Effect of varying storage conditions on diagnostic test outcomes of SARS-CoV-2.
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ABSTRACT:
SUBMITTER: Oguri S
PROVIDER: S-EPMC8018904 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:SARS-CoV-2 RNA in wastewater settled solids is associated with COVID-19 incidence in sewersheds and therefore, there is a strong interest in using these measurements to augment traditional disease surveillance methods. A wastewater surveillance program should provide rapid turn around for sample measurements (ideally within 24 hours), but storage of samples is necessary for a variety of reasons including biobanking. Here we investigate how storage of wastewater solids at 4 °C, -20 °C, and -80 °C affects measured concentrations of SARS-CoV-2 RNA. We find that short term (7 or 8 d) storage of raw solids at 4 °C has little effect on measured concentrations of SARS-CoV-2 RNA, whereas longer term storage at 4 °C (35-122 d) or freezing reduces measurements by 60%, on average. We show that normalizing SARS-CoV-2 RNA concentrations by concentrations of pepper mild mottle virus (PMMoV) RNA, an endogenous wastewater virus, can correct for changes during storage as storage can have a similar effect on PMMoV RNA as on SARS-CoV-2 RNA. The reductions in SARS-CoV-2 RNA in solids during freeze thaws is less than those reported for the same target in liquid influent by several authors.
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| S-EPMC8168736 | biostudies-literature
Project description:Naso-pharyngeal RT-PCR is the gold standard for the diagnosis of COVID-19, but there is a need for rapid and reliable tests. Some validation studies have used frozen aliquots mainly from adults. The aim of this real-life study was to test the performance of a SARS-CoV-2 rapid antigen test (SC2-RAT) in children. Symptomatic patients aged 0 to 17 years were recruited in the emergency department of the University Hospital of Creteil and in primary care pediatric practices from October 10, 2020 for 7 weeks. Each enrolled child had a SARS-CoV-2 RT-PCR test and a SC2-RAT from two distinct nasopharyngeal swabs. Among the 308 patients (mean [SD] age 4.9 [5.3] years), fever was the main symptom (73.4%), with no difference between COVID-19-negative and -positive groups. The prevalence of COVID-19 was 10.7% (95% CI 7.5-14.7). On the whole cohort, the sensitivity and specificity of the SC2-RAT compared to RT-PCR was 87.9% (95% CI 71.8-96.6) and 98.5% (95% CI 96.3-99.6). Considering samples with cycle threshold >25, the sensibility was lower: 63.6% (95% CI 30.8-89.1) and the specificity 99.6% (95% CI 98.0-100.0). The mean delay to obtain an SC2-RAT result was <15 min but was 3.2 h (SD 5.5) for an RT-PCR result. Contact with a COVID-19-positive person was more frequent for COVID-19-positive than -negative patients (n = 21, 61.6%, vs. n = 64, 24.6%; p < 0.01). In real life, SC2-RAT seems reliable for symptomatic children, allowing to detect contagious children.
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Project description:BackgroundSerial screening is critical for restricting spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by facilitating timely identification of infected individuals to interrupt transmission. Variation in sensitivity of different diagnostic tests at different stages of infection has not been well documented.MethodsIn a longitudinal study of 43 adults newly infected with SARS-CoV-2, all provided daily saliva and nasal swabs for quantitative reverse transcription polymerase chain reaction (RT-qPCR), Quidel SARS Sofia antigen fluorescent immunoassay (FIA), and live virus culture.ResultsBoth RT-qPCR and Quidel SARS Sofia antigen FIA peaked in sensitivity during the period in which live virus was detected in nasal swabs, but sensitivity of RT-qPCR tests rose more rapidly prior to this period. We also found that serial testing multiple times per week increases the sensitivity of antigen tests.ConclusionsRT-qPCR tests are more effective than antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (given timely results reporting). All tests showed >98% sensitivity for identifying infected individuals if used at least every 3 days. Daily screening using antigen tests can achieve approximately 90% sensitivity for identifying infected individuals while they are viral culture positive.
| S-EPMC8448437 | biostudies-literature
Project description:BackgroundAssigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.ObjectiveThe aim of this study was to develop and clinically validate an adaptable, personalized diagnostic model to assist clinicians in ruling in and ruling out COVID-19 in potential patients. We compared the diagnostic performance of probabilistic, graphical, and machine learning models against a previously published benchmark model.MethodsWe integrated patient symptoms and test data using machine learning and Bayesian inference to quantify individual patient risk of SARS-CoV-2 infection. We trained models with 100,000 simulated patient profiles based on 13 symptoms and estimated local prevalence, imaging, and molecular diagnostic performance from published reports. We tested these models with consecutive patients who presented with a COVID-19-compatible illness at the University of California San Diego Medical Center over the course of 14 days starting in March 2020.ResultsWe included 55 consecutive patients with fever (n=43, 78%) or cough (n=42, 77%) presenting for ambulatory (n=11, 20%) or hospital care (n=44, 80%). In total, 51% (n=28) were female and 49% (n=27) were aged <60 years. Common comorbidities included diabetes (n=12, 22%), hypertension (n=15, 27%), cancer (n=9, 16%), and cardiovascular disease (n=7, 13%). Of these, 69% (n=38) were confirmed via reverse transcription-polymerase chain reaction (RT-PCR) to be positive for SARS-CoV-2 infection, and 20% (n=11) had repeated negative nucleic acid testing and an alternate diagnosis. Bayesian inference network, distance metric learning, and ensemble models discriminated between patients with SARS-CoV-2 infection and alternate diagnoses with sensitivities of 81.6%-84.2%, specificities of 58.8%-70.6%, and accuracies of 61.4%-71.8%. After integrating imaging and laboratory test statistics with the predictions of the Bayesian inference network, changes in diagnostic uncertainty at each step in the simulated clinical evaluation process were highly sensitive to location, symptom, and diagnostic test choices.ConclusionsDecision support models that incorporate symptoms and available test results can help providers diagnose SARS-CoV-2 infection in real-world settings.
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Project description:We present the case of a patient with a nonbacterial thrombotic aortic valve endocarditis experiencing severe thromboembolic complications and an acute right internal carotid artery occlusion in the context of a paraneoplastic syndrome and an asymptomatic severe acute respiratory syndrome coronavirus-2 infection, despite treatment with different and overlapping anticoagulant medications. Patients with increased thrombogenicity due to an underlying disease might be at increased risk for thrombotic events during a severe acute respiratory syndrome coronavirus-2 infection.
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