The Diagnostic Evaluation of Clinical Symptoms and Signs for COVID¬-19
in hospitalized patients of Northern Iran
Abstract
Background: A novel coronavirus, led to a rapidly spreading outbreak of
COVID¬19 which caused morbidity and mortality worldwide. Appropriate
case definitions can help in diagnosing COVID¬19. The aim of this study
was to evaluate the existing and potential syndromic case definitions of
COVID¬19 using latent class analyses (LCA) among hospitalized patients
of North Iran. Methods. The data of this cross-sectional study was
collected from hospitalized patients tested for COVID-¬19 by RT-PCR
between February 20 and August 20, 2020. The sensitivity, specificity,
positive, and negative predictive values, and the area under the ROC
curve (AUC) of each syndromic pattern (standard case definitions and
alternative case definition patterns from Latent Class Analysis (LCA))
were compared and plotted. Results. Among 7,784 hospitalized patients
tested for COVID¬19 and included in the analyses, 2,233 (28, 7%) had
RT-PCR confirmed COVID-19. The symptoms of fever & chills, cough,
breathing difficulty, myalgia, sore throat, headache; and the signs of
body temperature >37.8, pharyngeal exudate, and abnormal
chest radiography were informative in all syndromic patterns. Among
latent classes, symptom-class 3 that was comprised of fever & chills,
cough, and breathing difficulty had the greatest AUC. While, among
standard syndromic patterns, the WHO-acute respiratory infection (ARI),
suspected-COVID-19 and probable-COVID-19 definitions had the greatest
sensitivity and AUC. Conclusion. The WHO ARI, suspected-COVID-19, and
probable-COVID-19 patterns were the most sensitive for detecting
COVID-19 infection among hospitalized patients. However, alternative
syndromic patterns can be used in case high specificity is required.