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Sensitivity and Specificity of Patient-Reported Clinical Manifestations to Diagnose COVID-19 in Adults from a National Database in Chile: A Cross-Sectional Study.
Martinez, Felipe; Muñoz, Sergio; Guerrero-Nancuante, Camilo; Taramasco, Carla.
  • Martinez F; Unidad de Cuidados Intensivos, Hospital Naval Almirante Nef, Viña del Mar 2520000, Chile.
  • Muñoz S; Facultad de Medicina, Escuela de Medicina, Universidad Andrés Bello, Viña del Mar 2531015, Chile.
  • Guerrero-Nancuante C; Concentra Educación e Investigación Biomédica, Viña del Mar 2552906, Chile.
  • Taramasco C; Departamento de Salud Pública-CIGES, Facultad de Medicina, Universidad de La Frontera, Francisco Salazar 1145, Temuco 4811230, Chile.
Biology (Basel) ; 11(8)2022 Jul 29.
Article in English | MEDLINE | ID: covidwho-1969081
ABSTRACT
(1)

Background:

The diagnosis of COVID-19 is frequently made on the basis of a suggestive clinical history and the detection of SARS-CoV-2 RNA in respiratory secretions. However, the diagnostic accuracy of clinical features is unknown. (2)

Objective:

To assess the diagnostic accuracy of patient-reported clinical manifestations to identify cases of COVID-19. (3)

Methodology:

Cross-sectional study using data from a national registry in Chile. Infection by SARS-CoV-2 was confirmed using RT-PCR in all cases. Anonymised information regarding demographic characteristics and clinical features were assessed using sensitivity, specificity, and diagnostic odds ratios. A multivariable logistic regression model was constructed to combine epidemiological risk factors and clinical features. (4)

Results:

A total of 2,187,962 observations were available for analyses. Male participants had a mean age of 43.1 ± 17.5 years. The most common complaints within the study were headache (39%), myalgia (32.7%), cough (31.6%), and sore throat (25.7%). The most sensitive features of disease were headache, myalgia, and cough, and the most specific were anosmia and dysgeusia/ageusia. A multivariable model showed a fair diagnostic accuracy, with a ROC AUC of 0.744 (95% CI 0.743-0.746). (5)

Discussion:

No single clinical feature was able to fully confirm or exclude an infection by SARS-CoV-2. The combination of several demographic and clinical factors had a fair diagnostic accuracy in identifying patients with the disease. This model can help clinicians tailor the probability of COVID-19 and select diagnostic tests appropriate to their setting.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Observational study / Prognostic study / Randomized controlled trials Country/Region as subject: South America / Chile Language: English Year: 2022 Document Type: Article Affiliation country: Biology11081136

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Observational study / Prognostic study / Randomized controlled trials Country/Region as subject: South America / Chile Language: English Year: 2022 Document Type: Article Affiliation country: Biology11081136