Lack of correlation between the SARS-CoV-2 cycle threshold (Ct ) value and clinical outcomes in patients with COVID-19.
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ABSTRACT: Problem
The utility of the polymerase chain reaction (PCR) cycle threshold (Ct ) values in the management of patients with coronavirus disease 2019 (COVID-19) remains controversial.Methods
We assessed the correlation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Ct values in nasopharyngeal swab samples with the oxygen requirements at the time of sample collection. Specimens were tested with the Simplexa PCR platform, which targets the SARS-CoV-2 ORF1ab and S genes.Results
We identified 23 COVID-19 patients with 49 Ct values available. While Ct values from ORF1ab and S genes were highly correlated for a given specimen, there was no correlation between Ct values for any of these target genes and the oxygen requirements of the patient at the time of sample collection. We found no differences in the initial nor the nadir Ct values between survivors and non-survivors or mild/moderate versus severe/critical illness at the maximum point of illness.Conclusion
SARS-CoV-2 Ct values have limited value in the management of COVID-19.
SUBMITTER: Camargo JF
PROVIDER: S-EPMC8427039 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLiver injury in patients with coronavirus disease 2019 (COVID-19) is common and prognostic. Direct viral tropism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for angiotensin-converting enzyme 2 receptors in hepatocytes may be one of the mechanisms of liver injury. We aimed to determine the role of viral persistence of SARS-CoV-2, based on cycle threshold (Ct) value, in liver injury in COVID-19.MethodsThis was a territory-wide retrospective cohort study of all public hospitals in Hong Kong. Laboratory-confirmed COVID-19 was identified. Serial liver biochemistries and Ct values of SARS-CoV-2 RNA were analyzed.ResultsWe identified 7622 COVID-19 patients (mean age, 47 years; 48.2% male) diagnosed from March 24 to January 1, 2021, who had serial liver biochemistries and Ct values. A total of 1363 (17.9%) COVID-19 patients had alanine transferase (ALT)/aspartate aminotransferase (AST) elevations with 2 temporal patterns-early (within first 14 days of symptom onset) and late (>14 days from symptom onset). COVID-19 patients with ALT/AST elevations had a lower Ct value at admission (23 vs 25; P < .001), day 5 (24 vs 26; P < .001), and day 20 (31 vs 32; P < .001) after admission, compared with those without ALT/AST elevations. COVID-19 patients with ALT/AST elevations had a longer duration from first positive to first negative reverse transcription polymerase chain reaction test for SARS-CoV-2 (13 vs 9 days; P < .001). ALT/AST elevation and presence of diabetes were independent risk factors of viral persistence.ConclusionsLiver injury in COVID-19 is linked to a higher SARS-CoV-2 viral load during the early phase of infection, signifying a possible direct viral injury to the liver. Prolonged viral persistence of SARS-CoV-2 is associated with liver injury.
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Project description:BackgroundImmunocompromised patients with coronavirus disease 2019 (COVID-19) have prolonged infectious viral shedding for more than 20 days. A test-based approach is suggested for de-isolation of these patients.MethodsThe strategy was evaluated by comparing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load (cycle threshold (Ct) values) and viral culture at the time of hospital discharge in a series of 13 COVID-19 patients: six immunocompetent and seven immunocompromised (five solid organ transplant patients, one lymphoma patient, and one hepatocellular carcinoma patient).ResultsThree of the 13 (23%) patients had positive viral cultures: one patient with lymphoma (on day 16) and two immunocompetent patients (on day 7 and day 11). Eighty percent of the patients had negative viral cultures and had a mean Ct value of 20.5. None of the solid organ transplant recipients had positive viral cultures.ConclusionsThe mean Ct value for negative viral cultures was 20.5 in this case series of immunocompromised patients. Unlike those with hematological malignancies, none of the solid organ transplant patients had positive viral cultures. Adopting the test-based approach for all immunocompromised patients may lead to prolonged quarantine. Large-scale studies in disease-specific populations are needed to determine whether a test-based approach versus a symptom-based approach or a combination is applicable for the de-isolation of various immunocompromised patients.
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Project description:AimAnticipating local surges in COVID-19 cases has predominantly been based on observation of increasing cases. We sought to determine if temporal trends in SARS-CoV-2 Cycle threshold (Ct) values from clinical testing were predictive of future cases.MethodsData were collected from a large, safety-net hospital in Los Angeles, California. Ct values for all SARS-CoV-2 detections by the GeneXpert system (Cepheid) between October 2020 to March 2021 were analyzed.ResultsA total of 2,114 SARS-CoV-2-positive samples were included. Cases increased dramatically in December 2020, peaking the first week of January, before returning to pre-surge numbers by mid-February. Ct values fell during this same period, with values in December and January (25.6 ± 7.8 and 27±7.9, respectively) significantly lower than those of the other months (30±9.3 to 37.7 ± 6.3). Average weekly Ct values for all patients negatively correlated with the number of tests run two weeks in the future (r= -0.74, p<0.0001), whereas Ct values for asymptomatic patients negatively correlated most strongly with total number of tests performed one month later (r= -0.88, p<0.0001). Predictive modeling using these Ct values correctly predicted whether cases would increase or decrease 65% of the time for a subsequent surge (May-July 2021).ConclusionsDuring the largest COVID-19 surge in Los Angeles to date, we observed significantly lower Ct values (representing higher levels of viral RNA) suggesting that increased transmission of COVID-19 was temporarily associated with higher viral loads. Decreasing Ct values appear to be a leading indicator for predicting future COVID-19 cases, which can facilitate improved hospital-level surge planning.
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Project description:BackgroundDespite the limitations in the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks.ObjectiveWe aimed to conduct an exploratory analysis of potential correlations between the population distribution of cycle threshold (CT) values and COVID-19 dynamics, which were operationalized as percent positivity, transmission rate (Rt), and COVID-19 hospitalization count.MethodsIn total, 148,410 specimens collected between September 15, 2020, and January 11, 2021, from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. The daily median CT value, daily Rt, daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression were used to evaluate possible associations between daily median CT values and outbreak measures. Cross-correlation plots were used to determine whether a time delay existed between changes in daily median CT values and measures of community disease dynamics.ResultsDaily median CT values negatively correlated with the daily Rt values (P<.001), the daily COVID-19 hospitalization counts (with a 33-day time delay; P<.001), and the daily changes in percent positivity among testing samples (P<.001). Despite visual trends suggesting time delays in the plots for median CT values and outbreak measures, a statistically significant delay was only detected between changes in median CT values and COVID-19 hospitalization counts (P<.001).ConclusionsThis study adds to the literature by analyzing samples collected from an entire geographical area and contextualizing the results with other research investigating population CT values.
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Project description:BackgroundThe detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patient samples is of critical importance in the management of patients and monitoring transmission in the population. However, data on the analytical performance characteristics for detection of SARS-CoV-2 in clinical specimens between individual targets within the same platform, and among different analytical platforms, are limited.MethodsHere we evaluated the performance of 6 different sample-to-answer SARS-CoV-2 detection methods-Roche cobas 6800, Cepheid GeneXpert, Diasorin Simplexa, Luminex Aries emergency use authorization (EUA), Luminex Aries research use only (RUO), and bioMérieux BioFire-in clinical specimens with a range of viral loads.ResultsThe positive percentage agreement between the Roche cobas 6800 and GeneXpert was 100%, Diasorin 95%, Aries EUA 74%, Aries RUO 83%, and BioFire 97%. Notably, in samples with cycle threshold (Ct) values below 30 for the E gene on the Roche cobas 6800 platform, we found 100% positive agreement among all platforms. Given these results, we examined the distribution of over 10 000 Ct values of all positive specimens from individuals at our institution on the Roche cobas platform. Nearly 60% of specimens from asymptomatic individuals had a PCR Ct value >30 as measured using the cobas 6800 assay E gene.ConclusionsOur results demonstrate performance characteristics between different platforms by Ct value and provide data regarding the distribution of viral RNA present in positive specimens.
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Project description:Cycle threshold (CT) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, CT values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between CT values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between CT values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean CT values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with CT values <25 had a high risk of more severe disease and mortality than patients with CT values >30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with CT values of 25-30 compared with >30.
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Project description:ACE2 on epithelial cells is the SARS-CoV-2 entry receptor. Single-cell RNA-sequencing data derived from two COVID-19 cohorts revealed that MAP4K3/GLK-positive epithelial cells were increased in patients. SARS-CoV-2-induced GLK overexpression in epithelial cells correlated with COVID-19 severity and vesicle secretion. GLK overexpression induced the epithelial cell-derived exosomes containing ACE2; the GLK-induced exosomes transported ACE2 proteins to recipient cells, facilitating pseudovirus infection. Consistently, ACE2 proteins were increased in the serum exosomes from another COVID-19 cohort. Remarkably, SARS-CoV-2 spike protein stimulated GLK, and GLK stabilized ACE2 in epithelial cells. Mechanistically, GLK phosphorylated ACE2 at two serine residues (Ser776, Ser783), leading to dissociation of ACE2 from its E3 ligase UBR4. Reduction of UBR4-induced Lys48-linked ubiquitination at three lysine residues (Lys26, Lys112, Lys114) of ACE2 prevented its degradation. Furthermore, SARS-CoV-2 pseudovirus or live virus infection in humanized ACE2 mice induced GLK and ACE2 protein levels, as well as ACE2-containing exosomes. Collectively, ACE2 stabilization by SARS-CoV-2-induced MAP4K3/GLK may contribute to the pathogenesis of COVID-19.
| S-SCDT-EMM-2022-15904 | biostudies-other
Project description:BackgroundThe distribution of population-level real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values as a proxy of viral load may be a useful indicator for predicting COVID-19 dynamics.ObjectiveThe aim of this study was to determine the relationship between the daily trend of average Ct values and COVID-19 dynamics, calculated as the daily number of hospitalized patients with COVID-19, daily number of new positive tests, daily number of COVID-19 deaths, and number of hospitalized patients with COVID-19 by age. We further sought to determine the lag between these data series.MethodsThe samples included in this study were collected from March 21, 2021, to December 1, 2021. Daily Ct values of all patients who were referred to the Molecular Diagnostic Laboratory of Iran University of Medical Sciences in Tehran, Iran, for RT-PCR tests were recorded. The daily number of positive tests and the number of hospitalized patients by age group were extracted from the COVID-19 patient information registration system in Tehran province, Iran. An autoregressive integrated moving average (ARIMA) model was constructed for the time series of variables. Cross-correlation analysis was then performed to determine the best lag and correlations between the average daily Ct value and other COVID-19 dynamics-related variables. Finally, the best-selected lag of Ct identified through cross-correlation was incorporated as a covariate into the autoregressive integrated moving average with exogenous variables (ARIMAX) model to calculate the coefficients.ResultsDaily average Ct values showed a significant negative correlation (23-day time delay) with the daily number of newly hospitalized patients (P=.02), 30-day time delay with the daily number of new positive tests (P=.02), and daily number of COVID-19 deaths (P=.02). The daily average Ct value with a 30-day delay could impact the daily number of positive tests for COVID-19 (β=-16.87, P<.001) and the daily number of deaths from COVID-19 (β=-1.52, P=.03). There was a significant association between Ct lag (23 days) and the number of COVID-19 hospitalizations (β=-24.12, P=.005). Cross-correlation analysis showed significant time delays in the average Ct values and daily hospitalized patients between 18-59 years (23-day time delay, P=.02) and in patients over 60 years old (23-day time delay, P<.001). No statistically significant relation was detected in the number of daily hospitalized patients under 5 years old (9-day time delay, P=.27) and aged 5-17 years (13-day time delay, P=.39).ConclusionsIt is important for surveillance of COVID-19 to find a good indicator that can predict epidemic surges in the community. Our results suggest that the average daily Ct value with a 30-day delay can predict increases in the number of positive confirmed COVID-19 cases, which may be a useful indicator for the health system.
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