Order of Occurrence of COVID-19 Symptoms. (January 2023)

• Record Type: Journal Article
• Authors: Wojtusiak, Janusz; Bagais, Wejdan; Vang, Jee; Roess, Amira; Alemi, Farrokh
• Is Part Of: Quality management in health care. Volume 32(2023)Supplement 1
• Page Start: S29
• Page End: S34
• Publication Date: 2023-01
• Subjects: COVID-19 diagnosis -- LASSO regression -- order of symptoms -- predictive model -- symptom screening; Medical care -- Quality control -- Periodicals; Total quality management -- Periodicals; Health services administration -- Periodicals; 362.1068
• DOI: 10.1097/QMH.0000000000000397
• Languages: English
• ISSNs: 1063-8628

Abstract

Abstract : Background and Objectives: COVID-19 symptoms change after onset—some show early, others later. This article examines whether the order of occurrence of symptoms can improve diagnosis of COVID-19 before test results are available. Methods: In total, 483 individuals who completed a COVID-19 test were recruited through Listservs. Participants then completed an online survey regarding their symptoms and test results. The order of symptoms was set according to ( a ) whether the participant had a "history of the symptom" due to a prior condition; and ( b ) whether the symptom "occurred first, " or prior to, other symptoms of COVID-19. Two LASSO (Least Absolute Shrinkage and Selection Operator) regression models were developed. The first model, referred to as "time-invariant, " used demographics and symptoms but not the order of symptom occurrence. The second model, referred to as "time-sensitive, " used the same data set but included the order of symptom occurrence. Results: The average cross-validated area under the receiver operating characteristic (AROC) curve for the time-invariant model was 0.784. The time-sensitive model had an AROC curve of 0.799. The difference between the 2 accuracy levels was statistically significant (α < .05). Conclusion: The order of symptom occurrence made a statistically significant, but small, improvement in the accuracy of the diagnosis of COVID-19.