SARS-CoV-2 Blood RNA Load Predicts Outcome in Critically Ill COVID-19 Patients
Fabian Heinrich, Michael F. Nentwich, Eric Bibiza-Freiwald, Dominik Nörz, Kevin Roedl, Martin Christner, Armin Hoffmann, Flaminia Olearo, Stefan Kluge, Martin Aepfelbacher, Dominic Wichmann, Marc Lütgehetmann, Susanne Pfefferle
Abstract
Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA loads in patient specimens may act as a clinical outcome predictor in critically ill patients with coronavirus disease 2019 (COVID-19). Methods We evaluated the predictive value of viral RNA loads and courses in the blood compared with the upper and lower respiratory tract loads of critically ill COVID-19 patients. Daily specimen collection and viral RNA quantification by reverse transcription quantitative polymerase chain reaction were performed in all consecutive 170 COVID-19 patients between March 2020 and February 2021 during the entire intensive care unit (ICU) stay (4145 samples analyzed). Patients were grouped according to their 90-day outcome as survivors (n=100) or nonsurvivors (n=70). Results In nonsurvivors, blood SARS-CoV-2 RNA loads were significantly higher at the time of admission to the ICU (P=.0009). Failure of blood RNA clearance was observed in 33/50 (66%) of the nonsurvivors compared with 12/64 (19%) survivors (P<.0001). As determined by multivariate analysis, taking sociodemographic and clinical parameters into account, blood SARS-CoV-2 RNA load represents a valid and independent predictor of outcome in critically ill COVID-19 patients (odds ratio [OR; log10], 0.23; 95% CI, 0.12–0.42; P<.0001), with a significantly higher effect for survival compared with respiratory tract SARS-CoV-2 RNA loads (OR [log10], 0.75; 95% CI, 0.66–0.85; P<.0001). Blood RNA loads exceeding 2.51×103 SARS-CoV-2 RNA copies/mL were found to indicate a 50% probability of death. Consistently, 29/33 (88%) nonsurvivors with failure of virus clearance exceeded this cutoff value constantly. Conclusions Blood SARS-CoV-2 load is an important independent outcome predictor and should be further evaluated for treatment allocation and patient monitoring.