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Background Cycle threshold (Ct) values can be used in an attempt to semiquantify results in the qualitative real-time polymerase-chain-reaction (PCR) for the new coronavirus SARS-CoV-2. The significance of Ct values in epidemiological studies and large cohorts is still unclear. Objective To monitor Ct values in a long-term study and compare the results with demographic data of patients who tested positive for SARS-CoV-2 by real-time PCR. Study design S gene SARS-CoV-2 Ct values were analyzed retrospectively from consecutive patients between March 15th to September 15th 2020 with special regard to age, gender, and in- or outpatient status. Results In total, 65,878 patients were tested, 1,103 (1.7%) of whom were positive for SARS-CoV-2. Twenty-six positive patients were excluded, because the respective PCR runs did not meet the stability requirements (Ct value of the positive controls between 26 and 29). Of the remaining 1,077 patients, females (n = 566; 53%) were significantly older than males (n = 511; 47%) (50.9 versus 45.1 years; p = 0.006) and had slightly higher mean Ct values than males (25.4 vs. 24.8; p = 0.04). Patients in the age groups >80 years had significantly higher Ct values than the remaining age groups (p < 0.001). Children (0-19 years) showed Ct values in the range of those found in adults (25.2 vs. 25.1, p = 0.9). There were no statistically different Ct values between in- and outpatients (p = 0.1), however, SARS-CoV-2 positive inpatients were significantly older than outpatients (p < 0.0001). Conclusions CT values are suitable for more detailed monitoring of the SARS-CoV-2 pandemic. Age is an important cofactor in SARS-CoV-2 positive patients and may have influence on Ct values in SARS-CoV-2-PCR.

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As it is common practice for laboratories to store patient samples for a predefined period, allowing clinicians to request additional tests on previously collected samples, knowledge about sample stability is indispensable for the laboratorian. A common approach to estimating the maximum storage time is to use a discrete study design, measuring the analyte of interest at various time-points and then checking for significant differences with the help of a statistical test, such as Student’s t-test, Wilcoxon’s test or an analysis of variance (ANOVA) test. Because only discrete time intervals are considered, stability data can just be approximated. Alternatively, a continuous study design, as described by the Clinical and Laboratory Standards Institute (CLSI) for performing stability experiments for in vitro diagnostic reagents, can also be adopted by the clinical laboratory to evaluate the stability of biological samples. The major advantage of this approach is that it allows laboratories to define individual stability limits for different medical situations and offers more flexibility when choosing time-points for measurements. The intent of this paper is to demonstrate the evaluation of sample stability in the clinical laboratory with a continuous study design implemented with linear or non-linear regression analysis. Appropriate statistical modeling and acceptance criteria are presented, stability functions are described briefly, and checking the overall validity of the results is discussed.