Background: This study aimed to establish machine learning models for preoperative prediction of the pathological types of acute appendicitis.Methods: Based on histopathology, 136 patients with acute appendicitis were included and divided into three types: acute simple appendicitis (SA, n=8), acute purulent appendicitis (PA, n=104), and acute gangrenous or perforated appendicitis (GPA, n=24). Patients with SA/PA and PA/GPA were divided into training (70%) and testing (30%) sets. Statistically significant features (P<0.05) for pathology prediction were selected by univariate analysis. According to clinical and laboratory data, machine learning logistic regression (LR) models were built. Area under receiver operating characteristic curve (AUC) was used for model assessment.Results: Nausea and vomiting, abdominal pain time, neutrophils (NE), CD4 + T cell, helper T cell, B lymphocyte, natural killer (NK) cell counts, and CD4 + /CD8 + ratio were selected features for the SA/ PA group (P<0.05). Nausea and vomiting, abdominal pain time, the highest temperature, CD8 + T cell, procalcitonin (PCT), and C-reactive protein (CRP) were selected features for the PA/GPA group (P<0.05).By using LR models, the blood markers can distinguish SA and PA (training AUC =0.904, testing AUC =0.910). To introduce additional clinical features, the AUC for the testing set increased to 0.926. In the PA/ GPA prediction model, AUC with blood biomarkers was 0.834 for the training and 0.821 for the testing set.Combining with clinical features, the AUC for the testing set increased to 0.854.Conclusions: Peripheral blood biomarkers can predict the pathological type of SA from PA and GPA.Introducing clinical symptoms could further improve the prediction performance.

Background: With the popularization of Enhanced Recovery After Surgery (ERAS), identifying patients with complications before discharging becomes important. This study aimed to explore the efficacy of C-reactive protein (CRP) in predicting infectious complications after gastrectomy. Methods: Patients with gastric cancer who underwent gastrectomy at Beijing Cancer Hospital from March 2017 to April 2018 were enrolled in the training set. Complications were prospectively registered. Receiver operating characteristic analysis was performed to assess the diagnostic accuracy of CRP via evaluating the area under the curve (AUC). Patients who had CRP tested on postoperative day (POD) 5 and accepted gastrectomy from April to December 2018 were included in the validation set to validate the cut-off value of CRP obtained from the training set. Results: A total of 350 patients were included (263 patients in the training set and 87 patients in the validation set). Out of these, 24 patients were diagnosed with infectious complications and 17 patients had anastomotic leakage in the training set. The CRP level on POD5 had superior diagnostic accuracy for infectious complications with an AUC of 0.81. The cut-off value of CRP on POD5 at 166.65 mg/L yielded 93% specificity and 97.2% negative predict value (NPV); For anastomotic leakage, the AUC of CRP on POD5 was 0.81. Using the cut-off value of CRP at 166.65 mg/L on POD5 achieved 92% specificity and 98.6% NPV. The optimal cut-off value (CRP 166.65 mg/L on POD5) was validated in the validation set. It achieved 97.5% specificity and 94.0% NPV for infectious complications, and 97.6% specificity and 96.4% NPV for anastomotic leakage. Conclusion: CRP is a reliable predictive marker for the diagnosis of inflammatory complications following gastric surgery. However, this study was based on preliminary data. The validity of this data needs confirmation by a larger number of cases.

Background: Enhanced recovery after surgery (ERAS) program has become the main trend in gastrointestinal surgery. The aim of this study is to investigate factors in uencing the decision-making of nasogastric tube (NGT) placement and its safety and e cacy in clinical practice.Methods: We analyzed our prospectively maintained database including 287 patients underwent elective gastrectomy in our department from January 1 to December 31, 2017. All cases were divided into two groups, namely, the non-nasogastric tube group and the nasogastric tube group. Logistic regression was used to analyze the factors that affect the decision of nasogastric tube placement, and propensity score matching (PSM) was later applied to balance those factors for the analysis of the safety outcomes between the groups.Results: Multivariate analysis showed that resection range ( p =0.004, proximal gastrectomy: OR=4.555, 95%CI=1.392-14.905, p =0.016; total gastrectomy: OR=1.990, 95%CI=1.205-3.287, p =0.009) was the only independent risk factors of nasogastric tube placement. NGT was omitted in the majority (58.8%) of distal gastrectomy, but only in 42.5% and 25% in total and proximal gastrectomy. After PSM, we found no signi cant differences between patients with or without NGT in postoperative hospital stay, time to rst atus and defecation, time to uid and semi-uid diet, rate of reinsertion, or hospitalization expenditure (p>0.05 respectively). The incidence of postoperative complications in the two groups were 21.7% and 23.5% respectively ( p =0.753), and the incidence of major complications were 7.0% and 9.6% ( p =0.472). Conclusions:The decision-making of NGT placement is mainly in uenced by the resection range.Omitting NGT is a safe approach in all types of gastrectomy but was not able to enhance the recovery in our practice.

Background: Enhanced recovery after surgery (ERAS) program has become the main trend in gastrointestinal surgery. The aim of this study is to investigate factors influencing the decision-making of nasogastric tube (NGT) placement and its safety and efficacy in clinical practice. Methods: We analyzed our prospectively maintained database including 287 patients underwent elective gastrectomy in our department from January 1 to December 31, 2017. All cases were divided into two groups, namely, the non-nasogastric tube group and the nasogastric tube group. Logistic regression was used to analyze the factors that affect the decision of nasogastric tube placement, and propensity score matching (PSM) was later applied to balance those factors for the analysis of the safety outcomes between the groups. Results: Multivariate analysis showed that resection range (p=0.004, proximal gastrectomy: OR=4.555, 95%CI=1.392-14.905, p=0.016; total gastrectomy: OR=1.990, 95%CI=1.205-3.287, p=0.009) was the only independent risk factors of nasogastric tube placement. NGT was omitted in the majority (58.8%) of distal gastrectomy, but only in 42.5% and 25% in total and proximal gastrectomy. After PSM, we found no significant differences between patients with or without NGT in postoperative hospital stay, time to first flatus and defecation, time to fluid and semi-fluid diet, rate of reinsertion, or hospitalization expenditure (p>0.05 respectively). The incidence of postoperative complications in the two groups were 21.7% and 23.5% respectively (p=0.753), and the incidence of major complications were 7.0% and 9.6% (p=0.472). Conclusions: The decision-making of NGT placement is mainly influenced by the resection range. Omitting NGT is a safe approach in all types of gastrectomy but was not able to enhance the recovery in our practice.