COVID-Q: validation of the first COVID-19 questionnaire based on
patient-rated symptom gravity
Abstract
Objectives The aim of the present study is to develop and validate the
COVID-Q, a novel symptom questionnaire specific for COVID-19 patients,
to provide a comprehensive and standard clinical evaluation. A secondary
goal of the present study was to evaluate the performance of the COVID-Q
in identifying subjects at higher risk of being tested positive for
COVID-19. Material and methods 460 subjects (230 COVID-19 cases and 230
healthy controls), answered the COVID-Q. Parallel Analysis and Principal
Component Analysis were used to identify clusters of items measuring the
same dimension. The IRT-based analyses evaluated the functioning of item
categories, the presence of clusters of local dependence among items,
item fit within the model and model fit to the data. Results Parallel
analysis suggested the extraction of six components, which corresponded
to as many clinical presentation patterns: asthenia, influenza-like
symptoms, ear and nose symptoms, breathing issues, throat symptoms, and
anosmia/ageusia. The final IRT models retained 27 items as significant
for symptom assessment. The total score on the questionnaire was
significantly associated with positivity to the molecular SARS-CoV-2
test. Subjects with multiple symptoms were significantly more likely to
be affected by COVID-19 (p < .001). Older age and male gender
also represented risk factors. None of the examined comorbidities had a
significant association with COVID-19 diagnosis. Conclusion The
application of the novel COVID-Q to everyday clinical practice may help
identifying subjects who are likely to be affected by COVID-19 and
address them to a nasopharyngeal swab in order to achieve an early
diagnosis.