Victor Iapascurta, Ion Fiodorov, Adrian Belii, Viorel Bostan
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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":"{\"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}","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
摘要
目的:脓毒症的高发病率需要为重症医师开发实用的决策工具,特别是在早期,关键的管理阶段。本研究评估了一种多药系统,旨在帮助临床医生进行抗生素治疗,并在诊断结果出来之前遵守当前的败血症管理指南。方法:开发了包含三种专门药物的多药物系统:脓毒症管理药物,抗生素推荐药物和脓毒症指南依从性药物。来自MIMIC IV数据库的脓毒症病例,作为临床小插曲组织,用于整合和测试这些药物以产生管理建议。该系统利用检索增强生成,通过整合当前文献和指南来改进决策。结果:该应用程序产生了与肺炎相关的脓毒症病例的管理建议,包括早期开始使用广谱抗生素和密切监测临床恶化。两名专家评估这些建议为“可接受的”,并报告了在建议有用性的各个方面的中度仲裁者一致性(Cohen’s kappa = 0.622, p = 0.003)。结论:通过优化抗生素治疗和确保指南的遵守,多药物系统有望加强败血症管理的决策。然而,对单一病例研究的依赖限制了研究结果的普遍性,强调需要在不同的临床环境中进行更广泛的验证,以改善患者的预后。
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.