COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler Looking for Clarity in the Haze of the Pandemic.
Yong HuangMelissa D PintoJessica L BorelliMilad Asgari MehrabadiHeather L AbrahimNikil DuttNatalie LambertErika L NurmiRana ChakrabortyAmir M RahmaniCharles A DownsPublished in: Clinical nursing research (2022)
Post-acute sequelae of SARS-CoV-2 (PASC) is defined as persistent symptoms after apparent recovery from acute COVID-19 infection, also known as COVID-19 long-haul. We performed a retrospective review of electronic health records (EHR) from the University of California COvid Research Data Set (UC CORDS), a de-identified EHR of PCR-confirmed SARS-CoV-2-positive patients in California. The purposes were to (1) describe the prevalence of PASC, (2) describe COVID-19 symptoms and symptom clusters, and (3) identify risk factors for PASC. Data were subjected to non-negative matrix factorization to identify symptom clusters, and a predictive model of PASC was developed. PASC prevalence was 11% (277/2,153), and of these patients, 66% (183/277) were considered asymptomatic at days 0-30. Five PASC symptom clusters emerged and specific symptoms at days 0-30 were associated with PASC. Women were more likely than men to develop PASC, with all age groups and ethnicities represented. PASC is a public health priority.
Keyphrases
- sars cov
- electronic health record
- coronavirus disease
- end stage renal disease
- respiratory syndrome coronavirus
- public health
- newly diagnosed
- ejection fraction
- patient reported
- chronic kidney disease
- liver failure
- peritoneal dialysis
- risk factors
- prognostic factors
- clinical decision support
- type diabetes
- respiratory failure
- patient reported outcomes
- hepatitis b virus
- machine learning
- adipose tissue
- pregnant women
- skeletal muscle
- acute respiratory distress syndrome
- deep learning
- pregnancy outcomes
- physical activity
- data analysis