Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, China.
Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, China.
Biomed Res Int. 2020 Sep 8;2020:3969868. doi: 10.1155/2020/3969868. eCollection 2020.
Influenza virus mainly causes acute respiratory infections in humans. However, the diagnosis of influenza is not accurate based on clinical evidence, as the symptoms of flu are similar to other respiratory virus. The lateral-flow assay is a rapid method to detect influenza virus. But the effectiveness of the technique in detecting flu viruses is unclear. Hence, a meta-analysis would be performed to evaluate the accuracy of LFA in detecting influenza virus.
Relevant literature was searched out in PubMed, Embase, Web of Science, and Cochrane Library databases with the keywords "lateral flow assay" and "flu virus". By Meta-DiSc software, pooled sensitivity, pooled specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), summary receiver operating characteristic curve (SROC), and area under the curve (AUC) can be calculated.
This meta-analysis contains 13 studies and 24 data. The pooled sensitivity and specificity of the influenza virus detected by LFA were 0.84 (95% CI: 0.82-0.86) and 0.97 (95% CI: 0.97-0.98), respectively. The pooled values of PLR, NLR, DOR, and SROC were 32.68 (17.16-62.24), 0.17 (0.13-0.24), 334.07 (144.27-773.53), and 0.9877. No publication bias was found.
LFA exhibited high sensitivity and specificity in diagnosing influenza virus. It is a valuable alternative method which can diagnose influenza virus quickly. However, more evidence is required to confirm whether LFA is comparable to traditional methods for detecting the virus.
流感病毒主要引起人类急性呼吸道感染。然而,由于流感的症状与其他呼吸道病毒相似,仅凭临床证据诊断并不准确。侧向流动检测是一种快速检测流感病毒的方法。但是,该技术检测流感病毒的效果尚不清楚。因此,我们将进行一项荟萃分析来评估侧向流动检测法检测流感病毒的准确性。
我们使用关键词“侧向流动检测”和“流感病毒”在 PubMed、Embase、Web of Science 和 Cochrane Library 数据库中检索相关文献。使用 Meta-DiSc 软件计算合并后的敏感度、合并后的特异度、阳性似然比 (PLR)、阴性似然比 (NLR)、诊断比值比 (DOR)、汇总受试者工作特征曲线 (SROC) 和曲线下面积 (AUC)。
本荟萃分析包含 13 项研究和 24 组数据。侧向流动检测法检测流感病毒的合并敏感度和特异度分别为 0.84(95%置信区间:0.82-0.86)和 0.97(95%置信区间:0.97-0.98)。PLR、NLR、DOR 和 SROC 的合并值分别为 32.68(17.16-62.24)、0.17(0.13-0.24)、334.07(144.27-773.53)和 0.9877。未发现发表偏倚。
侧向流动检测法在诊断流感病毒方面具有较高的敏感度和特异度。它是一种快速诊断流感病毒的有价值的替代方法。然而,需要更多的证据来证实侧向流动检测法是否可与传统的病毒检测方法相媲美。