Abstract
The spectrum of disease severity and the insidiousness of clinical presentation make
it difficult to recognize patients with coronavirus disease 2019 (COVID-19) at higher
risk of worse outcomes or death when they are seen in the early phases of the disease.
There are now well-established risk factors for worse outcomes in patients with COVID-19.
These should be factored in when assessing the prognosis of these patients. However,
a more precise prognostic assessment in an individual patient may warrant the use
of predictive tools. In this manuscript, we conduct a literature review on the severity
of illness scores and biomarkers for the prognosis of patients with COVID-19. Several
COVID-19-specific scores have been developed since the onset of the pandemic. Some
of them are promising and can be integrated into the assessment of these patients.
We also found that the well-known pneumonia severity index (PSI) and CURB-65 (confusion,
uremia, respiratory rate, BP, age ≥ 65 years) are good predictors of mortality in
hospitalized patients with COVID-19. While neither the PSI nor the CURB-65 should
be used for the triage of outpatient versus inpatient treatment, they can be integrated
by a clinician into the assessment of disease severity and can be used in epidemiological
studies to determine the severity of illness in patient populations. Biomarkers also
provide valuable prognostic information and, importantly, may depict the main physiological
derangements in severe disease. We, however, do not advocate the isolated use of severity
of illness scores or biomarkers for decision-making in an individual patient. Instead,
we suggest the use of these tools on a case-by-case basis with the goal of enhancing
clinician judgment.
Keywords
COVID-19 - PSI - CURB-65 - pneumonia - ARDS - biomarkers
