key: cord-0774075-90nyxhs5
authors: Shah, Vishal P; Farah, Wigdan H; Hill, James C; Hassett, Leslie C; Binnicker, Matthew J; Yao, Joseph D; Hassan Murad, M
title: Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis
date: 2021-08-31
journal: Open Forum Infect Dis
DOI: 10.1093/ofid/ofab453
sha: 208d36f31acfb6f2e5cd8a5d2709dc02eeb360c0
doc_id: 774075
cord_uid: 90nyxhs5

Cycle threshold (C(T)) 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, C(T) 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 C(T) 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 C(T) 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 C(T) values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with C(T) values <25 had a high risk of more severe disease and mortality than patients with C(T) 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 C(T) values of 25–30 compared with >30.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may lead to a spectrum of disease, ranging from asymptomatic infection to severe symptomatic coronavirus disease 2019 (COVID- 19) . As of May 5, 2021, there have been over 32 million confirmed cases of COVID-19 in the United States, resulting in >5 million hospitalizations [1, 2] . Among hospitalized patients with COVID-19, roughly one-third of patients have required intensive care unit (ICU) admission, and 1 in 9 patients have died [3] [4] [5] [6] .

Current known host risk factors for progression to severe COVID-19 include advanced age, male sex, and certain comorbidities including obesity and heart failure [7] [8] [9] . Laboratory values such as interleukin-6 level, C-reactive protein level, and peripheral blood lymphocyte count have also been correlated with disease severity [10] [11] [12] .

There has also been interest in assessing the impact of viral load on clinical outcomes. Most patients with COVID-19 are diagnosed with real-time polymerase chain reaction (rtPCR) assays, which are most commonly qualitative tests (ie, providing a positive or negative result). Many rtPCR assays can provide a cycle threshold (C T ) value, which refers to the number of PCR cycles required to generate target amplification (as measured by fluorescence) that is distinguishable from baseline fluorescence [13] . Using a standard curve correlating C T values to different known concentrations of SARS-CoV-2 virions, a quantitative viral load can be determined in a given clinical specimen.

While C T value is inversely proportional to viral load, this correlation is nonlinear, and many factors influence this association, including sample collection and rtPCR assay [14] . Additional limitations in the use of C T values in patients with SARS-CoV-2 include the impact of the timing of sample collection, as generally earlier in the disease course individuals will have a higher viral load. Despite these limitations, there is widespread interest among clinicians in how the C T value can be used to better manage patients infected with SARS-CoV-2.

However, a gap remains in the knowledge of the clinical utility of C T values to aid in prognostication of patients with COVID-19. An early systematic review evaluated the clinical utility of C T values in patients with COVID-19, but this analysis only included 1 study on disease progression and another study on patient mortality [15] . Several studies have reported noncorrelative results between clinical outcomes in patients with COVID-19 and both SARS-CoV-2 viral load and C T values [16] [17] [18] [19] [20] [21] . These discrepancies may be due, in part, to different technologies used, timing of testing, and differing criteria for assessing clinical outcomes at varying institutions across the globe. Given this uncertainty, we conducted a systematic review and meta-analysis to assess the association between C T values and clinical outcomes, including the risk of hospitalization among patients with COVID-19 and the risk of disease severity and death in such patients.

This study was registered in PROSPERO (CRD42021235617), and findings were reported according to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guideline (Supplementary Data).

We sought to identify published studies evaluating the association between CT values and 3 distinct outcomes among patients with a confirmed SARS-CoV-2 infection: (1) need for hospitalization; and among hospitalized patients, (2) disease severity (WHO Severity scale grade 5 or higher, specifically invasive or noninvasive ventilation and/or ICU need); (3) in-hospital and 30-day mortality.

A comprehensive search of several databases from January 1, 2019, through January 28, 2021, limited to the English language and excluding animal studies, was conducted. Given the rapid pace of publications, the search was repeated on April 19, 2021. The databases included Ovid MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Web of Science, and Scopus. The search strategy was designed and conducted by a medical reference librarian (L.C.H.) with input from the study investigators. Controlled vocabulary supplemented with keywords was used to search for studies describing the association between SARS-CoV-2 C T values and clinical outcomes. The actual strategy listing all search terms used and how they are combined is described in the Appendix (Supplementary Data).

We included cohort studies, randomized controlled trials, and case reports and series that met the following criteria: (1) adults ≥18 years, (2) publication in English, (3) reported C T value data, (4) specified sample source (eg, nasopharyngeal swab), (5) specified rtPCR assay, (6) minimum 5 study subjects with specified outcome of interest, and (7) full manuscript available.

Each study was assessed for inclusion by 2 independent reviewers, first by screening the publication title and abstract and subsequently by analyzing content in the full-text articles (V.P.S., W.H.F., or J.C.H.). Discordance of study data was resolved by evaluation by a third reviewer or discussion on eligibility and consensus agreement.

Two reviewers abstracted data from each included study (V.P.S. and W.H.F.). Disagreements were resolved by discussion. When multiple studies from the same data set were reported, we included only the largest data set. If a study reported the use of multiple rtPCR assays, data were abstracted and synthesized separately for each assay.

For each outcome of interest, adjusted odds ratios (ORs) for low (C T <25) and medium (C T 25-30) compared with high (C T >30) C T values were collected. If unavailable or not reported, data from tables were abstracted and unadjusted odds ratios were calculated. If data were reported but were insufficient for meta-analysis (eg, graphic data), authors were contacted for more details.

Additionally, the mean C T value and SD for each outcome were collected if available (eg, survivor vs nonsurvivor mean C T values). If mean C T values and SD data were not available, information was imputed from interquartile ranges. Sample population, sample source, and rtPCR platform data were also collected.

Risk of Bias assessment was performed using a modified Newcastle-Ottawa scale by 2 independent reviewers (V.P.S. and W.H.F.) (Supplementary Data). Disagreements were resolved by discussion and consensus. We assessed the representativeness of the study population, selection of the nonexposed cohort, comparability, and outcome assessment. A quantitative score for risk of bias was not used, but we focused on the most critical element of bias in this specific context, which was adjustment for confounders [22] .

Studies that reported ORs or reported data from which odds ratios could be calculated were analyzed separately from studies that reported C T values as continuous variables for outcomes of interest. If studies reported C T values both as categorical and continuous variables, the study was evaluated as part of the synthesis that had the larger data set.

Because of heterogeneity across study settings and populations, the DerSimonian-Laird random effect model as implemented in the OpenMeta Analyst software package was used [23] . Heterogeneity was assessed using the I 2 statistic, with low heterogeneity being <50%, moderate 50% to 75%, and high >75%. Heterogeneity was explored using subgroup analyses by sample source, rtPCR assay, use of adjusted vs unadjusted ORs, and risk of bias. We were unable to statistically evaluate the presence of publication bias due to the small number of studies included per analysis.

The search yielded 459 potentially relevant articles, of which 21 studies met inclusion criteria ( Figure 1 ). Study characteristics are listed in Tables 1-3 for each outcome. A total of 18 studies contributed data to the meta-analysis. Overall, 8 and 10 studies reported C T values as categorical and continuous variables, respectively, in relation to outcomes of interest and were synthesized collectively for each outcome.

Overall, 15 studies had a high risk of bias (Supplementary Data). Three studies were deemed to have a moderate risk of bias.

For the outcome of hospitalization, 1 study reported only categorical C T values, and thus we were not able to perform an analysis [21] . Seven studies (n = 3291 patients) were analyzed, and 4 studies reported higher C T values in hospitalized patients, 1 of which did not reach statistical significance. Three studies reported lower mean C T values among hospitalized patients, 1 of which did not reach statistical significance. Meta-analysis found no difference in the mean C T value between hospitalized and nonhospitalized patients with SARS-CoV-2 with high heterogeneity (0.062; 95% CI, -1.933 to 2.056; I 2 = 92.71%) ( Figure  2 ).

For disease severity among hospitalized patients, 4 studies (n = 2347 patients) reported categorical C T values. Hospitalized patients with C T values <25 or 25-30 had an increased risk of (Figure 3 ). There was low heterogeneity for these outcomes (I 2 = 0%). Analysis of 4 studies (n = 675 patients) found a mean C T difference of -5.22 (95% CI, -7.11 to -3.32) in patients with severe disease compared with nonsevere disease among hospitalized patients, also with low heterogeneity (I 2 = 42.07%) ( Figure 3C ). For the outcome of mortality, 7 studies (n = 6053 patients) reported categorical C T values. While Magleby et al. reported on the relationship between C T values and mortality, this data set was also included in the report by Westblade et al., which was a larger data set [20, 24] . Thus, the synthesis did not include data from Magleby et al. for the mortality outcome to avoid duplication of results. Hospitalized patients with C T values <25 had an increased risk of mortality compared with those with C T values >30 (OR, 2.95; 95% CI, 2.19 to 3.96) ( Figure 4A ). There was moderate heterogeneity (I 2 = 53.25%), which did not change significantly during a subgroup analysis by risk of bias or rtPCR assay (data not shown). In subgroup analysis by sample source, the 6 studies that utilized only nasopharyngeal swab had low heterogeneity (I 2 = 28.9%) ( Figure 4B ).

Hospitalized patients with C T values of 25-30 compared with >30 also had an increased mortality risk (OR, 1.59; 95% CI, 1.19 to 2.14) with low heterogeneity (I 2 = 41.19%), though this finding was driven by a single large study ( Figure 4C ) [24] . Three additional studies (n = 1382 patients) reported on the relationship between mean C T values and mortality in hospitalized patients and found a lower mean C T value among nonsurvivors than survivors (OR, -4.27; 95% CI, -6.38 to -2.16) with high heterogeneity (I 2 = 83.88%).

Three studies did not provide sufficient data for metaanalysis and are summarized narratively. Piubelli et al. reported 373 patients from a single center in Italy and reported C T values by month. C T values decreased from March 2020 through April 2020 with decreased ICU need, consistent with a waning epidemic trajectory, but the C T values for patients who required ICU-level care did not change [25, 26] . Young et al. reported a prospective observational study of 100 patients from Singapore in which 20 patients had pneumonia and hypoxia and found no difference in C T values compared with patients without pneumonia [27] . However, there was no separate analysis for the 12 patients who required ICU care. Yu et al. reported a study from China of 92 patients comparing baseline C T values in patients with severe disease with C T values in those with mild or moderate disease on admission [28] . They found that patients with more severe disease on admission, as well as patients who went on to have severe disease during their hospitalization, had lower admission C T values compared with those with mild or moderate disease. However, disease severity was not defined.

This systematic review and meta-analysis did not find an association between C T values and hospitalization of persons with SARS-CoV-2. Four studies reported higher C T values in hospitalized patients, while 3 studies reported lower C T values. The single study that reported only OR for the outcome of hospitalization also found no association between low C T value and risk of hospitalization [21] . There was high heterogeneity in the data, which did not significantly decrease in subgroup analysis by sample source (data not shown). These 7 studies from 6 different countries utilized 6 different rtPCR assays, which may account for the difference in results. Additionally, the different study periods and local disease dynamics may contribute to the heterogeneity in the reported data. If testing was limited or delayed, this could also have an impact on the comparator group and may, in part, account for some of the observed heterogeneity. The certainty of a lack of association is also limited by different standards for hospitalization globally, particularly early in the COVID-19 pandemic when many institutions were admitting all patients with SARS-CoV-2 infection regardless of symptoms. For the disease severity and mortality outcomes, C T value data were evaluated both as a numerical difference between outcomes and as a categorical variable depending upon how individual studies reported data. Comparing outcomes across studies using categorical C T values is challenging due to variations in sample collection and the rtPCR platform utilized between studies. Evaluating mean differences in C T values has the advantage of canceling out systematic differences within studies such as testing availability and the rtPCR platform, which allows for more robust comparisons between studies.

Among patients hospitalized with COVID-19, those with lower C T values had more severe disease necessitating noninvasive ventilation, mechanical ventilation, or ICU admission. This association was most notable when comparing patients with C T values <25 with patients with C T values >30 and was also noted among patients with C T values of 25-30. Consistent with this finding, our analyses also revealed a lower mean C T value among those with more severe disease ( Figure 3C ). Contrary to the other 3 studies, Gaston et al. found no mean difference in those with more severe outcomes, though confidence intervals overlapped with other studies. However, this study was in patients with a solid organ transplant, representing a unique patient population. Overall, we observed low heterogeneity in the data.

Among patients hospitalized with COVID-19, lower C T values, particularly C T values <25, were associated with higher mortality compared with those with C T values >30. This analysis included the study by Shah et al., which evaluated mortality among patients with severe disease, defined as having pulse oximetry readings of <93% on room air [29] . This cohort is similar to other hospitalized patients and was thus included in the pooled analysis. There was moderate heterogeneity that decreased during subgroup analysis by sample source ( Figure 4B ). The association between C T values and mortality was less pronounced when comparing hospitalized patients with C T values of 25-30 with patients with C T values of >30, driven largely by a single study ( Figure 4C ). Our analysis also revealed higher mean C T values among survivors compared with nonsurvivors. Interestingly, there have been mixed reports of the association between viral load and outcomes in patients with other respiratory illnesses. A low C T was not associated with worsened outcomes in patients with influenza [30] . Duncan et al. evaluated adults with respiratory syncytial virus and showed that higher viral loads were not independent predictors of hospitalization, but peak viral load was a predictor for mechanical ventilation [31] . Hung et al. performed a prospective study of 154 patients infected with the original SARS-CoV in 2003 and found that higher viral load later in the disease course was associated with increased rates of mechanical ventilation and death [32] . These mixed reports have been described in patients with SARS-CoV-2, and the heterogeneity in the data may be, in part, due to different sample populations, sample sources, and rtPCR assays.

The timing of clinical specimen collection is critical and may impact the C T value as well. A study by Hu et al. suggested that viral load peaks shortly after symptom onset then declines in a steady manner [33] . Early in the disease course, patients infected with SARS-CoV-2 generally have low C T values, with no discernable difference between those who require hospitalization and those who do not. However, as symptoms progress and those who require hospitalization present for medical care, patients with persistently high viral loads may have a worsened prognosis, which may be predicted using the C T value as a surrogate marker. This correlation may also be age-dependent. Faes et al. evaluated a cohort of patients in Belgium and found age to be correlated with time from symptom onset to hospitalization, with younger patients having the shortest duration [34] . The time at which patients get tested may impact the C T value, particularly for those with less severe disease.

There are several limitations to our review. As highlighted by Rhoads et al., the use of C T values for clinical decision-making is a challenging proposal for several reasons [35] . First, sample source, collection method, volume, and storage may impact the C T value. Additionally, C T values can vary widely based on the rtPCR assay used.

This meta-analysis was limited to studies published in English. However, patients from many countries are represented in this evaluation. Due to the small number of studies per outcome, the presence of publication bias could not be evaluated; nonetheless, reporting and publication bias remain a concern as the overall large number of publications related to COVID-19 may have resulted in studies with null results that may not have been reported or published. In addition, time from symptom onset to sample collection or testing was not considered in this evaluation as such data were not widely reported in published studies. Most studies were conducted earlier in the pandemic, when rtPCR testing was more limited and individuals were immune-naive. Findings from this analysis may not be applicable to those with immunity through vaccination or prior infection. Furthermore, most studies were found to have a high risk of bias, largely due to not adjusting for potential confounding variables that are known to affect outcomes assessed in this study, such as age, gender, and use of therapeutics. Additionally, study population was mostly done by convenience sampling, which can lead to significant selection bias. Therefore, using the GRADE approach to evaluate certainty in the meta-analytic estimates, we judged this certainty to be very low due to risk of bias and heterogeneity [36] .

Further prospective research that takes into account confounding factors such as age, gender, comorbidities, and duration from symptom onset to testing would further add to the knowledge base on the clinical utility of the C T value. A prospective serial evaluation of C T values in patients with multiple risk factors for severe disease could aid in determining whether persistently high levels of viral RNA early in the disease course are related to worse outcomes and whether patients who are able to mount an immunologic response and clear more virus have improved outcomes. Additional evaluation of viral load and C T value dynamics in emerging variants and in populations with immunity would also be valuable. Development and availability of quantitative rtPCR assays would allow for standardization and more direct comparison of the prognostic utility of viral load of SARS-CoV-2. To date, no quantitative SARS-CoV-2 assay has received Emergency Use Authorization by the US Food and Drug Administration.

Despite limitations on the interpretation of individual C T values, they may aid in prognostication of patients, along with other demographic, clinical, and laboratory findings. The C T value may allow clinicians to better triage certain patients admitted to the hospital to provide appropriate interventions in a timely manner. Another major benefit of the C T value is that it may be obtained without need for additional testing, assuming the test for SARS-CoV-2 is performed on rtPCR assays that provide this value.

This systematic review suggests a role for C T values in the prognostication of hospitalized individuals for the outcomes of disease severity and mortality, with lower C T values (ie, higher levels of viral RNA) correlating with increased disease severity and mortality. However, C T results must be interpreted with caution given the limitations and lack of assay standardization.

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