Rapid diagnosis of SARS-CoV-2 pneumonia on lower respiratory tract specimens

Background The ongoing SARS-CoV-2 pandemic requires the availability of accurate and rapid diagnostic tests, especially in such clinical settings as emergency and intensive care units. The objective of this study was to evaluate the diagnostic performance of the Vivalytic SARS-CoV-2 rapid PCR kit in lower respiratory tract (LRT) specimens. Methods Consecutive LRT specimens (bronchoalveolar lavage and bronchoaspirates) were collected from Intensive Care Units of San Martino Hospital (Genoa, Italy) between November 2020 and January 2021. All samples underwent RT-PCR testing by means of the Allplex™ SARS-CoV-2 assay (Seegene Inc., South Korea). On the basis of RT-PCR results, specimens were categorized as negative, positive with high viral load [cycle threshold (Ct) ≤ 30] and positive with low viral load (Ct of 31–35). A 1:1:1 ratio was used to achieve a sample size of 75. All specimens were subsequently tested by means of the Vivalytic SARS-CoV-2 rapid PCR assay (Bosch Healthcare Solutions GmbH, Germany). The diagnostic performance of this assay was assessed against RT-PCR through the calculation of accuracy, Cohen’s κ, sensitivity, specificity and expected positive (PPV) and negative (NPV) predictive values. Results The overall diagnostic accuracy of the Vivalytic SARS-CoV-2 was 97.3% (95% CI: 90.9–99.3%), with an excellent Cohen’s κ of 0.94 (95% CI: 0.72–1). Sensitivity and specificity were 96% (95% CI: 86.5–98.9%) and 100% (95% CI: 86.7–100%), respectively. In samples with high viral loads, sensitivity was 100% (Table 1). The distributions of E gene Ct values were similar (Wilcoxon’s test: p = 0.070), with medians of 35 (IQR: 25–36) and 35 (IQR: 25–35) on Vivalytic and RT-PCR, respectively (Fig. 1). NPV and PPV was 92.6% and 100%, respectively.Table 1 Demographic characteristics and data sample type of the study cases (N = 75) Male, N (%) 56 (74.6%) Age (yr), Median (IQR) 65 (31–81) BAS, N (%) 43 (57.3%) Negative 30.2% Positive—High viral load [Ct ≤ 30] 27.9% Positive—Low viral load [Ct 31–35] 41.9% BAL, N (%) 32 (42.7%) Negative 37.5% Positive—High viral load [Ct ≤ 30] 40.6% Positive—Low viral load [Ct 31–35] 21.9% Data were expressed as proportions for categorical variables. Specimens were categorized into negative, positive with high viral load [cycle threshold (Ct) ≤ 30] and positive with low viral load (Ct of 31–35). BAS bronchoaspirates, BAL bronchoalveolar lavage, Ct cycle threshold Conclusions Vivalytic SARS-CoV-2 can be used effectively on LRT specimens following sample liquefaction. It is a feasible and highly accurate molecular procedure, especially in samples with high viral loads. This assay yields results in about 40 min, and may therefore accelerate clinical decision-making in urgent/emergency situations.

1595 Instituting Rapid and Semi-rapid COVID-19 Testing Pathways to Facilitate Emergency Surgery

Aim Defining a patient’s COVID-19 status on admission is essential for optimised patient management, safe bed-placement, and flow across the hospital. Perioperative COVID-19 infection is associated with significantly poorer outcomes and may influence a patient's and/or surgeon's decision to proceed. Rapid PCR tests (1-2 hours) for COVID-19 remain the gold-standard, however most NHS Trust’s either do not have, or have severely limited access to such testing modalities. Our aim was to introduce a surgical triaging algorithm to conserve rapid testing for immediate surgery, whilst developing a semi-rapid pathway with results available in 12-15 hours for surgery within 24-48 hours. Method Using quality improvement methodology, based on a ‘PDSA’ model we introduced a surgical triaging algorithm. Testing options were categorised into rapid, semi-rapid or routine (24 hours). Defined outcomes, as well as primary and secondary drivers were identified. Both the pre-analytical and post-analytical testing pathways were characterised, concentrating on electronic requesting, laboratory transportation and reporting. Five ‘PDSA’ cycles were performed with immediate audit and feed-back to surgeons after each round. A vetting procedure was also introduced to improve compliance with requesting. Results Turn-around-times for COVID-19 PCR swabs at our institution improved from 23 hrs:13 minutes at baseline, to 9 hrs:38 minutes for semi-rapids, to < 2 hours for rapid swabs. Conclusions Adoption of a surgical triaging algorithm ensured prioritisation of rapid and semi-rapid COVID testing based on clinical need. This ensured optimised patient care, safe theatre and anaesthetic Infection Prevention and Control practices, as well as correct post-operative placement.

Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against nasopharyngeal swab specimens and found saliva methods require further optimization to match this gold standard. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.

Rapid Diagnosis of SARS-CoV-2 Pneumonia on Lower Respiratory Tract Specimens

Background: The ongoing pandemic of SARS-CoV-2 requires the availability of accurate and rapid diagnostic tests, especially in some clinical settings like emergency and intensive care units. The objective of this study was to evaluate the diagnostic performances of rapid PCR kit Vivalytic SARS-CoV-2 in lower respiratory tract (LRT) specimens.Methods: A consecutive sample of LRT specimens (bronchoalveolar lavage and bronchoaspirates) was collected from Intensive Care Units of San Martino Hospital (Genoa, Italy) between November 2020 and January 2021. All samples were tested in RT-PCR by using Allplex™ SARS-CoV-2 assay (Seegene Inc., South Korea). Based on RT-PCR results, specimens were categorized into negative, positive with high viral load [cycle threshold (Ct) ≤30] and positive with low viral load (Ct of 31–35). A quota 1:1:1 sampling was used to achieve a sample size of 75. Then, all specimens were tested in the rapid PCR assay Vivalytic SARS-CoV-2 (Bosch Healthcare Solutions GmbH, Germany). The diagnostic performance of the rapid PCR against RT-PCR was assessed through calculation of accuracy, Cohen’s κ, sensitivity, specificity and expected positive (PPV) and negative (NPV) predictive values.Results: The overall diagnostic accuracy of the Vivalytic SARS-CoV-2 was 97.3% (95% CI: 90.9–99.3%) with an excellent Cohen’s κ of 0.94 (95% CI: 0.72–1). The sensitivity and specificity were 96% (95% CI: 86.5–98.9%) and 100% (95% CI: 86.7–100%), respectively. Samples with high viral loads had a sensitivity of 100% (Table 1). The distributions of E gene Ct values were similar (Wilcoxon’s test: P=0.070) with medians of 35 (IQR: 25–36) and 35 (IQR: 25–35), respectively (Figure 1). NPV and PPV was 92.6% and 100%, respectively.Conclusions: This study shows Vivalytic SARS-CoV-2 can be used following the sample liquefaction on LRT specimens. It’s a feasible and highly accurate molecular procedure especially in high viral load samples. This assay allows having a result in about 40 min and therefore may accelerate the clinical decision making in urgent/emergency situations.

SARS-CoV-2 genome sequencing with Oxford Nanopore Technology and Rapid PCR Barcoding in Bolivia

SARS-CoV-2 genomic surveillance has Illumina technology as the golden standard. However, Oxford Nanopore Technology (ONT) provides significant improvements in accessibility, turnaround time and portability. Characteristics that gives developing countries the opportunity to perform genome surveillance. The most used protocol to sequence SARS-CoV-2 with ONT is an amplicon-sequencing protocol provided by the ARTIC Network which requires DNA ligation. Ligation reagents can be difficult to obtain in countries like Bolivia. Thus, here we provide an alternative for library preparation using the rapid PCR barcoding kit (ONT). We mapped more than 3.9 million sequence reads that allowed us to sequence twelve SARS-CoV-2 genomes from three different Bolivian cities. The average sequencing depth was 324X and the average genome length was 29527 bp. Thus, we could cover in average a 98,7% of the reference genome. The twelve genomes were successfully assigned to four different nextstrain clades (20A, 20B, 20E and 20G) and we could observe two main lineages of SARS-CoV-2 circulating in Bolivia. Therefore, this alternative library preparation for SARS-CoV-2 genome sequencing is effective to identify SARS-CoV-2 variants with high accuracy and without the need of DNA ligation. Hence, providing another tool to perform SARS-CoV-2 genome surveillance in developing countries.

Excellent negative predictive value (99.8%) of two rapid molecular COVID-19 tests compared to conventional RT-PCR for SARS-CoV-2 (COVID-19) in 2,011 tests performed in a single centre.

Conventional Reverse Transcription Polymerase Chain Reaction (RT-PCR) remains the gold standard for testing SARS-CoV-2. Since their availability, two rapid molecular COVID-19 tests were performed in parallel with RT-PCR in all urgent and emergency admissions, as the negative predictive value was not yet ascertained. In this study, we present the data of 2011 test results using either ID Now COVID-19 (Abbott) (Abbott ID NOW) or Xpert Xpress SARS-CoV-2 (Cepheid) (GeneXpert) tests comparing to conventional RT-PCR results. The negative predictive value is 99.8%(3 false negatives out of 1,964 tests) using a cut-off CT value of 40. Using a cut-off of RT-PCR CT value of 30 (predicting infectivity), the negative predictive value is reduced to 99.9% (1 out of 1,964 tests). With these results, we feel confident to recommend the immediate use of the rapid PCR tests alone and to use conventional RT-PCR for confirmation testing after.

Evaluation of the accuracy of diagnostic coding for influenza compared to laboratory results: the availability of test results before hospital discharge facilitates improved coding accuracy

Background Assessing the accuracy of diagnostic coding is essential to ensure the validity and reliability of administrative coded data. The aim of the study was to evaluate the accuracy of assigned International Classification of Diseases version 10-Australian Modification (ICD-10-AM) codes for influenza by comparing with patients’ results of their polymerase chain reaction (PCR)-based laboratory tests. Method A retrospective study was conducted across seven public hospitals in New South Wales, Australia. A total of 16,439 patients who were admitted and tested by either cartridge-based rapid PCR or batched multiplex PCR between January 2016 and December 2017 met the inclusion criteria. We calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of ICD-10-AM coding using laboratory results as a gold standard. Separate analyses were conducted to determine whether the availability of test results at the time of hospital discharge influenced diagnostic coding accuracy. Results Laboratory results revealed 2759 positive influenza cases, while ICD-10-AM coding identified 2527 patients. Overall, 13.7% (n = 378) of test positive patients were not assigned an ICD-10-AM code for influenza. A further 5.8% (n = 146) patients with negative test results were incorrectly assigned an ICD-10-AM code for influenza. The sensitivity, specificity, PPV and NPV of ICD-10-AM coding were 93.1%; 98.9%; 94.5% and 98.6% respectively when test results were received before discharge and 32.7%; 99.2%; 87.8% and 89.8% respectively when test results were not available at discharge. The sensitivity of ICD-10-AM coding varied significantly across hospitals. The use of rapid PCR or hospitalisation during the influenza season were associated with greater coding accuracy. Conclusion Although ICD-10-AM coding for influenza demonstrated high accuracy when laboratory results were received before discharge, its sensitivity was substantially lower for patients whose test results were not available at discharge. The timely availability of laboratory test results during the episode of care could contribute to improved coding accuracy.