International external quality assessment for SARS-CoV-2 molecular detection and survey on clinical laboratory preparedness during the COVID-19 pandemic, April/May 2020

A sensitive and affordable multiplex RT-qPCR assay for SARS-CoV-2 detection

With the ongoing COVID-19 (Coronavirus Disease 2019) pandemic, caused by the novel coronavirus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), there is a need for sensitive, specific, and affordable diagnostic tests to identify infected individuals, not all of whom are symptomatic. The most sensitive test involves the detection of viral RNA using RT-qPCR (quantitative reverse transcription PCR), with many commercial kits now available for this purpose. However, these are expensive, and supply of such kits in sufficient numbers cannot always be guaranteed. We therefore developed a multiplex assay using well-established SARS-CoV-2 targets alongside a human cellular control (RPP30) and a viral spike-in control (Phocine Herpes Virus 1 [PhHV-1]), which monitor sample quality and nucleic acid extraction efficiency, respectively. Here, we establish that this test performs as well as widely used commercial assays, but at substantially reduced cost. Furthermore, we demonstrate >1,000-fold variability in material routinely collected by combined nose and throat swabbing and establish a statistically significant correlation between the detected level of human and SARS-CoV-2 nucleic acids. The inclusion of the human control probe in our assay therefore provides a quantitative measure of sample quality that could help reduce false-negative rates. We demonstrate the feasibility of establishing a robust RT-qPCR assay at approximately 10% of the cost of equivalent commercial assays, which could benefit low-resource environments and make high-volume testing affordable.

Specificity and positive predictive value of SARS-CoV-2 nucleic acid amplification testing in a low-prevalence setting

Objectives

When the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is low, many positive test results are false positives. Confirmatory testing reduces overdiagnosis and nosocomial infection and enables real-world estimates of test specificity and positive predictive value. This study estimates these parameters to evaluate the impact of confirmatory testing and to improve clinical diagnosis, epidemiological estimation and interpretation of vaccine trials.

Methods

Over 1 month we took all respiratory samples from our laboratory with a patient's first detection of SARS-CoV-2 RNA (Hologic Aptima SARS-CoV-2 assay or in-house RT-PCR platform), and repeated testing using two platforms. Samples were categorized by source, and by whether clinical details suggested COVID-19 or corroborative testing from another laboratory. We estimated specificity and positive predictive value using approaches based on maximum likelihood.

Results

Of 19 597 samples, SARS-CoV-2 RNA was detected in 107; 52 corresponded to first-time detection (0.27% of tests on samples without previous detection). Further testing detected SARS-CoV-2 RNA once or more (‘confirmed’) in 29 samples (56%), and failed to detect SARS-CoV-2 RNA (‘not confirmed’) in 23 (44%). Depending upon assumed parameters, point estimates for specificity and positive predictive value were 99.91–99.98% and 61.8–89.8% respectively using the Hologic Aptima SARS-CoV-2 assay, and 97.4–99.1% and 20.1–73.8% respectively using an in-house assay.

Conclusions

Nucleic acid amplification testing for SARS-CoV-2 is highly specific. Nevertheless, when prevalence is low a significant proportion of initially positive results fail to confirm, and confirmatory testing substantially reduces the detection of false positives. Omitting additional testing in samples with higher prior detection probabilities focuses testing where it is clinically impactful and minimizes delay.

IFCC Interim Guidelines on Molecular Testing of SARS-CoV-2 Infection

The diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection globally has relied extensively on molecular testing, contributing vitally to case identification, isolation, contact tracing, and rationalization of infection control measures during the coronavirus disease 2019 (COVID-19) pandemic. Clinical laboratories have thus needed to verify newly developed molecular tests and increase testing capacity at an unprecedented rate. As the COVID-19 pandemic continues to pose a global health threat, laboratories continue to encounter challenges in the selection, verification, and interpretation of these tests. This document by the International Federation for Clinical Chemistry and Laboratory Medicine (IFCC) Task Force on COVID-19 provides interim guidance on: (A) clinical indications and target populations, (B) assay selection, (C) assay verification, and (D) test interpretation and limitations for molecular testing of SARS-CoV-2 infection. These evidence-based recommendations will provide practical guidance to clinical laboratories worldwide and highlight the continued importance of laboratory medicine in our collective pandemic response.

Comparison of clinical and microbiological diagnoses for older adults with COVID-19 in Wuhan: a retrospective study

Background

The potential differences between a clinical diagnosis of coronavirus disease 2019 (COVID-19) (i.e., symptoms without positive virus test) and a microbiological diagnosis (i.e., positive virus test results) of COVID-19 are not known.

Aims

This study explored the differences between the two types of COVID-19 diagnosis among older patients in terms of clinical characteristics and outcomes.

Methods

A total of 244 inpatients aged ≥ 60 years with COVID-19 were included in this study, of whom 52 were clinically diagnosed and 192 were microbiologically diagnosed. Clinical and laboratory data on hospital admission and outcomes (discharged or died in hospital) of all patients were retrieved from medical records retrospectively. Patients who met the criteria for clinical diagnosis with negative virus test results were assigned to the clinical diagnosis group, whereas those with positive virus test results were assigned to the microbiological diagnosis group. After univariate analyses, two propensity score analyses [i.e., covariate adjustment using propensity score (CAPS) and propensity score matching (PSM)] were conducted to control bias.

Results

The clinical and microbiological diagnosis groups demonstrated significant differences in outcomes and in the majority of laboratory findings. After propensity score analyses, many differences between the two groups disappeared and the rate of mortality had no statistically significant difference (P = 0.318 and 0.828 for CAPS and PSM, respectively).

Conclusions

Patients with similar signs, symptoms, and laboratory and imaging findings as confirmed COVID-19 cases may have a similar mortality risk, regardless of the virus test results, and require timely intervention to reduce their mortality.