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一种使用便携式分子诊断平台区分细菌/病毒感染的快速宿主反应血液检测方法。

A Rapid Host Response Blood Test for Bacterial/Viral Infection Discrimination Using a Portable Molecular Diagnostic Platform.

作者信息

Iglesias-Ussel Maria D, O'Grady Nicholas, Anderson Jack, Mitsis Paul G, Burke Thomas W, Henao Ricardo, Scavetta Joseph, Camilleri Clare, Naderi Sepideh, Carittini Amanda, Perelman Max, Myers Rachel A, Ginsburg Geoffrey S, Ko Emily R, McClain Micah T, van Westrienen Jesse, Tsalik Ephraim L, Tillekeratne L Gayani, Woods Christopher W

机构信息

Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.

Biomeme, Inc, Philadelphia, Pennsylvania, USA.

出版信息

Open Forum Infect Dis. 2024 Dec 11;12(1):ofae729. doi: 10.1093/ofid/ofae729. eCollection 2025 Jan.

DOI:10.1093/ofid/ofae729
PMID:39758742
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11697109/
Abstract

BACKGROUND

Difficulty discriminating bacterial versus viral etiologies of infection drives unwarranted antibacterial prescriptions and, therefore, antibacterial resistance.

METHODS

Utilizing a rapid portable test that measures peripheral blood host gene expression to discriminate bacterial and viral etiologies of infection (the HR-B/V assay on Biomeme's polymerase chain reaction-based Franklin platform), we tested 3 cohorts of subjects with suspected infection: the HR-B/V training cohort, the HR-B/V technical correlation cohort, and a coronavirus disease 2019 cohort.

RESULTS

The Biomeme HR-B/V test showed very good performance at discriminating bacterial and viral infections, with a bacterial model accuracy of 84.5% (95% confidence interval [CI], 80.8%-87.5%), positive percent agreement (PPA) of 88.5% (95% CI, 81.3%-93.2%), negative percent agreement (NPA) of 83.1% (95% CI, 78.7%-86.7%), positive predictive value of 64.1% (95% CI, 56.3%-71.2%), and negative predictive value of 95.5% (95% CI, 92.4%-97.3%). The test showed excellent agreement with a previously developed BioFire HR-B/V test, with 100% (95% CI, 85.7%-100.0%) PPA and 94.9% (95% CI, 86.1%-98.3%) NPA for bacterial infection, and 100% (95% CI, 93.9%-100.0%) PPA and 100% (95% CI, 85.7%-100.0%) NPA for viral infection. Among subjects with acute severe acute respiratory syndrome coronavirus 2 infection of ≤7 days, accuracy was 93.3% (95% CI, 78.7%-98.2%) for 30 outpatients and 75.9% (95% CI, 57.9%-87.8%) for 29 inpatients.

CONCLUSIONS

The Biomeme HR-B/V test is a rapid, portable test with high performance at identifying patients unlikely to have bacterial infection, offering a promising antibiotic stewardship strategy that could be deployed as a portable, laboratory-based test.

摘要

背景

难以区分感染的细菌与病毒病因导致了不必要的抗菌药物处方,进而引发了抗菌药物耐药性。

方法

利用一种可快速测量外周血宿主基因表达以区分感染的细菌和病毒病因的便携式检测方法(基于Biomeme聚合酶链反应的富兰克林平台上的HR-B/V检测),我们对3组疑似感染的受试者进行了检测:HR-B/V训练队列、HR-B/V技术相关性队列和2019冠状病毒病队列。

结果

Biomeme HR-B/V检测在区分细菌和病毒感染方面表现出非常好的性能,细菌模型准确率为84.5%(95%置信区间[CI],80.8%-87.5%),阳性百分比一致性(PPA)为88.5%(95%CI,81.3%-93.2%),阴性百分比一致性(NPA)为83.1%(95%CI,78.7%-86.7%),阳性预测值为64.1%(95%CI,56.3%-71.2%),阴性预测值为95.5%(95%CI,92.4%-97.3%)。该检测与先前开发的BioFire HR-B/V检测显示出极好的一致性,细菌感染的PPA为100%(95%CI,85.7%-100.0%),NPA为94.9%(95%CI,86.1%-98.3%),病毒感染的PPA为100%(95%CI,93.9%-100.0%),NPA为100%(95%CI,85.7%-100.0%)。在感染严重急性呼吸综合征冠状病毒2且病程≤7天的受试者中,30名门诊患者的准确率为93.3%(95%CI,78.7%-98.2%),29名住院患者的准确率为75.9%(95%CI,57.9%-87.8%)。

结论

Biomeme HR-B/V检测是一种快速、便携式检测方法,在识别不太可能患有细菌感染的患者方面具有高性能,提供了一种有前景的抗生素管理策略,可作为一种基于实验室的便携式检测方法加以应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/c003e7b9655f/ofae729f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/c0062f87a528/ofae729f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/4cce5fe1a76c/ofae729f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/c003e7b9655f/ofae729f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/c0062f87a528/ofae729f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/4cce5fe1a76c/ofae729f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/713f/11697109/c003e7b9655f/ofae729f3.jpg

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JAMA Netw Open. 2022 Apr 1;5(4):e227299. doi: 10.1001/jamanetworkopen.2022.7299.
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Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis.2019 年全球细菌对抗菌药物耐药性的负担:系统分析。
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