Distinguishing bacterial versus non-bacterial causes of febrile illness - A systematic review of host biomarkers

被引:36
作者
Fernandez-Carballo, B. Leticia [1 ]
Escadafal, Camille [1 ]
MacLean, Emily [2 ]
Kapasi, Anokhi J. [1 ]
Dittrich, Sabine [1 ,3 ]
机构
[1] Fdn Innovat New Diagnost FIND, Chemin Mines 9, Geneva, Switzerland
[2] McGill Univ, Dept Epidemiol Biostat & Occupat Hlth, 1020 Av Pins O, Montreal, PQ H3A 1A2, Canada
[3] Univ Oxford, Nuffield Dept Med, Oxford, England
关键词
C-REACTIVE PROTEIN; ANTIBIOTIC-TREATMENT; CEREBROSPINAL-FLUID; INFECTIONS; PROCALCITONIN; MENINGITIS; CHILDREN; INFANTS; DIAGNOSIS; TESTS;
D O I
10.1016/j.jinf.2021.01.028
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Background: Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development. Objectives: To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI. Data sources: The PubMed database was systematically searched for relevant studies published between 2015 and 2019. Study eligibility criteria: Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included. Participants: Studies involving human participants and/or human samples were included. Methods: We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A risk of bias assessment was performed, based on a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Score 2). Results: We identified 1107 publications. Following screening, 55 publications were included, with 265 biomarker entries. Entries mostly comprised protein biomarkers (58.9%), followed by haematological, RNA, and metabolite biomarkers (15.5%, 8.7%, 12.5%). Sensitivity/specificity was reported for 45.7% of biomarker entries. We assessed a high overall risk of bias for most entries (75.8%). In studies with low/medium risk of bias, four biomarker entries tested in blood samples had sensitivity/specificity of more than 0.90/0.80. Only 12 additional biomarker entries were identified with sensitivity/specificity of more than 0.65/0.65. Conclusions: Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of The British Infection Association.
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页码:1 / 10
页数:10
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