Combining rapid diagnostic tests to estimate primary and post-primary dengue immune status at the point of care.
Combining rapid diagnostic tests to estimate primary and post-primary dengue immune status at the point of care.
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DOI：
10.1371/journal.pntd.0010365
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发表时间：
2022-05
影响因子：
3.8
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中科院分区：
文献类型：
--
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在护理点确定登革热病毒感染史的特征具有挑战性，因为它依赖于强化的实验室技术。我们研究了如何联合使用不同的快速诊断测试（RDTs）来准确地确定诊断期间报告患者的原发性和原发性DENV免疫状态。采用登革热实验室检测和随机对照试验对印度尼西亚（200例）和越南（1217例）急性登革热疑似患者的横断面调查血清进行了检测。采用logistic回归模型，根据相应的实验室病毒血症、IgM和IgG ELISA指标确定DENV NS1、IgM和IgG RDT阳性的概率。使用约登J指数计算RDT阳性/阴性的实验室检测阈值，并用于估计菲律宾患者的RDT结果，其中只有病毒血症、IgM和IgG的数据可用（N:28,326）。最后，根据使用所有rdt的每个结果，按发热天数计算初诊或初诊后的概率。合并NS1、IgM和IgG的RDTs在发烧的头5天分别捕获了94.6%（52/55）和95.4%（104/109）的实验室确诊原发性和原发性登革热病毒病例。实验室检测预测RDT结果与实际RDT结果具有较高的一致性（79.5%(159/200)）。在菲律宾患者中，估计RDT结果的不同组合指示了原发性和原发性免疫状态。总体而言，IgG RDT阳性结果证实了原发后感染。相比之下，IgG RDT阴性结果提示在发热1-2天出现原发性感染和原发性感染后感染，但在发热3-5天确诊为原发性感染。我们展示了如何通过结合NS1、IgM和IgG rrt并考虑症状出现后的天数，在护理点评估报告患者的原发性和原发性DENV免疫状态。该框架具有加强监测行动和登革热预后的潜力，特别是在资源匮乏的环境中。NS1、IgM和IgG联合登革热快速诊断检测（RDTs）以前已被证明能够准确地诊断出在护理点经历登革热病毒（DENV）感染的人，现在作为单一的商业试剂盒提供。然而，由于准确的免疫状态分类目前依赖于实验室分析，因此使用此类试剂盒进一步确定经历原发性（第一次）或原发性后（第二次、第三次或第四次）登革热感染的患者仍然具有挑战性。我们采用logistic回归建模方法，根据相应的PCR和ELISA实验室方法估计RDT阳性和阴性结果，具有较高的敏感性和特异性。然后在大量疑似登革热病例报告样本中预测登革热RDT结果，根据每组可能的登革热RDT结果，按发热天数计算登革热初诊或初诊后的概率。在感染的某些阶段，不同的RDT结果表明了原发性和后原发性免疫状态。利用我们的框架确定资源匮乏地区医疗点的登革热免疫状况，区域监测系统可以估计和监测登革热传播强度。此外，该框架可能支持登革热的预后，并确定将受益于当前疫苗接种制度的原发病例，以防止随后与严重疾病相关的继发感染。
Characterising dengue virus (DENV) infection history at the point of care is challenging as it relies on intensive laboratory techniques. We investigated how combining different rapid diagnostic tests (RDTs) can be used to accurately determine the primary and post-primary DENV immune status of reporting patients during diagnosis. Serum from cross-sectional surveys of acute suspected dengue patients in Indonesia (N:200) and Vietnam (N: 1,217) were assayed using dengue laboratory assays and RDTs. Using logistic regression modelling, we determined the probability of being DENV NS1, IgM and IgG RDT positive according to corresponding laboratory viremia, IgM and IgG ELISA metrics. Laboratory test thresholds for RDT positivity/negativity were calculated using Youden’s J index and were utilized to estimate the RDT outcomes in patients from the Philippines, where only data for viremia, IgM and IgG were available (N:28,326). Lastly, the probabilities of being primary or post-primary according to every outcome using all RDTs, by day of fever, were calculated. Combining NS1, IgM and IgG RDTs captured 94.6% (52/55) and 95.4% (104/109) of laboratory-confirmed primary and post-primary DENV cases, respectively, during the first 5 days of fever. Laboratory test predicted, and actual, RDT outcomes had high agreement (79.5% (159/200)). Among patients from the Philippines, different combinations of estimated RDT outcomes were indicative of post-primary and primary immune status. Overall, IgG RDT positive results were confirmatory of post-primary infections. In contrast, IgG RDT negative results were suggestive of both primary and post-primary infections on days 1–2 of fever, yet were confirmatory of primary infections on days 3–5 of fever. We demonstrate how the primary and post-primary DENV immune status of reporting patients can be estimated at the point of care by combining NS1, IgM and IgG RDTs and considering the days since symptoms onset. This framework has the potential to strengthen surveillance operations and dengue prognosis, particularly in low resource settings. Combined NS1, IgM and IgG dengue rapid diagnostic tests (RDTs) have previously been shown to accurately diagnose those experiencing dengue virus (DENV) infections at the point of care and are now available as single commercial kits. Using such kits to additionally determine those experiencing primary (first) or post-primary (second, third or fourth) dengue infections however remains challenging as accurate immune status classification currently relies on laboratory analysis. We used logistic regression modelling methods to estimate RDT positive and negative outcomes according to corresponding PCR and ELISA laboratory-based methods, which showed high sensitivity and specificity. Dengue RDT outcomes were then predicted among a large sample of suspected dengue case reports, to calculate the probability of being primary or post-primary for dengue according to every possible set of dengue RDT outcomes, by day of fever. Different RDT outcomes, at certain stages of infection, were indicative of primary and post-primary immune status. Using our framework to determine dengue immune status at the point of care in low resource settings, regional surveillance systems could estimate and monitor dengue transmission intensity. Additionally, this framework could potentially support dengue prognosis and identify primary cases who would benefit from current vaccination regimes to prevent subsequent secondary infections associated with severe disease.
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影响因子：
9.3
作者：
Biggs JR;Sy AK;Sherratt K;Brady OJ;Kucharski AJ;Funk S;Reyes MAJ;Quinones MA;Jones-Warner W;Avelino FL;Sucaldito NL;Tandoc AO;la Paz EC;Capeding MRZ;Padilla CD;Hafalla JCR;Hibberd ML
通讯作者：
Hibberd ML
影响因子：
17.1
作者：
OhAinle M;Balmaseda A;Macalalad AR;Tellez Y;Zody MC;Saborío S;Nuñez A;Lennon NJ;Birren BW;Gordon A;Henn MR;Harris E
通讯作者：
Harris E
影响因子：
3.7
作者：
Liu LT;Chen CH;Tsai CY;Lin PC;Hsu MC;Huang BY;Wang YH;Tsai JJ
通讯作者：
Tsai JJ
影响因子：
3.7
作者：
Changal, Khalid Hamid;Raina, Ab Hameed;Changal, Qayum Hamid
通讯作者：
Changal, Qayum Hamid
影响因子：
8.4
作者：
Matusali, Giulia;Colavita, Francesca;Castilletti, Concetta
通讯作者：
Castilletti, Concetta