Standardization of SARS-CoV-2 Cycle Threshold Values: Multisite Investigation Evaluating Viral Quantitation across Multiple Commercial COVID-19 Detection Platforms.

The demand for testing during the coronavirus disease 2019 (COVID-19) pandemic has resulted in the production of several different commercial platforms and laboratory-developed assays for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This has created several challenges, including, but not limited to, the standardization of diagnostic testing, utilization of cycle threshold () values for quantitation and clinical interpretation, and data harmonization. Using reference standards consisting of a linear range of SARS-CoV-2 concentrations quantitated by viral culture-based methods and droplet digital PCR, we investigated the commutability and standardization of SARS-CoV-2 quantitation across different laboratories in the United States.

Evaluation of potential COVID-19 recurrence in patients with late repeat positive SARS-CoV-2 testing.

Background: SARS-CoV-2 reinfection and reactivation has mostly been described in case reports. We therefore investigated the epidemiology of recurrent COVID-19 SARS-CoV-2.

Methods: Among patients testing positive for SARS-CoV-2 between March 11 and July 31, 2020 within an integrated healthcare system, we identified patients with a recurrent positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) assay ≥60 days after an initial positive test.

Clinical evaluation of the acuitas® AMR gene panel for rapid detection of bacteria and genotypic antibiotic resistance determinants.

Urinary tract infections are leading causes of hospital admissions. Accurate and timely diagnosis is important due to increasing morbidity and mortality from antimicrobial resistance. We evaluated a polymerase chain reaction test (Acuitas AMR Gene Panel with the Acuitas Lighthouse Software) for detection of 5 common uropathogens (Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa, Enterococcus faecalis) and antibiotic resistance genes directly from urine for prediction of phenotypic resistance.