Interpretation of SARS-CoV-2 replication according to RT-PCR crossing threshold value.
Ontology highlight
ABSTRACT:
SUBMITTER: Marot S
PROVIDER: S-EPMC7845522 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundThe COVID-19 pandemic has led to an unprecedented daily use of RT-PCR tests. These tests are interpreted qualitatively for diagnosis, and the relevance of the test result intensity, i.e. the number of quantification cycles (Cq), is debated because of strong potential biases.AimWe explored the possibility to use Cq values from SARS-CoV-2 screening tests to better understand the spread of an epidemic and to better understand the biology of the infection.MethodsWe used linear regression models to analyse a large database of 793,479 Cq values from tests performed on more than 2 million samples between 21 January and 30 November 2020, i.e. the first two pandemic waves. We performed time series analysis using autoregressive integrated moving average (ARIMA) models to estimate whether Cq data information improves short-term predictions of epidemiological dynamics.ResultsAlthough we found that the Cq values varied depending on the testing laboratory or the assay used, we detected strong significant trends associated with patient age, number of days after symptoms onset or the state of the epidemic (the temporal reproduction number) at the time of the test. Furthermore, knowing the quartiles of the Cq distribution greatly reduced the error in predicting the temporal reproduction number of the COVID-19 epidemic.ConclusionOur results suggest that Cq values of screening tests performed in the general population generate testable hypotheses and help improve short-term predictions for epidemic surveillance.
| S-EPMC8832522 | biostudies-literature
Project description: Not available
| S-EPMC8242732 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) is an infectious, acute respiratory disease caused mainly by person-to-person transmission of the coronavirus SARS-CoV-2. Its emergence has caused a world-wide acute health crisis, intensified by the challenge of reliably identifying individuals likely to transmit the disease. Diagnosis is hampered by the many unknowns surrounding this disease, including those relating to infectious viral burden. This uncertainty is exacerbated by disagreement surrounding the clinical relevance of molecular testing using reverse transcription quantitative PCR (RT-qPCR) for the presence of viral RNA, most often based on the reporting of quantification cycles (Cq), which is also termed the cycle threshold (Ct) or crossing point (Cp). Despite it being common knowledge that Cqs are relative values varying according to a wide range of different parameters, there have been efforts to use them as though they were absolute units, with Cqs below an arbitrarily determined value, deemed to signify a positive result and those above, a negative one. Our results investigated the effects of a range of common variables on Cq values. These data include a detailed analysis of the effect of different carrier molecules on RNA extraction. The impact of sample matrix of buccal swabs and saliva on RNA extraction efficiency was demonstrated in RT-qPCR and the impact of potentially inhibiting compounds in urine along with bile salts were investigated in RT-digital PCR (RT-dPCR). The latter studies were performed such that the impact on the RT step could be separated from the PCR step. In this way, the RT was shown to be more susceptible to inhibitors than the PCR. Together, these studies demonstrate that the consequent variability of test results makes subjective Cq cut-off values unsuitable for the identification of infectious individuals. We also discuss the importance of using reliable control materials for accurate quantification and highlight the substantial role played by dPCR as a method for their development.
| S-EPMC8387146 | biostudies-literature
Project description:ObjectivesTo exploit the features of digital PCR for implementing SARS-CoV-2 observational studies by reliably including the viral load factor expressed as copies/μL.MethodsA small cohort of 51 Covid-19 positive samples was assessed by both RT-qPCR and digital PCR assays. A linear regression model was built using a training subset, and its accuracy was assessed in the remaining evaluation subset. The model was then used to convert the stored cycle threshold values of a large dataset of 6208 diagnostic samples into copies/μL of SARS-CoV-2. The calculated viral load was used for a single cohort retrospective study. Finally, the cohort was randomly divided into a training set (n = 3095) and an evaluation set (n = 3113) to establish a logistic regression model for predicting case-fatality and to assess its accuracy.ResultsThe model for converting the Ct values into copies/μL was suitably accurate. The calculated viral load over time in the cohort of Covid-19 positive samples showed very low viral loads during the summer inter-epidemic waves in Italy. The calculated viral load along with gender and age allowed building a predictive model of case-fatality probability which showed high specificity (99.0%) and low sensitivity (21.7%) at the optimal threshold which varied by modifying the threshold (i.e. 75% sensitivity and 83.7% specificity). Alternative models including categorised cVL or raw cycle thresholds obtained by the same diagnostic method also gave the same performance.ConclusionThe modelling of the cycle threshold values using digital PCR had the potential of fostering studies addressing issues regarding Sars-CoV-2; furthermore, it may allow setting up predictive tools capable of early identifying those patients at high risk of case-fatality already at diagnosis, irrespective of the diagnostic RT-qPCR platform in use. Depending upon the epidemiological situation, public health authority policies/aims, the resources available and the thresholds used, adequate sensitivity could be achieved with acceptable low specificity.
| S-EPMC8687578 | biostudies-literature
Project description:The emergence of SARS-CoV-2 in December 2019 lead to the rapid implementation of assays for virus detection, with real-time RT-PCR arguably considered the gold-standard. In our laboratory Altona RealStar SARS-Cov-2 RT-PCR kits are used with Applied Biosystems QuantStudio 7 Flex thermocyclers. Real-time PCR data interpretation is potentially complex and time-consuming, particularly for SARS-CoV-2, where the laboratory handles up to 2000 samples each day. To simplify this, an automated system that rapidly interprets the curves, developed by diagnostics.ai was introduced. QuantStudio software provides two methods for interpretation, relative threshold and baseline threshold. Many of our assays are analysed using relative threshold and directly exported into pcr.ai software, however, in some rare cases the QuantStudio software assigns positive results to 'ambiguous' curves, flagged by pcr.ai, requiring manual intervention. Due to the sample numbers processed and the proportionate increase in curves flagged by pcr.ai, the two methods were investigated. An audit was carried out to determine the frequency of these curves, involving 138 samples tested during November 2020, including 97 serial samples from 38 patients and it was determined that the relative threshold method produced unreliable results in many of these cases. In addition, we present a solution to simplify the interpretation and automate the process.
| S-EPMC9307283 | biostudies-literature
Project description:We conducted a multicentre cross sectional observational study of laboratory, public health and hospitalisation data for PCR-confirmed COVID-19 cases within the New Zealand Northern Region, between 12 February and 8 June 2020. The aim of this study was to describe population level SARS-CoV-2 upper respiratory tract (URT) viral load dynamics by stratifying positivity rates and polymerase chain reaction (PCR) cycle threshold (Ct) values of URT samples from COVID-19 cases by days since symptom onset, and to explore utility of Ct values in determining length of time post-infection and thus potential infectivity. Of 123,124 samples tested for SARS-CoV-2 by PCR, 579 samples (407 positive and 172 negative) from 368 symptomatic non-hospitalised individuals with PCR-confirmed infection were included. Sample positivity rate was 61.5% (8/13) for pre-symptomatic samples, rising to 93.2% (317/340) for samples collected during the purported symptomatic infectious period (days 0-10 post-symptom onset), and dropping to 36.3% (82/226) for post-infectious period samples (day 11 onwards). URT viral load peaked shortly after symptom onset, with median Ct values ranging 20.00-29.99 until 15 days post-symptom onset, and >30.00 after this time. Of samples with a Ct value of <20.00, 96.1% were collected during the symptomatic infectious period. However, of samples with a Ct value ≥30.00 and ≥35.00, 46.9% and 18.5%, respectively, were also collected during the symptomatic infectious period. The findings of this study indicate that at or soon after symptom onset represents the optimum time to test for SARS-CoV-2 in the URT, with median Ct values suggesting the useful testing window extends until around 15 days post-symptom onset. In asymptomatic individuals or those with unknown dates of symptom onset, Ct values <20.00 imply recent onset/potential infectivity, but Ct values ≥30.00 or ≥35.00 do not exclude recent onset/potential infectivity. Individual sample Ct values should not be used as an absolute marker of length of time post-infection or to exclude infectivity where date of symptom onset is unavailable.
| S-EPMC7980174 | biostudies-literature
Project description:ObjectiveLow viral load from patients infected with SARS-CoV-2 during infection late stage easily lead to false negative nucleic acid testing results, thus having great challenges to the prevention and control of the current pandemic. In present study, we mainly aimed to evaluate specimen types and specimen collection timepoint on the positive detection of 2019 novel coronavirus from patients at infection late stage based on RT-PCR testing.MethodsPaired nasopharyngeal swabs, nasal swabs, oropharyngeal swabs and anal swabs were collected from patients infected with SARS-CoV-2 during infection late stage before washing in the morning and afternoon on the same day. Then virus RNA was extracted and tested for 2019-nCoV identification by RT-PCR within 24 h.ResultsViral load was low at late infection stage. Specimens collected before washing in the morning would increase the detection ratio of 2019-nCoV. Detection ratio of nasopharyngeal swab [65 (95 % CI: 49.51-77.87) vs 42.5(95 % CI: 28.51-57.8)] or nasal swab [57.5 (95 % CI: 42.2-71.49) vs 35 (95 % CI: 22.13-50.49)] is higher not only than oropharyngeal swab[22.5 (95 % CI: 12.32-37.5) vs 7.5 (95 % CI: 2.58-19.86)], but also anal swab[2.5 (95 % CI: 0.44-12.88) vs 5 (95 % CI: 1.38-16.5)].ConclusionsIn summary, our research discovers that nasopharyngeal or nasal swab collected before washing in the morning might be more suitable for detecting of large-scale specimens from patients infected with low SARS-CoV-2 load during infection late stage. Those results could facilitate other laboratories in collecting appropriate specimens for improving detection of SARS-CoV-2 from patients during infection late stage as well as initially screening.
| S-EPMC7493793 | biostudies-literature
Project description:ObjectiveTo evaluate the efficacy of sample pooling compared to the individual analysis for the diagnosis of coronavirus disease 2019 (COVID-19) by using different commercial platforms for nucleic acid extraction and amplification.MethodsA total of 3519 nasopharyngeal samples received at nine Spanish clinical microbiology laboratories were processed individually and in pools (342 pools of ten samples and 11 pools of nine samples) according to the existing methodology in place at each centre.ResultsWe found that 253 pools (2519 samples) were negative and 99 pools (990 samples) were positive; with 241 positive samples (6.85%), our pooling strategy would have saved 2167 PCR tests. For 29 pools (made out of 290 samples), we found discordant results when compared to their correspondent individual samples, as follows: in 22 of 29 pools (28 samples), minor discordances were found; for seven pools (7 samples), we found major discordances. Sensitivity, specificity and positive and negative predictive values for pooling were 97.10% (95% confidence interval (CI), 94.11-98.82), 100%, 100% and 99.79% (95% CI, 99.56-99.90) respectively; accuracy was 99.80% (95% CI, 99.59-99.92), and the kappa concordant coefficient was 0.984. The dilution of samples in our pooling strategy resulted in a median loss of 2.87 (95% CI, 2.46-3.28) cycle threshold (Ct) for E gene, 3.36 (95% CI, 2.89-3.85) Ct for the RdRP gene and 2.99 (95% CI, 2.56-3.43) Ct for the N gene.ConclusionsWe found a high efficiency of pooling strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA testing across different RNA extraction and amplification platforms, with excellent performance in terms of sensitivity, specificity and positive and negative predictive values.
| S-EPMC7481316 | biostudies-literature
Project description: Not available
| S-EPMC8610841 | biostudies-literature
Project description:Bivalve shellfish are readily contaminated by human pathogens present in waters impacted by municipal sewage, and the detection of SARS-CoV-2 in feces of infected patients and in wastewater has drawn attention to the possible presence of the virus in bivalves. The aim of this study was to collect data on SARS-CoV-2 prevalence in bivalve mollusks from harvesting areas of Campania region. A total of 179 samples were collected between September 2019 and April 2021 and were tested using droplet digital RT-PCR (dd RT-PCR) and real-time RT-PCR. Combining results obtained with different assays, SARS-CoV-2 presence was detected in 27/179 (15.1%) of samples. A median viral concentration of 1.1 × 102 and 1.4 × 102 g.c./g was obtained using either Orf1b nsp14 or RdRp/gene E, respectively. Positive results were unevenly distributed among harvesting areas and over time, positive samples being more frequent after January 2021. Partial sequencing of the spike region was achieved for five samples, one of which displaying mutations characteristic of the Alpha variant (lineage B.1.1.7). This study confirms that bivalve mollusks may bioaccumulate SARS-CoV-2 to detectable levels and that they may represent a valuable approach to track SARS-CoV-2 in water bodies and to monitor outbreak trends and viral diversity.
| S-EPMC8776039 | biostudies-literature