Aileen Scheibner, K. Betthauser, A. Bewley, P. Juang, B. Lizza, S. Micek, P. Lyons
{"title":"机器学习预测感染性休克患者的抗利尿激素反应性","authors":"Aileen Scheibner, K. Betthauser, A. Bewley, P. Juang, B. Lizza, S. Micek, P. Lyons","doi":"10.1002/phar.2683","DOIUrl":null,"url":null,"abstract":"The objective of this study was to develop and externally validate a model to predict adjunctive vasopressin response in patients with septic shock being treated with norepinephrine for bedside use in the intensive care unit.","PeriodicalId":19812,"journal":{"name":"Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Machine learning to predict vasopressin responsiveness in patients with septic shock\",\"authors\":\"Aileen Scheibner, K. Betthauser, A. Bewley, P. Juang, B. Lizza, S. Micek, P. Lyons\",\"doi\":\"10.1002/phar.2683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study was to develop and externally validate a model to predict adjunctive vasopressin response in patients with septic shock being treated with norepinephrine for bedside use in the intensive care unit.\",\"PeriodicalId\":19812,\"journal\":{\"name\":\"Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/phar.2683\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/phar.2683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine learning to predict vasopressin responsiveness in patients with septic shock
The objective of this study was to develop and externally validate a model to predict adjunctive vasopressin response in patients with septic shock being treated with norepinephrine for bedside use in the intensive care unit.