Risk factors for severe illness in hospitalized Covid-19 patients at a regional hospital

Turcotte, Justin J.; Meisenberg, Barry R.; MacDonald, James H.; Menon, Nandakumar; Fowler, Marcia B.; West, Michaline; Rhule, Jane; Qureshi, Sadaf S.; MacDonald, Eileen B.

BACKGROUND: The Covid-19 pandemic threatens to overwhelm scarce clinical resources. Risk factors for severe illness must be identified to make efficient resource allocations. OBJECTIVE: To evaluate risk factors for severe illness. DESIGN: Retrospective, observational case series. SETTING: Single-institution. PARTICIPANTS: First 117 consecutive patients hospitalized for Covid-19 from March 1 to April 12, 2020. EXPOSURE: None. MAIN OUTCOMES AND MEASURES: Intensive care unit admission or death. RESULTS: In-hospital mortality was 24.8% and average total length of stay was 11.82 days (95% CI: 10.01 to 13.63 days). 30.8% of patients required intensive care unit admission and 29.1% required mechanical ventilation. Multivariate regression identified the amount of supplemental oxygen required at admission (OR: 1.208, 95% CI: 1.011–1.443, p = .037), sputum production (OR: 6.734, 95% CI: 1.630–27.812, p = .008), insulin dependent diabetes mellitus (OR: 11.873, 95% CI: 2.218–63.555, p = .004) and chronic kidney disease (OR: 4.793, 95% CI: 1.528–15.037, p = .007) as significant risk factors for intensive care unit admission or death. Of the 48 patients who were admitted to the intensive care unit or died, this occurred within 3 days of arrival in 42%, within 6 days in 71%, and within 9 days in 88% of patients. CONCLUSIONS: At our regional medical center, patients with Covid-19 had an average length of stay just under 12 days, required ICU care in 31% of cases, and had a 25% mortality rate. Patients with increased sputum production and higher supplemental oxygen requirements at admission, and insulin dependent diabetes or chronic kidney disease may be at increased risk for severe illness. A model for predicting intensive care unit admission or death with excellent discrimination was created that may aid in treatment decisions and resource allocation. Early identification of patients at increased risk for severe illness may lead to improved outcomes in patients hospitalized with Covid-19.