Predictors of post-acute sequelae of coronavirus disease 2019 and long COVID in adults and children: a retrospective cohort study using us electronic health record data.

OBJECTIVE

This study examined the incidence and predictors of post-acute sequelae of COVID-19 (PASC) and Long COVID in adults and children with confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Associations assessed included demographic factors, comorbidities, lab markers, and patient clinical complications.

METHOD: A retrospective cohort of 13,940 patients with confirmed SARS-CoV-2 infection (7836 adults and 6104 children) from the Optum® COVID-19 Electronic Health Record dataset was analyzed (1 June 2020-30 June 2021). PASC was defined as symptoms lasting <3 months postinfection and Long COVID as symptoms ≥3 months. Inclusion criteria were patients of all ages with a confirmed SARS-CoV-2 infection. Excluded from the study were patients in the Texas Department of Criminal Justice system and patients with active HIV, malignancy, or respiratory viral/bacterial infection. Statistical analyses (chi-square, Mann-Whitney U, multivariable logistic regression) were performed using Microsoft Excel and IBM Statistical Package for the Social Sciences statistics V.25.

RESULTS

Symptoms consistent with PASC were reported by 21.5% of adult patients, with 8.8% reporting Long COVID; 10.5% of pediatric patients reported PASC, with 9% reporting Long COVID (P < .05). In adults, predictors of PASC included age ≥54, female sex, non-Caucasian race, smoking, obesity, pneumonia, and multiple comorbidities; higher red blood cell count was protective. Predictors of Long COVID in adults was associated with female sex, obesity, and heart disease. In children, predictors of PASC included female sex and comorbidities. Younger age (≤10 years) was a significant predictor of Long COVID in children.

CONCLUSIONS AND PUBLIC HEALTH IMPLICATIONS: Protocols that include targeted follow-up and early intervention are needed for post-COVID conditions in high-risk individuals across age groups. Integrating predictive markers into routine care could enhance preparedness and resilience against future waves of post-viral syndromes.