Characteristics and predictors of death among 4,035 consecutively hospitalized patients with COVID-19 in Spain

Berenguer, Juan; Ryan, Pablo; Rodríguez-Baño, Jesús; Jarrín, Inmaculada; Carratalà , Jordi; Pachón, Jerónimo; Yllescas, María; Arribas, José Ramón

OBJECTIVES: We aimed to analyse the characteristics and predictors of death in hospitalized patients with COVID-19 in Spain. METHODS: Retrospective observational study of the first consecutive patients hospitalized with COVID-19 confirmed by real-time polymerase chain reaction (RT-PCR) assay in 127 Spanish centres until March 17, 2020. The follow-up censoring date was April 17, 2020. We collected demographic, clinical, laboratory, treatment, and complications data. The primary endpoint was all-cause mortality. Univariable and multivariable Cox regression analyses were performed to identify factors associated with death. RESULTS: Of the 4,035 patients, males accounted for 2,433/3,987 (61.0%), the median age was 70 years, and 2,539/3,439 (73.8%) had >1 comorbidity. The most common symptoms were a history of fever, cough, malaise, and dyspnoea. During hospitalization 1,255/3,979 (31.5%) patients developed acute respiratory distress syndrome, 736/3,988 (18.5%) were admitted to intensive care units, and 619/3,992 (15.5%) underwent mechanical ventilation. Viral or host-targeted medications included lopinavir/ritonavir 2,820/4,005 (70.4%), hydroxychloroquine 2,618/3,995 (65.5%), interferon-beta 1,153/3,950 (29.2%), corticosteroids 1,109/3,965 (28.0%), and tocilizumab 373/3,951 (9.4%). Overall 1,131/4,035 (28%) patients died. Mortality increased with age (85.6% occurring in older than 65 years). Seventeen factors were independently associated with an increased hazard of death, the strongest among them included advanced age, liver cirrhosis, low age-adjusted oxygen saturation, higher concentrations of C-reactive protein, and lower estimated glomerular filtration rate. CONCLUSIONS: Our findings provide comprehensive information about characteristics and complications of severe COVID-19 and may help to identify patients at a higher risk of death.