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Background: The aim of this study was to identify a preoperative inflammatory marker with the most predictive value for postoperative complications after pancreaticoduodenectomy (PD). We then combined it with other perioperative variables to construct and validate a nomogram for complications after PD.Methods: A total of 223 patients who received PD from January 2014 to July 2019 at a high-volume (>60 PDs/year) pancreatic centers in China were included in this retrospective study. All of the PDs were performed by the same surgeon who is beyond the learning curve with more than 100 PDs over the previous 3 years before 2014. 15 preoperative inflammatory markers were collected, including neutrophils, lymphocytes, high-sensitivity C-reactive protein and lactic dehydrogenase. The inflammatory markers' predicting abilities for complications were analyzed by calculating the values of an area under the curve (AUC).The complications included surgical complications (such as pancreatic fistula, delayed gastric emptying and bile leakage) and medical complications (such as sepsis, pneumonia, urinary tract infection, acute heart failure and acute liver failure) in this study. Univariable and multivariable logistic regression analyses were performed to investigate the perioperative features for independent risk factors for complications after PD. Nomograms with or without the most predictive inflammatory for complications were subsequently developed based on multivariable logistic regression using Akaike information criterion. Nomograms' performance was quantified and compared in terms of calibration and discrimination. We studied the utility of the nomograms using decision curve analysis.Results: The albumin/ NLR score (ANS) exhibited the highest AUC value (0.616) for predicting postoperative complications. ANS and approach method were identified as independent risk factors for complications. The nomogram with ANS had higher C-index (0.725) and better calibration. The NRI compared between nomograms was 0.160 (95%

Objective To construct and validate a nomogram composed of preoperative variables to predict intraoperative blood transfusion for gastric cancer surgery. Background Intraoperative transfusion for gastric cancer surgery is a common medical procedure that is associated with increased postoperative complications. Methods A total of 999 patients who underwent gastrectomy between January 2010 and June 2019 were randomly allocated into the primary and validation cohorts in a 2:1 ratio. In the primary cohort, logistic analyses were performed to identify independent predictors for transfusion. Using the Akaike information criterion, selected variables were incorporated to construct a nomogram. Validations of the nomogram were performed in the primary and validation cohorts. The discrimination ability of the nomogram was assessed by the concordance index (C‐index), and calibration was assessed by calibration curves and the Hosmer–Lemeshow goodness‐of‐fit test. Results The following risk factors for transfusion were identified and used to construct the nomogram: ASA status (III‐IV vs I‐II: odds ratio [OR] 1.74), comorbidities (yes vs no: OR 1.57), tumour location (diffuse vs lower: OR 4.05), cTNM stage (III vs I: OR 1.95), and a preoperative haemoglobin level less than 80 g/L (vs over 120 g/L: OR 35.30). The C‐index was 0.859 and 0.850 in the primary and validation cohorts, respectively, which both indicated good discrimination of the nomogram. Additionally, both calibration curves and Hosmer–Lemeshow tests (p‐value 0.184 and 0.887, respectively) demonstrated high agreement between the predictions and actual outcomes. Conclusion A nomogram composed of preoperative variables to predict blood transfusion for gastric cancer surgery was effectively developed and validated. This nomogram could be used to improve the utilisation of red blood cells for gastrectomy.