W. Siljan, D. Sivakumaran, C. Ritz, S. Jenum, T. Ottenhoff, E. Ulvestad, J. Holter, L. Heggelund, H. Grewal
{"title":"宿主转录特征预测社区获得性肺炎的病因:潜在的抗生素管理工具","authors":"W. Siljan, D. Sivakumaran, C. Ritz, S. Jenum, T. Ottenhoff, E. Ulvestad, J. Holter, L. Heggelund, H. Grewal","doi":"10.1177/11772719221099130","DOIUrl":null,"url":null,"abstract":"Background: Current approaches for pathogen identification in community-acquired pneumonia (CAP) remain suboptimal, leaving most patients without a microbiological diagnosis. If better diagnostic tools were available for differentiating between viral and bacterial CAP, unnecessary antibacterial therapy could be avoided in viral CAP patients. Methods: In 156 adults hospitalized with CAP classified to have bacterial, viral, or mixed viral-bacterial infection based on microbiological testing or both microbiological testing and procalcitonin (PCT) levels, we aimed to identify discriminatory host transcriptional signatures in peripheral blood samples acquired at hospital admission, by applying Dual-color-Reverse-Transcriptase-Multiplex-Ligation-dependent-Probe-Amplification (dc-RT MLPA). Results: In patients classified by microbiological testing, a 9-transcript signature showed high accuracy for discriminating bacterial from viral CAP (AUC 0.91, 95% CI 0.85-0.96), while a 10-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.91, 95% CI 0.86-0.96). In patients classified by both microbiological testing and PCT levels, a 13-transcript signature showed excellent accuracy for discriminating bacterial from viral CAP (AUC 1.00, 95% CI 1.00-1.00), while a 7-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.93, 95% CI 0.87-0.98). Conclusion: Our findings support host transcriptional signatures in peripheral blood samples as a potential tool for guiding clinical decision-making and antibiotic stewardship in CAP.","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Host Transcriptional Signatures Predict Etiology in Community-Acquired Pneumonia: Potential Antibiotic Stewardship Tools\",\"authors\":\"W. Siljan, D. Sivakumaran, C. Ritz, S. Jenum, T. Ottenhoff, E. Ulvestad, J. Holter, L. Heggelund, H. Grewal\",\"doi\":\"10.1177/11772719221099130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Current approaches for pathogen identification in community-acquired pneumonia (CAP) remain suboptimal, leaving most patients without a microbiological diagnosis. If better diagnostic tools were available for differentiating between viral and bacterial CAP, unnecessary antibacterial therapy could be avoided in viral CAP patients. Methods: In 156 adults hospitalized with CAP classified to have bacterial, viral, or mixed viral-bacterial infection based on microbiological testing or both microbiological testing and procalcitonin (PCT) levels, we aimed to identify discriminatory host transcriptional signatures in peripheral blood samples acquired at hospital admission, by applying Dual-color-Reverse-Transcriptase-Multiplex-Ligation-dependent-Probe-Amplification (dc-RT MLPA). Results: In patients classified by microbiological testing, a 9-transcript signature showed high accuracy for discriminating bacterial from viral CAP (AUC 0.91, 95% CI 0.85-0.96), while a 10-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.91, 95% CI 0.86-0.96). In patients classified by both microbiological testing and PCT levels, a 13-transcript signature showed excellent accuracy for discriminating bacterial from viral CAP (AUC 1.00, 95% CI 1.00-1.00), while a 7-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.93, 95% CI 0.87-0.98). Conclusion: Our findings support host transcriptional signatures in peripheral blood samples as a potential tool for guiding clinical decision-making and antibiotic stewardship in CAP.\",\"PeriodicalId\":47060,\"journal\":{\"name\":\"Biomarker Insights\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomarker Insights\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/11772719221099130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarker Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11772719221099130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 1
摘要
背景:目前社区获得性肺炎(CAP)的病原体鉴定方法仍然不够理想,使大多数患者无法进行微生物学诊断。如果有更好的诊断工具来区分病毒性和细菌性CAP,就可以避免对病毒性CAP患者进行不必要的抗菌治疗。方法:根据微生物检测或微生物检测和降钙素原(PCT)水平,对156名CAP住院成人进行细菌、病毒或混合病毒-细菌感染的分类,我们旨在通过双色逆转录酶-多重连接依赖性探针扩增(dc-RT MLPA)技术,在入院时获得的外周血样本中识别歧视性宿主转录特征。结果:在微生物检测分类的患者中,9个转录本标记在区分细菌和病毒性CAP方面具有很高的准确性(AUC 0.91, 95% CI 0.85-0.96),而10个转录本标记在区分病毒性CAP和混合病毒-细菌方面具有相似的准确性(AUC 0.91, 95% CI 0.86-0.96)。在通过微生物检测和PCT水平进行分类的患者中,13个转录本标记在区分细菌和病毒性CAP方面表现出极好的准确性(AUC为1.00,95% CI为1.00-1.00),而7个转录本标记同样可以区分混合病毒-细菌和病毒性CAP (AUC为0.93,95% CI为0.87-0.98)。结论:我们的研究结果支持外周血样本中的宿主转录特征作为指导CAP临床决策和抗生素管理的潜在工具。
Background: Current approaches for pathogen identification in community-acquired pneumonia (CAP) remain suboptimal, leaving most patients without a microbiological diagnosis. If better diagnostic tools were available for differentiating between viral and bacterial CAP, unnecessary antibacterial therapy could be avoided in viral CAP patients. Methods: In 156 adults hospitalized with CAP classified to have bacterial, viral, or mixed viral-bacterial infection based on microbiological testing or both microbiological testing and procalcitonin (PCT) levels, we aimed to identify discriminatory host transcriptional signatures in peripheral blood samples acquired at hospital admission, by applying Dual-color-Reverse-Transcriptase-Multiplex-Ligation-dependent-Probe-Amplification (dc-RT MLPA). Results: In patients classified by microbiological testing, a 9-transcript signature showed high accuracy for discriminating bacterial from viral CAP (AUC 0.91, 95% CI 0.85-0.96), while a 10-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.91, 95% CI 0.86-0.96). In patients classified by both microbiological testing and PCT levels, a 13-transcript signature showed excellent accuracy for discriminating bacterial from viral CAP (AUC 1.00, 95% CI 1.00-1.00), while a 7-transcript signature similarly discriminated mixed viral-bacterial from viral CAP (AUC 0.93, 95% CI 0.87-0.98). Conclusion: Our findings support host transcriptional signatures in peripheral blood samples as a potential tool for guiding clinical decision-making and antibiotic stewardship in CAP.