ABSTRACT
OBJECTIVES: Although many demographic and clinical predictors of mortality have been studied in relation to COVID-19, little has been reported about the prognostic utility of inflammatory biomarkers. MATERIAL AND METHODS: Retrospective cohort study. All patients with laboratory-confirmed COVID-19 treated in a hospital emergency department were included consecutively if baseline measurements of the following biomarkers were on record: lymphocyte counts, neutrophil-to-lymphocyte ratio NRL, and C-reactive protein (CRP) and procalcitonin (PCT) levels. We analyzed associations between the biomarkers and all-cause 30-day mortality using Cox regression models and dose-response curves. RESULTS: We included 896 patients, 151 (17%) of whom died within 30 days. The median (interquartile range) age was 63 (51-78) years, and 494 (55%) were men. NLR, CRP and PCT levels at ED presentation were higher, while lymphocyte counts were lower, in patients who died compared to those who survived (P .001). The areas under the receiver operating characteristic curves revealed the PCT concentration (0.79;95% CI, 0.75-0.83) to be a better predictor of 30-day mortality than the lymphocyte count (0.70;95% CI, 0.65-0.74;P .001), the NLR (0.74;95% CI, 0.69-0.78;P = .03), or the CRP level (0.72;95% CI, 0.68-0.76;P .001). The proposed PCT concentration decision points for use in emergency department case management were 0.06 ng/L (negative) and 0.72 ng/L (positive). These cutoffs helped classify risk in 357 patients (40%). Multivariable analysis demonstrated that the PCT concentration had the strongest association with mortality. CONCLUSION: PCT concentration in the emergency department predicts all-cause 30-day mortality in patients with COVID-19 better than other inflammatory biomarkers.
ABSTRACT
OBJECTIVE: With the global spread of COVID-19, studies in the US and UK have shown that certain communities have been strongly impacted by COVID-19 in terms of incidence and mortality. The objective of the study was to determine social determinants of health among COVID-19 patients hospitalized in the two major cities of Spain. METHODS: A multicenter retrospective case series study was performed collecting administrative databases of all COVID-19 patients ≥18 years belonging to two centers in Madrid and two in Barcelona (Spain) collecting data from 1st March to 15th April 2020. Variables obtained age, gender, birthplace and residence ZIP code. From ZIP code we obtained per capita income of the area. Predictors of the outcomes were explored through generalized linear mixed-effects models, using center as random effect. RESULTS: There were 5,235 patients included in the analysis. After multivariable analysis adjusted by age, sex, per capita income, population density, hospital experience, center and hospital saturation, patients born in Latin American countries were found to have an increase in ICU admission rates (OR 1.56 [1.13-2.15], p<0.01) but no differences were found in the same model regarding mortality (OR 1.35 [0.95-1.92], p=0.09). CONCLUSIONS: COVID-19 severity varies widely, not only depending on biological but also socio-economic factors. With the emerging evidence that this subset of population is at higher risk of poorer outcomes, targeted public health strategies and studies are needed.