{"title":"内镜逆行胆管造影患者术前胃潴留:评估风险和优化结果。","authors":"Nuo-Ya Zhou, Bing Hu","doi":"10.4240/wjgs.v16.i12.3655","DOIUrl":null,"url":null,"abstract":"<p><p>This article is a comment on the article by Jia <i>et al</i>, aiming at establishing a predictive model to predict the occurrence of preoperative gastric retention in endoscopic retrograde cholangiopancreatography preparation. We share our perspectives on this predictive model. First, further differentiation in predicting the severity of gastric retention could enhance clinical outcomes. Second, we ponder whether this predictive model can be generalized to predictions of gastric retention before various endoscopic procedures. Third, large datasets and prospective clinical validation are needed to improve the prediction model.</p>","PeriodicalId":23759,"journal":{"name":"World Journal of Gastrointestinal Surgery","volume":"16 12","pages":"3655-3657"},"PeriodicalIF":1.8000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11650241/pdf/","citationCount":"0","resultStr":"{\"title\":\"Preoperative gastric retention in endoscopic retrograde cholangiopancreatography patients: Assessing risks and optimizing outcomes.\",\"authors\":\"Nuo-Ya Zhou, Bing Hu\",\"doi\":\"10.4240/wjgs.v16.i12.3655\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This article is a comment on the article by Jia <i>et al</i>, aiming at establishing a predictive model to predict the occurrence of preoperative gastric retention in endoscopic retrograde cholangiopancreatography preparation. We share our perspectives on this predictive model. First, further differentiation in predicting the severity of gastric retention could enhance clinical outcomes. Second, we ponder whether this predictive model can be generalized to predictions of gastric retention before various endoscopic procedures. Third, large datasets and prospective clinical validation are needed to improve the prediction model.</p>\",\"PeriodicalId\":23759,\"journal\":{\"name\":\"World Journal of Gastrointestinal Surgery\",\"volume\":\"16 12\",\"pages\":\"3655-3657\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11650241/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"World Journal of Gastrointestinal Surgery\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4240/wjgs.v16.i12.3655\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Journal of Gastrointestinal Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4240/wjgs.v16.i12.3655","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/27 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Preoperative gastric retention in endoscopic retrograde cholangiopancreatography patients: Assessing risks and optimizing outcomes.
This article is a comment on the article by Jia et al, aiming at establishing a predictive model to predict the occurrence of preoperative gastric retention in endoscopic retrograde cholangiopancreatography preparation. We share our perspectives on this predictive model. First, further differentiation in predicting the severity of gastric retention could enhance clinical outcomes. Second, we ponder whether this predictive model can be generalized to predictions of gastric retention before various endoscopic procedures. Third, large datasets and prospective clinical validation are needed to improve the prediction model.