Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department.
Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department.
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DOI：
10.1128/spectrum.02305-22
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发表时间：
2022-12-21
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
急诊科(ED)的临床医生面临着同时评估疑似新冠肺炎感染患者、检测细菌重叠感染和确定疾病严重程度的挑战，因为当前的做法需要单独的工作流程。在这里，我们探讨了IMX-BVN-3/IMX-SEV-329mRNA宿主反应分类器在同时检测严重急性呼吸综合征冠状病毒2型感染和细菌混合感染以及预测新冠肺炎临床严重程度方面的准确性。在斯坦福医院急诊室登记了16 1名聚合酶链式反应确诊的新冠肺炎患者(52.2%女性；中位年龄50.0 岁；51%住院；5.6%死亡)。提取总RNA(2.5mLPAX基因全血总RNA)，用纳米串计数器定量检测29个宿主 。IMX-BVN-3诊断SARS-CoV-2感染151例，敏感性为93.8%。在10名未被分类器检测到的患者中，有6名在登记前9天以上的 检测呈阳性，其余患者在随后的测试中在阳性和阴性结果之间摇摆。该分类器还预测有6名患者(3.7%)合并细菌感染。6例患者中有5例(83.3%)有细菌感染，即艰难梭状芽胞杆菌结肠炎(n = 1)、尿路感染(n = 1)和临床诊断细菌感染(n = 3)，其特异性为99.4%。101名(2.8%)IMX-SEV-3“低”严重度患者和7/60(11.7%)“中等”严重度分级患者在登记后30天内死亡。IMX-BVN-3/IMX-SEV-3分类器准确识别新冠肺炎患者和细菌混合感染患者，并预测患者的死亡风险。正在开发的这些分类器的护理点版本可以改进急诊患者的管理，包括更准确的治疗决策和优化的资源利用。重要性我们测试了单次测试IMX-BVN-3/IMX-SEV-3分类器的实用性，这种分类器只需要2.5 毫升的患者血液，就可以同时检测病毒和细菌感染，并预测感染的严重性和30天后的结果。一种正在开发的护理点设备将绕过血液培养的需要，并极大地减少检测感染所需的时间。这将消除广谱抗生素经验性使用的必要性，并允许对抗生素的使用进行管理。此外，对感染严重程度的准确分类和对30天严重后果的预测将允许适当分配医院资源。
Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 “Low” severity classification and 7/60 (11.7%) in the “Moderate” severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients’ risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.
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影响因子：
4.3
作者：
Sidstedt M;Hedman J;Romsos EL;Waitara L;Wadsö L;Steffen CR;Vallone PM;Rådström P
通讯作者：
Rådström P
影响因子：
17.1
作者：
Sweeney TE;Wong HR;Khatri P
通讯作者：
Khatri P
DOI：
10.1016/j.cmi.2020.07.016
发表时间：
2020-12
期刊：
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
影响因子：
--
作者：
Langford BJ;So M;Raybardhan S;Leung V;Westwood D;MacFadden DR;Soucy JR;Daneman N
通讯作者：
Daneman N
DOI：
10.1007/s10096-015-2383-0
发表时间：
2015-08-01
影响因子：
4.5
作者：
Peretz, A.;Isakovich, N.;Brodsky, D.
通讯作者：
Brodsky, D.
影响因子：
9.4
作者：
Henning, Claes;Aygul, Nilsu;Ozenci, Volkan
通讯作者：
Ozenci, Volkan