Predictors of severity and mortality among patients hospitalized with COVID-19 in Rhode Island.

BACKGROUND

In order for healthcare systems to prepare for future waves of COVID-19, an in-depth understanding of clinical predictors is essential for efficient triage of hospitalized patients.

METHODS

We performed a retrospective cohort study of 259 patients admitted to our hospitals in Rhode Island to examine differences in baseline characteristics (demographics and comorbidities) as well as presenting symptoms, signs, labs, and imaging findings that predicted disease progression and in-hospital mortality.

RESULTS

Patients with severe COVID-19 were more likely to be older (p = 0.02), Black (47.2% vs. 32.0%, p = 0.04), admitted from a nursing facility (33.0% vs. 17.9%, p = 0.006), have diabetes (53.9% vs. 30.4%, p<0.001), or have COPD (15.4% vs. 6.6%, p = 0.02). In multivariate regression, Black race (adjusted odds ratio [aOR] 2.0, 95% confidence interval [CI]: 1.1-3.9) and diabetes (aOR 2.2, 95%CI: 1.3-3.9) were independent predictors of severe disease, while older age (aOR 1.04, 95% CI: 1.01-1.07), admission from a nursing facility (aOR 2.7, 95% CI 1.1-6.7), and hematological co-morbidities predicted mortality (aOR 3.4, 95% CI 1.1-10.0). In the first 24 hours, respiratory symptoms (aOR 7.0, 95% CI: 1.4-34.1), hypoxia (aOR 19.9, 95% CI: 2.6-152.5), and hypotension (aOR 2.7, 95% CI) predicted progression to severe disease, while tachypnea (aOR 8.7, 95% CI: 1.1-71.7) and hypotension (aOR 9.0, 95% CI: 3.1-26.1) were associated with increased in-hospital mortality.

CONCLUSIONS

Certain patient characteristics and clinical features can help clinicians with early identification and triage of high-risk patients during subsequent waves of COVID-19.