Determining COVID-19 severity and mortality in patients is an evolving and important topic as it is needed to guide clinical practice. COVID-19 patients’ prognosis cannot be simply judged by how they visually appear. In a phenomenon known as “happy hypoxia,” patients who do not appear distressed have been found to be extremely hypoxic, with oxygen saturation levels as low as 50%. Patients usually lose consciousness at oxygen saturation levels under 75%.
While blood tests and nasopharyngeal viral load can give some insight on disease severity, the development of other tests such as saliva tests can give clinicians a better picture of patient prognosis.
Silva et al., found that saliva viral load was significantly higher in people with COVID-19 risk factors, correlated with increased disease severity, and was a stronger predictor of mortality over time compared to nasopharyngeal viral load.
The group quantified nasopharyngeal and saliva viral RNA using RT-qPCR in 154 patients admitted to Yale-New Haven Hospital. Plasma cytokines, chemokine, antibodies, and leukocyte profiles were analyzed as well. Patients who were hospitalized were found to have higher salivary viral loads. These patients were also found to have higher levels of known COVID-19 associated inflammatory markers such as IL-6, IL-18, IL-10, CXCL10, and type 1 immune response cytokines, and lower platelet and lymphocyte counts. In patients with fatal cases of COVID-19, the high salivary viral loads correlated with follicular CD4+ T cell depletion and lower anti-spike and anti-receptor binding domain IgG production.
Authors concluded that: “Together these results demonstrated that viral load – as measured by saliva but not nasopharyngeal — is a dynamic unifying correlate of disease presentation, severity, and mortality over time.”
Journal Articles:
- Silva et al., (Pre-Print). Saliva viral load is a dynamic unifying correlate of COVID-19 severity and mortality. MedRxiv.
- Couzin-Frankel (2020). The mystery of the pandemic’s ‘happy hypoxia’. Science
Summary by Maxwell Chan