Background: Reliable point-of-care (POC) diagnostics not requiring laboratory infrastructure could be a game changer in the COVID-19 pandemic, particularly in the Global South. We assessed performance, limit of detection (LOD) and ease-of-use of three antigen-detecting, rapid POC diagnostics (Ag-RDT) for SARS-CoV-2.
Methods: This prospective, multi-centre diagnostic accuracy study, recruited participants suspected to have SARS-CoV2 in Germany and UK. Paired nasopharyngeal swabs (NP) or NP and/or oropharyngeal swabs (OP) were collected from participants (one for clinical real-time reverse transcription polymerase chain reaction (RT-PCR) and one for Ag-RDT testing). Performance of each of three Ag-RDTs was compared to RT-PCR overall, and according to predefined subcategories e.g. cycle threshold (CT)-value, days from symptom onset, etc. In addition, limited verification of analytical limit-of-detection (LOD) was determined. To understand the usability of each Ag-RDT a System Usability Scale (SUS) questionnaire and ease-of-use assessment were performed.
Results: Between April 17th and August 25th, 2020, 2417 participants were enrolled, with 70 (3.0%) testing positive by RT-PCR. The best-performing test (SD Biosensor, Inc. STANDARD Q) was 76.6% [95% Confidence Interval (CI) 62.8-86.4] sensitive and 99.3% [CI 98.6-99.6] specific. A sub-analysis showed all samples with RT-PCR CT-values <25 were detectable by STANDARD Q. The test was considered easy-to-use (SUS 86/100) and suitable for POC. Bioeasy and Coris showed specificity of 93.1% [CI 91.0%-94.8%] and 95.8% [CI 93.4%-97.4%], respectively, not meeting the predefined target of ≥98%.
Conclusion: There is large variability in performance of Ag-RDT tests with one test showing promise. Given the usability at POC, these tests are likely to have impact despite imperfect sensitivity; however further research and modelling are needed.
Background
COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.
Methods
This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.
Results
Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).
Discussion
This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors that predict severe COVID-19 outcomes and will inform clinical scores to support early decision-making.
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