Goldilocks principle of minimally invasive surgery for gastric subepithelial tumors

BACKGROUND Minimally invasive surgery had been tailored to individual cases of gastric subepithelial tumors(SETs)after comparing the clinical outcomes of endoscopic resection(ER),laparoscopic resection(LR),and hybrid methods.AIM To study the use of Goldilocks principle to determine the best form of minimally invasive surgery for gastric SETs.METHODS In this retrospective study,194 patients of gastric SETs with high probability of surgical intervention were included.All patients underwent tumor resection in the operating theater between January 2013 and December 2021.The patients were divided into two groups,ER or LR,according to the tumor characteristics and the initial intent of intervention.Few patients in the ER group required further backup laparoscopic surgery after an incomplete ER.The patients who had converted open surgery were excluded.A logistic regression model was used to assess the associations between patient characteristics and the likelihood of a treatment strategy.The area under the curve was used to assess the discriminative ability of tumor size and Youden’s index to determine the optimal cut-off tumor size.RESULTS One-hundred ninety-four patients(100 in the ER group and 94 in the LR group)underwent tumor resection in the operating theater.In the ER group,27 patients required backup laparoscopic surgery after an incomplete ER.The patients in the ER group had small tumor sizes and shorter procedure durations while the patients in the LR group had large tumor sizes,exophytic growth,malignancy,and tumors that were more often located in the middle or lower third of the stomach.Both groups had similar durations of hospital stays and a similar rate of major postoperative complications.The patients in the ER group who underwent backup surgery required longer procedures(56.4 min)and prolonged stays(2 d)compared to the patients in the LR group without the increased rate of major postoperative complications.The optimal cut-off point for the tumor size for laparoscopic surgery was 2.15 cm.CONCLUSION Multidisciplinary teamwork leads to the adoption of different strategies to yield efficient clinical outcomes according to the tumor characteristics.

Risk factors and prediction score for chronic pancreatitis: A nationwide population-based cohort study

AIM To explore the risk factors of developing chronic pancreatitis(CP) in patients with acute pancreatitis(AP) and develop a prediction score for CP.METHODS Using the National Health Insurance Research Database in Taiwan, we obtained large, population-based data of 5971 eligible patients diagnosed with AP from 2000 to 2013. After excluding patients with obstructive pancreatitis and biliary pancreatitis and those with a follow-up period of less than 1 year, we conducted a multivariate analysis using the data of 3739 patients to identify the risk factors of CP and subsequently develop a scoring system that could predict the development of CP in patients with AP. In addition, we validated the scoring system using a validation cohort.RESULTS Among the study subjects, 142 patients(12.98%) devel-oped CP among patients with RAP. On the other hand, only 32 patients(1.21%) developed CP among patients with only one episode of AP. The multivariate analysis revealed that the presence of recurrent AP(RAP), alcoholism, smoking habit, and age of onset of < 55 years were the four important risk factors for CP. We developed a scoring system(risk score 1 and risk score 2) from the derivation cohort by classifying the patients into low-risk, moderate-risk, and high-risk categories based on similar magnitudes of hazard and validated the performance using another validation cohort. Using the prediction score model, the area under the curve(AUC) [95% confidence interval(CI)] in predicting the 5-year CP incidence in risk score 1(without the number of AP episodes) was 0.83(0.79, 0.87), whereas the AUC(95%CI) in risk score 2(including the number of AP episodes) was 0.84(0.80, 0.88). This result demonstrated that the risk score 2 has somewhat better prediction performance than risk score 1. However, both of them had similar performance between the derivation and validation cohorts.CONCLUSION In the study,we identified the risk factors of CP and developed a prediction score model for CP.