Victor Iapascurta, Ion Fiodorov, Adrian Belii, Viorel Bostan
{"title":"Multi-Agent Approach for Sepsis Management.","authors":"Victor Iapascurta, Ion Fiodorov, Adrian Belii, Viorel Bostan","doi":"10.4258/hir.2025.31.2.209","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The high incidence of sepsis necessitates the development of practical decision-making tools for intensivists, especially during the early, critical phases of management. This study evaluates a multi-agent system intended to assist clinicians with antibiotic therapy and adherence to current sepsis management guidelines before diagnostic results become available.</p><p><strong>Methods: </strong>A multi-agent system incorporating three specialized agents was developed: a sepsis management agent, an antibiotic recommendation agent, and a sepsis guidelines compliance agent. A sepsis case from the MIMIC IV database, organized as a clinical vignette, was used to integrate and test these agents for generating management recommendations. The system leverages retrieval-augmented generation to improve decision-making through the integration of current literature and guidelines.</p><p><strong>Results: </strong>The application produced management recommendations for a sepsis case associated with pneumonia, including early initiation of broad-spectrum antibiotics and close monitoring for clinical deterioration. Two expert intensivists evaluated these recommendations as \"acceptable\" and reported moderate interrater agreement (Cohen's kappa = 0.622, p = 0.003) across various aspects of recommendation usefulness.</p><p><strong>Conclusions: </strong>The multi-agent system shows promise in enhancing decision-making for sepsis management by optimizing antibiotic therapy and ensuring guideline compliance. However, reliance on a single case study limits the generalizability of the findings, highlighting the need for broader validation in diverse clinical settings to improve patient outcomes.</p>","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 2","pages":"209-214"},"PeriodicalIF":2.3000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12086443/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare Informatics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4258/hir.2025.31.2.209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/30 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: The high incidence of sepsis necessitates the development of practical decision-making tools for intensivists, especially during the early, critical phases of management. This study evaluates a multi-agent system intended to assist clinicians with antibiotic therapy and adherence to current sepsis management guidelines before diagnostic results become available.
Methods: A multi-agent system incorporating three specialized agents was developed: a sepsis management agent, an antibiotic recommendation agent, and a sepsis guidelines compliance agent. A sepsis case from the MIMIC IV database, organized as a clinical vignette, was used to integrate and test these agents for generating management recommendations. The system leverages retrieval-augmented generation to improve decision-making through the integration of current literature and guidelines.
Results: The application produced management recommendations for a sepsis case associated with pneumonia, including early initiation of broad-spectrum antibiotics and close monitoring for clinical deterioration. Two expert intensivists evaluated these recommendations as "acceptable" and reported moderate interrater agreement (Cohen's kappa = 0.622, p = 0.003) across various aspects of recommendation usefulness.
Conclusions: The multi-agent system shows promise in enhancing decision-making for sepsis management by optimizing antibiotic therapy and ensuring guideline compliance. However, reliance on a single case study limits the generalizability of the findings, highlighting the need for broader validation in diverse clinical settings to improve patient outcomes.