American Journal of Epidemiology · 2023 · 29 citations · 29 references
MedicineInfectious DiseasesClinical EpidemiologyDisease SurveillanceElectronic Health RecordsComorbidityComorbidity AssessmentComorbidity CaptureElectronic Health Record SurveillanceSymptom ReportingAmbulatory Care UseCohort Study InvestigationComorbidity AnalysisLogistic RegressionLong CovidMultivariable Regression AnalysisPatient Demographic VariablesRetrospective Case Study
Estimates of the prevalence of long-term symptoms of coronavirus disease 2019 (COVID-19), referred to as long COVID, vary widely. This retrospective cohort study describes the incidence of long COVID symptoms 12-20 weeks postdiagnosis in a US ambulatory care setting and identifies potential risk factors. We identified patients with and without a diagnosis of or positive test for COVID-19 between January 1, 2020, and March 13, 2022, in the Veradigm (Veradigm LLC, Chicago, Illinois) electronic health record database. We captured data on patient demographic characteristics, clinical characteristics, and COVID-19 comorbidity in the 12-month baseline period. We compared long COVID symptoms between matched cases and controls 12-20 weeks after the index date (COVID-19 diagnosis date (cases) or median visit date (controls)). Multivariable logistic regression was used to examine associations between baseline COVID-19 comorbid conditions and long COVID symptoms. Among 916,894 patients with COVID-19, 14.8% had at least 1 long COVID symptom in the 12-20 weeks postindex as compared with 2.9% of patients without documented COVID-19. Commonly reported symptoms were joint stiffness (4.5%), cough (3.0%), and fatigue (2.7%). Among patients with COVID-19, the adjusted odds of long COVID symptoms were significantly higher among patients with a baseline COVID-19 comorbid condition (odds ratio = 1.91, 95% confidence interval: 1.88, 1.95). In particular, prior diagnosis of cognitive disorder, transient ischemic attack, hypertension, or obesity was associated with higher odds of long COVID symptoms.
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