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Drug-induced liver injury and COVID-19:Use of artificial intelligence and the updated Roussel Uclaf Causality Assessment Method in clinical practice
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作者 Gabriela Xavier Ortiz Ana Helena dias Pereira dos santos Ulbrich +4 位作者 Gabriele Lenhart henrique dias pereirados santos Karin Hepp Schwambach Matheus William Becker Carine Raquel Blatt 《Artificial Intelligence in Gastroenterology》 2023年第2期36-47,共12页
BACKGROUND Liver injury is a relevant condition in coronavirus disease 2019(COVID-19)inpatients.Pathophysiology varies from direct infection by virus,systemic inflammation or drug-induced adverse reaction(DILI).DILI d... BACKGROUND Liver injury is a relevant condition in coronavirus disease 2019(COVID-19)inpatients.Pathophysiology varies from direct infection by virus,systemic inflammation or drug-induced adverse reaction(DILI).DILI detection and monitoring is clinically relevant,as it may contribute to poor prognosis,prolonged hospitalization and increase indirect healthcare costs.Artificial Intelligence(AI)applied in data mining of electronic medical records combining abnormal liver tests,keyword searching tools,and risk factors analysis is a relevant opportunity for early DILI detection by automated algorithms.AIM To describe DILI cases in COVID-19 inpatients detected from data mining in electronic medical records(EMR)using AI and the updated Roussel Uclaf Causality Assessment Method(RUCAM).METHODS The study was conducted in March 2021 in a hospital in southern Brazil.The NoHarm©system uses AI to support decision making in clinical pharmacy.Hospital admissions were 100523 during this period,of which 478 met the inclusion criteria.From these,290 inpatients were excluded due to alternative causes of liver injury and/or due to not having COVID-19.We manually reviewed the EMR of 188 patients for DILI investigation.Absence of clinical information excluded most eligible patients.The DILI assessment causality was possible via the updated RUCAM in 17 patients.RESULTS Mean patient age was 53 years(SD±18.37;range 22-83),most were male(70%),and admitted to the non-intensive care unit sector(65%).Liver injury pattern was mainly mixed,mean time to normalization of liver markers was 10 d,and mean length of hospitalization was 20.5 d(SD±16;range 7-70).Almost all patients recovered from DILI and one patient died of multiple organ failure.There were 31 suspected drugs with the following RUCAM score:Possible(n=24),probable(n=5),and unlikely(n=2).DILI agents in our study were ivermectin,bicalutamide,linezolid,azithromycin,ceftriaxone,amoxicillin-clavulanate,tocilizumab,piperacillin-tazobactam,and albendazole.Lack of essential clinical information excluded most patients.Although rare,DILI is a relevant clinical condition in COVID-19 patients and may contribute to poor prognostics.CONCLUSION The incidence of DILI in COVID-19 inpatients is rare and the absence of relevant clinical information on EMR may underestimate DILI rates.Prospects involve creation and validation of alerts for risk factors in all DILI patients based on RUCAM assessment causality,alterations of liver biomarkers and AI and machine learning. 展开更多
关键词 Chemical and drug induced liver injury RUCAM Artificial intelligence COVID-19 Liver injury
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