RESUMO
Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care.
Assuntos
Assistência Ambulatorial , Teste para COVID-19/métodos , COVID-19/diagnóstico , Dor Abdominal/fisiopatologia , Adolescente , Adulto , COVID-19/fisiopatologia , Estudos de Casos e Controles , Regras de Decisão Clínica , Tosse/fisiopatologia , Diarreia/fisiopatologia , Progressão da Doença , Dispneia/fisiopatologia , Feminino , Febre/fisiopatologia , Cefaleia/fisiopatologia , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Mialgia/fisiopatologia , Razão de Chances , Seleção de Pacientes , Faringite/fisiopatologia , Rinorreia/fisiopatologia , SARS-CoV-2 , Sensibilidade e Especificidade , Índice de Gravidade de Doença , Adulto JovemRESUMO
An 18-month epidemiologic investigation of Candida bloodstream infections in a Singapore hospital identified 52 candidemic patients: 36% of whose infections were caused by C. tropicalis, 29% were due to C. albicans, 10% with C. parapsilosis and 21% involved C. glabrata. A predominant clonal C. tropicalis strain was demonstrated. No association with ICU stay, prior exposure to fluconazole/broad-spectrum antibiotics or increased mortality was found in this apparent shift towards non-C. albicans Candida species as the primary agents of candidemia.