Association of SARS-CoV-2 Genomic Load with Outcomes in Patients with COVID-19

Zacharioudakis, Ioannis M.; Prasad, Prithiv; Zervou, Fainareti N.; Basu, Atreyee; Inglima, Kenneth; Weisenberg, Scott A.; Agüero-Rosenfeld, Maria E.

doi:10.1513/annalsats.202008-931rl

Cited by 48 publications

(43 citation statements)

References 18 publications

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“…However, this is a fact that may be caused by multiple factors related to hospitalization, and this finding is not replicated in our work. A recently published work also found a relationship between high viral load on admission and a composite outcome of death, intubation or ECMO during hospitalization [19], and Westblade et al reported a higher mortality in patients with high viral load in the oncological population [20]. Yu X. et al [21] reported in a limited number of patients that those with high viral loads in sputum had more severe disease than those with lower viral loads.…”

Section: Discussionmentioning

confidence: 91%

Impact of viral load at admission on the development of respiratory failure in hospitalized patients with SARS-CoV-2 infection

Calle

Lalueza

Mancheño‐Losa

et al. 2021

Eur J Clin Microbiol Infect Dis

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Section: Discussionmentioning

confidence: 91%

Impact of viral load at admission on the development of respiratory failure in hospitalized patients with SARS-CoV-2 infection

Calle

Lalueza

Mancheño‐Losa

et al. 2021

Eur J Clin Microbiol Infect Dis

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“…In contrast, studies where a positive association between nasopharyngeal SARS-CoV-2 Ct values and COVID-19 severity or outcomes was detailed are flourishing [ 6 , 7 , 9 , 10 , 11 , 12 , 17 , 34 , 35 ]. Most of them included samples of more than 100 individuals with the reference swab represented by the diagnostic one, despite only two reported the time between disease onset and swab collection [ 7 , 17 ].…”

Section: Discussionmentioning

confidence: 99%

Diagnostic SARS-CoV-2 Cycle Threshold Value Predicts Disease Severity, Survival, and Six-Month Sequelae in COVID-19 Symptomatic Patients

Trunfio

Venuti

Alladio

et al. 2021

Viruses

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To date, there is no severe acute respiratory syndrome coronavirus 2- (SARS-CoV-2)-specific prognostic biomarker available. We assessed whether SARS-CoV-2 cycle threshold (Ct) value at diagnosis could predict novel CoronaVirus Disease 2019 (COVID-19) severity, clinical manifestations, and six-month sequelae. Hospitalized and outpatient cases were randomly sampled from the diagnoses of March 2020 and data collected at 6 months by interview and from the regional database for COVID-19 emergency. Patients were stratified according to their RNA-dependent-RNA-polymerase Ct in the nasopharyngeal swab at diagnosis as follows: Group A ≤20.0, 20.0< group B ≤28.0, and Group C >28.0. Disease severity was classified according to a composite scale evaluating hospital admission, worst oxygen support required, and survival. Two hundred patients were included, 27.5% in Groups A and B both, 45.0% in Group C; 90% of patients were symptomatic and 63.7% were hospitalized. The median time from COVID-19 onset to swab collection was five days. Lethality, disease severity, type, and number of signs and symptoms, as well as six-month sequelae distributed inversely among the groups with respect to SARS-CoV-2 Ct. After controlling for confounding, SARS-CoV-2 Ct at diagnosis was still associated with COVID-19-related death (p = 0.023), disease severity (p = 0.023), number of signs and symptoms (p < 0.01), and presence of six-month sequelae (p < 0.01). Early quantification of SARS-CoV-2 may be a useful predictive marker to inform differential strategies of clinical management and resource allocation.

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“…Furthermore, the progression of the disease relates to the levels of initial viremia, and low levels of viral load can lead to virus clearance even for older, at-risk patients ( SI Appendix , Fig. S5 ) ( 42 ).…”

Section: Resultsmentioning

confidence: 99%

In silico dynamics of COVID-19 phenotypes for optimizing clinical management

Voutouri

Nikmaneshi

Hardin

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin−angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8+ T cells and sufficient control of the innate immune response. Furthermore, the best treatment—or combination of treatments—depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

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Association of SARS-CoV-2 Genomic Load with Outcomes in Patients with COVID-19

Cited by 48 publications

References 18 publications

Impact of viral load at admission on the development of respiratory failure in hospitalized patients with SARS-CoV-2 infection

Impact of viral load at admission on the development of respiratory failure in hospitalized patients with SARS-CoV-2 infection

Diagnostic SARS-CoV-2 Cycle Threshold Value Predicts Disease Severity, Survival, and Six-Month Sequelae in COVID-19 Symptomatic Patients

In silico dynamics of COVID-19 phenotypes for optimizing clinical management

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