Webster Katie E, Parkhouse Tom, Dawson Sarah, Jones Hayley E, Brown Emily L, Hay Alastair D, Whiting Penny, Cabral Christie, Caldwell Deborah M, Higgins Julian Pt
NIHR Bristol Evidence Synthesis Group, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
Health Technol Assess. 2024 Oct 2:1-75. doi: 10.3310/JLCP4570.
Acute respiratory infections are a common reason for consultation with primary and emergency healthcare services. Identifying individuals with a bacterial infection is crucial to ensure appropriate treatment. However, it is also important to avoid overprescription of antibiotics, to prevent unnecessary side effects and antimicrobial resistance. We conducted a systematic review to summarise evidence on the diagnostic accuracy of symptoms, signs and point-of-care tests to diagnose bacterial respiratory tract infection in adults, and to diagnose two common respiratory viruses, influenza and respiratory syncytial virus.
The primary approach was an overview of existing systematic reviews. We conducted literature searches (22 May 2023) to identify systematic reviews of the diagnostic accuracy of point-of-care tests. Where multiple reviews were identified, we selected the most recent and comprehensive review, with the greatest overlap in scope with our review question. Methodological quality was assessed using the Risk of Bias in Systematic Reviews tool. Summary estimates of diagnostic accuracy (sensitivity, specificity or area under the curve) were extracted. Where no systematic review was identified, we searched for primary studies. We extracted sufficient data to construct a 2 × 2 table of diagnostic accuracy, to calculate sensitivity and specificity. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 tool. Where possible, meta-analyses were conducted. We used GRADE to assess the certainty of the evidence from existing reviews and new analyses.
We identified 23 reviews which addressed our review question; 6 were selected as the most comprehensive and similar in scope to our review protocol. These systematic reviews considered the following tests for bacterial respiratory infection: individual symptoms and signs; combinations of symptoms and signs (in clinical prediction models); clinical prediction models incorporating C-reactive protein; and biological markers related to infection (including C-reactive protein, procalcitonin and others). We also identified systematic reviews that reported the accuracy of specific tests for influenza and respiratory syncytial virus. No reviews were found that assessed the diagnostic accuracy of white cell count for bacterial respiratory infection, or multiplex tests for influenza and respiratory syncytial virus. We therefore conducted searches for primary studies, and carried out meta-analyses for these index tests. Overall, we found that symptoms and signs have poor diagnostic accuracy for bacterial respiratory infection (sensitivity ranging from 9.6% to 89.1%; specificity ranging from 13.4% to 95%). Accuracy of biomarkers was slightly better, particularly when combinations of biomarkers were used (sensitivity 80-90%, specificity 82-93%). The sensitivity and specificity for influenza or respiratory syncytial virus varied considerably across the different types of tests. Tests involving nucleic acid amplification techniques (either single pathogen or multiplex tests) had the highest diagnostic accuracy for influenza (sensitivity 91-99.8%, specificity 96.8-99.4%).
Most of the evidence was considered low or very low certainty when assessed with GRADE, due to imprecision in effect estimates, the potential for bias and the inclusion of participants outside the scope of this review (children, or people in hospital).
Currently evidence is insufficient to support routine use of point-of-care tests in primary and emergency care. Further work must establish whether the introduction of point-of-care tests adds value, or simply increases healthcare costs.
This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR159948.
急性呼吸道感染是患者前往基层医疗和急诊医疗服务机构就诊的常见原因。识别细菌感染患者对于确保恰当治疗至关重要。然而,避免抗生素过度处方以防止不必要的副作用和抗菌药物耐药性也很重要。我们进行了一项系统评价,以总结关于症状、体征和即时检验诊断成人细菌性呼吸道感染以及两种常见呼吸道病毒(流感病毒和呼吸道合胞病毒)的诊断准确性的证据。
主要方法是对现有系统评价进行概述。我们进行了文献检索(2023年5月22日),以识别关于即时检验诊断准确性的系统评价。若识别出多篇综述,我们选择最新且最全面、与我们的综述问题范围重叠最大的综述。使用《系统评价中的偏倚风险》工具评估方法学质量。提取诊断准确性的汇总估计值(敏感性、特异性或曲线下面积)。若未识别出系统评价,我们则检索原始研究。我们提取了足够的数据以构建诊断准确性的2×2表格,计算敏感性和特异性。使用《诊断准确性研究质量评估》第2版工具评估方法学质量。尽可能进行荟萃分析。我们使用GRADE评估现有综述和新分析证据的确定性。
我们识别出23篇涉及我们综述问题的综述;6篇被选为最全面且与我们的综述方案范围相似的综述。这些系统评价考虑了以下用于细菌性呼吸道感染的检测:个体症状和体征;症状和体征组合(在临床预测模型中);纳入C反应蛋白的临床预测模型;以及与感染相关的生物标志物(包括C反应蛋白、降钙素原等)。我们还识别出报告流感病毒和呼吸道合胞病毒特定检测准确性的系统评价。未发现评估白细胞计数对细菌性呼吸道感染的诊断准确性或流感病毒和呼吸道合胞病毒多重检测的综述。因此,我们检索了原始研究,并对这些指标检测进行了荟萃分析。总体而言,我们发现症状和体征对细菌性呼吸道感染的诊断准确性较差(敏感性范围为9.6%至89.1%;特异性范围为13.4%至95%)。生物标志物的准确性略好,特别是当使用生物标志物组合时(敏感性80 - 90%,特异性82 - 93%)。流感病毒或呼吸道合胞病毒检测的敏感性和特异性在不同类型检测中差异很大。涉及核酸扩增技术的检测(单病原体或多重检测)对流感病毒的诊断准确性最高(敏感性91 - 99.8%,特异性96.8 - 99.4%)。
使用GRADE评估时,由于效应估计不精确、存在偏倚可能性以及纳入了本综述范围之外的参与者(儿童或住院患者),大多数证据被认为确定性低或非常低。
目前证据不足以支持在基层医疗和急诊医疗中常规使用即时检验。进一步的工作必须确定引入即时检验是否增加价值,还是仅仅增加医疗成本。
本文介绍了由英国国家卫生与保健研究所(NIHR)卫生技术评估计划资助的独立研究,资助编号为NIHR159948。