A predictive score for COVID-19 diagnosis using clinical, laboratory and chest image data
Braz. j. infect. dis
; Braz. j. infect. dis;24(4): 343-348, Jul.-Aug. 2020. tab, graf
Article
em En
| LILACS, ColecionaSUS
| ID: biblio-1132463
Biblioteca responsável:
BR1.1
ABSTRACT
Abstract Objectives Differential diagnosis of COVID-19 includes a broad range of conditions. Prioritizing containment efforts, protective personal equipment and testing can be challenging. Our aim was to develop a tool to identify patients with higher probability of COVID-19 diagnosis at admission. Methods This cross-sectional study analyzed data from 100 patients admitted with suspected COVID-19. Predictive models of COVID-19 diagnosis were performed based on radiology, clinical and laboratory findings; bootstrapping was performed in order to account for overfitting. Results A total of 29% of patients tested positive for SARS-CoV-2. Variables associated with COVID-19 diagnosis in multivariate analysis were leukocyte count ≤7.7 × 103 mm-3, LDH >273 U/L, and chest radiographic abnormality. A predictive score was built for COVID-19 diagnosis, with an area under ROC curve of 0.847 (95% CI 0.77-0.92), 96% sensitivity and 73.5% specificity. After bootstrapping, the corrected AUC for this model was 0.827 (95% CI 0.75-0.90). Conclusions Considering unavailability of RT-PCR at some centers, as well as its questionable early sensitivity, other tools might be used in order to identify patients who should be prioritized for testing, re-testing and admission to isolated wards. We propose a predictive score that can be easily applied in clinical practice. This score is yet to be validated in larger populations.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
LILACS
/
ColecionaSUS
Assunto principal:
Pneumonia Viral
/
Infecções por Coronavirus
/
Técnicas de Laboratório Clínico
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
/
Aged
/
Female
/
Humans
/
Male
Idioma:
En
Revista:
Braz. j. infect. dis
Assunto da revista:
DOENCAS TRANSMISSIVEIS
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Brasil