{"title":"肝硬化腹水患者自发性细菌性腹膜炎的诊断模型:一项多中心队列研究。","authors":"Xuehong Yin,Enqiang Qin,Rui Song,Xuli Bao,Jinling Dong,Wei Hou,Wei Hua,Bo Tu,Yuening Zhang,Qinghua Meng","doi":"10.1097/meg.0000000000002841","DOIUrl":null,"url":null,"abstract":"INTRODUCTION\r\nSpontaneous bacterial peritonitis (SBP) is a potentially life-threatening complication of cirrhotic ascites. Early diagnosis and treatment of SBP are essential to improve the survival rates and prognosis of patients. We aimed to identify the predictors of SBP to establish a new noninvasive early diagnostic tool.\r\n\r\nMETHODS\r\nWe screened 1618 patients who underwent paracentesis due to cirrhotic ascites between January 2017 and December 2018 in three hospitals. We evaluated the symptomatic, clinical, and laboratory parameters to identify the predictors of SBP. The primary diagnostic model was displayed as a nomogram.\r\n\r\nRESULTS\r\nThe model included abdominal pain, diarrhea, white blood cell count, neutrophil percentage, procalcitonin, C-reactive protein, lactate dehydrogenase, glucose, and Model for End-stage Liver Disease score. The model's diagnostic performance was good, with an AUC of 0.84 [95% confidence interval (CI), 0.81-0.87] in the training cohort. In the validation cohort, the diagnostic ability was also good, with AUCs of 0.87 (95% CI, 0.83-0.91) and 0.90 (95% CI, 0.87-0.94) for inner and outer validation queues, respectively. Moreover, the decision curve analysis confirmed the clinical utility of the nomogram model. In addition, we developed a Microsoft Excel calculation model to allow convenient adoption of the model in clinical practice.\r\n\r\nCONCLUSION\r\nWe developed good performing diagnostic models for SBP.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnostic model for spontaneous bacterial peritonitis in cirrhotic patients with ascites: a multicenter cohort study.\",\"authors\":\"Xuehong Yin,Enqiang Qin,Rui Song,Xuli Bao,Jinling Dong,Wei Hou,Wei Hua,Bo Tu,Yuening Zhang,Qinghua Meng\",\"doi\":\"10.1097/meg.0000000000002841\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"INTRODUCTION\\r\\nSpontaneous bacterial peritonitis (SBP) is a potentially life-threatening complication of cirrhotic ascites. Early diagnosis and treatment of SBP are essential to improve the survival rates and prognosis of patients. We aimed to identify the predictors of SBP to establish a new noninvasive early diagnostic tool.\\r\\n\\r\\nMETHODS\\r\\nWe screened 1618 patients who underwent paracentesis due to cirrhotic ascites between January 2017 and December 2018 in three hospitals. We evaluated the symptomatic, clinical, and laboratory parameters to identify the predictors of SBP. The primary diagnostic model was displayed as a nomogram.\\r\\n\\r\\nRESULTS\\r\\nThe model included abdominal pain, diarrhea, white blood cell count, neutrophil percentage, procalcitonin, C-reactive protein, lactate dehydrogenase, glucose, and Model for End-stage Liver Disease score. The model's diagnostic performance was good, with an AUC of 0.84 [95% confidence interval (CI), 0.81-0.87] in the training cohort. In the validation cohort, the diagnostic ability was also good, with AUCs of 0.87 (95% CI, 0.83-0.91) and 0.90 (95% CI, 0.87-0.94) for inner and outer validation queues, respectively. Moreover, the decision curve analysis confirmed the clinical utility of the nomogram model. In addition, we developed a Microsoft Excel calculation model to allow convenient adoption of the model in clinical practice.\\r\\n\\r\\nCONCLUSION\\r\\nWe developed good performing diagnostic models for SBP.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/meg.0000000000002841\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/meg.0000000000002841","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Diagnostic model for spontaneous bacterial peritonitis in cirrhotic patients with ascites: a multicenter cohort study.
INTRODUCTION
Spontaneous bacterial peritonitis (SBP) is a potentially life-threatening complication of cirrhotic ascites. Early diagnosis and treatment of SBP are essential to improve the survival rates and prognosis of patients. We aimed to identify the predictors of SBP to establish a new noninvasive early diagnostic tool.
METHODS
We screened 1618 patients who underwent paracentesis due to cirrhotic ascites between January 2017 and December 2018 in three hospitals. We evaluated the symptomatic, clinical, and laboratory parameters to identify the predictors of SBP. The primary diagnostic model was displayed as a nomogram.
RESULTS
The model included abdominal pain, diarrhea, white blood cell count, neutrophil percentage, procalcitonin, C-reactive protein, lactate dehydrogenase, glucose, and Model for End-stage Liver Disease score. The model's diagnostic performance was good, with an AUC of 0.84 [95% confidence interval (CI), 0.81-0.87] in the training cohort. In the validation cohort, the diagnostic ability was also good, with AUCs of 0.87 (95% CI, 0.83-0.91) and 0.90 (95% CI, 0.87-0.94) for inner and outer validation queues, respectively. Moreover, the decision curve analysis confirmed the clinical utility of the nomogram model. In addition, we developed a Microsoft Excel calculation model to allow convenient adoption of the model in clinical practice.
CONCLUSION
We developed good performing diagnostic models for SBP.