Objective To explore the application of combined optimized machine learning algorithm for predicting the risk model of postoperative infectious complications of gastric cancer and to compare the accuracy with other algorithms, so as to find reliable biomarkers for early diagnosis of postoperative infection of gastric cancer. Methods The clinical data of 420 patients with gastric cancer at the Third Affiliated Hospital of Anhui Medical University from May 2018 to April 2023 were retrospectively analyzed and the patients were randomly divided into training set and validation set. Univariate analysis was used to determine the risk factors of postoperative infectious complications. Six conventional machine learning models are constructed using the training set: linear regression, random forest, SVM, BP, LGBM, XGBoost, and MGA-XGBoost model. The validation set was used to evaluate the seven models through evaluation indicators such as ACC, precision, ROC and AUC. Results Postoperative infectious complications were significantly correlated with age, operation time, diabetes, extent of resection, combined resection, stage, preoperative albumin, perioperative blood transfusion, preoperative PNI, LCR and LMR. Among the seven machine learning models, the MGA-XGBoost model performed best. Among the seven machine learning models, the MGA-XGBoost model performed best, with AUC of 0.936, ACC of 0.889, recall of 0.6, F1-score of 0.682, and precision of 0.79 on the validation set. Diabetes had the greatest influence on the internal structure of the model. Conclusion This study proves that the MGA-XGBoost model incorporating comprehensive inflammation indicators can predict postoperative infectious complications in patients with gastric cancer.
ObjectiveTo assess whether pre-operative use of infliximab (IFX) will increase the risk of post-operative infectious complications in patients with inflammatory bowel disease (IBD). MethodsPubmed, Web of Science, CBM, CNKI and Wanfang database were searched for all the trials that investigated the effects of infliximab on postoperative infectious complication rates in patients with IBD between January 1990 and April 2013. Two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted data and assessed the quality of the included studies. Then, meta-analysis was performed using RevMan 5.1 software. ResultsTotally, 14 cohort studies were finally included in the review. There was no significant difference on infectious complications [RR=0.99, 95%CI (0.47, 2.07), P=0.97] between IFX groups and control groups with ulcerative colitis. The same results were found in patients with Crohn's disease on infectious complications [RR=1.32, 95%CI (0.87, 1.98), P=0.19]. ConclusionPre-operative infliximab use is safe and does not increase the risk of post-operative infectious complications in patients with IBD.
The global incidence of urolithiasis continues to rise. Although surgical treatment is highly effective, postoperative infectious complications remain common and can be life-threatening. Reducing infection risk in high-risk patients, improving surgical safety, and decreasing antimicrobial resistance are urgent issues in urolithiasis surgery. This study constructs a perioperative infection prevention and control framework based on the correlation between surgical approaches, patient immunity, stone characteristics, and urinary microbiota. By standardizing preoperative evaluation, intraoperative procedures, and postoperative monitoring, combined with risk stratification and precise antibiotic use, perioperative management is optimized to enhance surgical safety and provide practical perioperative infection control strategies for urolithiasis in clinical practice.