ABSTRACT
Although control of Covid-19 has improved, the virus continues to cause infections, such as tuberculosis, that is still endemic in many countries, representing a scenario of coinfection. To compare Covid-19 clinical manifestations and outcomes between patients with active tuberculosis infection and matched controls. This is a matched case-control study based on data from the Brazilian Covid-19 Registry, in hospitalized patients aged 18 or over with laboratory confirmed Covid-19 from March 1, 2020, to March 31, 2022. Cases were patients with tuberculosis and controls were Covid-19 patients without tuberculosis. From 13,636 Covid-19, 36 also had active tuberculosis (0.0026%). Pulmonary fibrosis (5.6% vs 0.0%), illicit drug abuse (30.6% vs 3.0%), alcoholism (33.3% vs 11.9%) and smoking (50.0% vs 9.7%) were more common among patients with tuberculosis. They also had a higher frequency of nausea and vomiting (25.0% vs 10.4%). There were no significant differences in in-hospital mortality, mechanical ventilation, need for dialysis and ICU stay. Patients with TB infection presented a higher frequency of pulmonary fibrosis, abuse of illicit drugs, alcoholism, current smoking, symptoms of nausea and vomiting. The outcomes were similar between them.
Subject(s)
COVID-19 , Coinfection , Hospitalization , SARS-CoV-2 , Humans , COVID-19/complications , Male , Brazil/epidemiology , Case-Control Studies , Female , Middle Aged , Coinfection/epidemiology , Hospitalization/statistics & numerical data , Adult , Registries , Tuberculosis/complications , Tuberculosis/epidemiology , Hospital Mortality , Pandemics , Aged , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Betacoronavirus , Coronavirus Infections/complications , Coronavirus Infections/epidemiologyABSTRACT
OBJECTIVES: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. METHODS: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. RESULTS: Median (25-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829-0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833-0.885]) and Spanish (0.894 [95% CI 0.870-0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). CONCLUSIONS: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.
