Clinical characteristics and predictors of death among hospitalized patients infected with SARS-CoV-2 in Sicily, Italy: A retrospective observational study

Abstract

Since late December 2019, severe acute respiratory syndrome coronavirus 2 has spread across the world, which resulted in the World Health Organization declaring a global pandemic. Coronavirus disease 2019 (COVID-19) presents a highly variable spectrum with regard to the severity of illness. Most infected individuals exhibit a mild to moderate illness (81%); however, 14% have a serious disease and 5% develop severe acute respiratory distress syndrome (ARDS), requiring intensive care support. The mortality rate of COVID-19 continues to rise across the world. Data regarding predictors of mortality in patients with COVID 19 are still scarce but are being actively investigated. The present multicenter retrospective observational study provides a complete description of the demographic and clinical characteristics, comorbidities and laboratory abnormalities in a population of 421 hospitalized patients recruited across eight infectious disease units in Southern Italy (Sicily) with the aim of identifying the baseline characteristics predisposing COVID-19 patients to critical illness or death. In this study, older age, pre-existing comorbidities and certain changes in laboratory markers (such as neutrophilia, lymphocytopenia and increased C-reactive protein levels) at the time of admission were associated with a higher risk of mortality. Male sex, on the other hand, was not significantly associated with increased risk of mortality. Symptoms such as fatigue, older age, a number of co-pathologies and use of continuous positive airway pressure were the most significant contributors in the estimation of clinical prognosis. Further research is required to better characterize the epidemiological features of COVID-19, to understand the related predictors of death and to develop new effective therapeutic strategies.

Keywords: SARS-CoV-2; epidemiological features; pandemic; predictors of death.

Figure 1

Distribution of infected people and median age of each group.

Figure 2

Survival probability in relation to age groups. Patients have been stratified and compared according to age in the following groups: <45 years, 45-55 years, 56-65 years, 66-75 years, >75 years.

Figure 3

Decision tree algorithm. The decision tree contains a root node, internal nodes and leaf or terminal nodes. Each leaf is assigned for a class label. The numbers under the leaves represent the output result. For example, D_ICU 28-6 indicates that there were 34 subjects in this class: 28 individuals who died or were transferred to the ICU and 6 individuals who recovered. CPAP, continuous positive airway pressure; R, recovered; D_ICU, died or were transferred to the intensive care unit.