gastric cancer (GC) patients undergoing laparoscopic distal gastrectomy (LDG) and developed a novel inflammatory-nutritional score (INS). In this study, 156 GC patients who underwent LDG were included. We used multiple linear regression to analyze the correlation between postoperative QoL and inflammatory-nutritional indicators. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to construct INS. Hemoglobin was positively correlated with physical functioning (β =8.5; p = 0.003) and cognitive functioning (β = 3.5; p = 0.038) 3 mo, after surgery. Prognostic nutritional index (PNI) was positively associated with global health status (β =5.8; p = 0.043). Albumin-alkaline phosphatase ratio (AAPR) was negatively correlated with emotional functioning 12 mo, after surgery (β = −5.7; p = 0.024). Neutrophil-lymphocyte ratio (NLR), Lymphocyte- monocyte ratio (LMR), AAPR, hemoglobin and PNI were selected using LASSO regression analysis to construct INS. The C-index values of the model in the training group and the validation group were 0.806 (95% CI, 0.719-0.893) and 0.758 (95% CI: 0.591-0.925), respectively. INS had particular predictive value for postoperative QoL in patients undergoing LDG and provided a reference for risk stratification and clinical practice. [ABSTRACT FROM AUTHOR]

Background.Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity.Methods.We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system.Results.Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation,p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed,p= 1/(1 + e(4.810–1.287X1–0.504X2–0.500X3–0.474X4–0.405X5–0.318X6–0.316X7–0.305X8–0.278X9–0.255X10–0.138X11)). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively.Conclusions.This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient’s risk factors, estimate patients’ risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups. [ABSTRACT FROM AUTHOR]