Association between Postoperative Anastomotic Leakage and Dynamic Changes of SII Score in Esophageal Cancer Patients With Neoadjuvant Chemoradiotherapy - A two-center study
Wei, M.; Wei, M.; Zhang, H.; Yuan, M.; Zhang, z.
Show abstract
ObjectiveTo investigate the correlation between postoperative anastomotic leakage (AOL) and dynamic changes in systemic immune inflammatory index (SII) scores in esophageal cancer patients undergoing neoadjuvant chemoradiotherapy (NAC-CA) after surgery. MethodsA retrospective analysis was conducted on 247 esophageal cancer patients who underwent NAC-CA surgery at Fujian Medical University Union Hospital and Yantai Affiliated Hospital of Binzhou Medical University (two centers) from January 2021 to December 2023. Patients were classified into two groups based on postoperative AOL occurrence: leakage group (38 cases) and non-leakage group (209 cases). The study compared general demographics and dynamic SII scores (preoperative, postoperative day 1, day 3, day 7) between groups, and performed multivariate logistic regression analysis to identify independent risk factors for AOL development. ResultsThe leakage group showed significantly higher rates of age, hypertension prevalence, and dynamic SII scores (especially postoperative day 3) compared to the non-leakage group (P<0.05). The SII score of the leakage group peaked on postoperative day 3 (1897.0{+/-}592.9), which was significantly higher than that of the non-leakage group (1144.5{+/-}316.7) on the same day. Multivariate logistic regression analysis revealed that age (OR=1.05,95% CI=1.02-1.08, P=0.00), hypertension (OR=2.49,95%CI=1.09-5.67, P=0.03), and postoperative day 3 SII score (OR=1.003,95%CI=1.003-1.004, P=0.00) were independent risk factors for AOL. ConclusionDynamic changes of SII scores in esophageal cancer patients undergoing NAC-CA are closely associated with AOL occurrence, and the postoperative day 3 SII score is the most valuable predictor for assessing postoperative leakage risk.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Machine learning based prediction of recurrence after curative resection for rectal cancer 96%
- The safety and efficacy of remimazolam tosylate combined with propofol in upper gastrointestinal endoscopy: a multicenter, randomized clinical trial 96%
- Association between Intraoperative End-Tidal Carbon Dioxide and Postoperative Organ Dysfunction in Major Abdominal Surgery: A Retrospective Cohort Study 95%
Similar papers in this journal
- Systems biomedicine of primary and metastatic colorectal cancer reveals potential therapeutic targets 93%
- miR-100-5p downregulates mTOR to suppress the proliferation, migration and invasion of prostate cancer cells 93%
- Cyclin G2 inhibits oral squamous cell carcinoma growth and metastasis by binding to insulin-like growth factor binding protein 3 and regulating the FAK-SRC-STAT signaling pathway 93%
Similar papers in this journal
- Improvement of Survival Outcomes of Cholangiocarcinoma by Ultrasonography Surveillance: Multicenter Retrospective Cohorts 96%
- ChatGPT achieves comparable accuracy to specialist physicians in predicting the efficacy of high-flow oxygen therapy 93%
- Screening of plasma IL-6 and IL-17 in Bangladeshi lung cancer patients 92%
Similar papers in this journal
- PDAC-ANN: an artificial neural network to predict Pancreatic Ductal Adenocarcinoma based on gene expression 95%
- Translational control of Bcl-2 promotes apoptosis of gastric carcinoma cells 94%
- Comparative Immune profiling in Pancreatic Ductal Adenocarcinoma Progression Among South African patients 94%
Similar papers in this journal
- Effects of different environmental intervention durations on the intestinal mucosal barrier and the brain-gut axis in rats with colorectal cancer 95%
- Combined DeRitis ratio and alkaline phosphatase on the Prediction of Portal Vein Tumor Thrombosis in Patients with Hepatocellular Carcinoma 95%
- Genetic Risk Factors for Colorectal Cancer in Multiethnic Indonesians 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.