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Utilizing group-based models to identify adverse event patterns after an intervention
Wei Wang1, Sara Abbaspour2, Kimberly G Blumenthal3
1Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Background:
Standard adverse event (AE) monitoring only records whether events occur after the intervention, and not whether these events vary over time.
Objective:
To test whether there were statistically distinct time-varying trajectories of AE (e.g., "side effects") after an intervention and identify characteristics of individuals associated with these patterns.
Design:
Group-based trajectory models applied to an observational study of individuals who received one or two doses of a mRNA COVID-19 vaccine (i.e., the intervention).
Participants:
50,484 healthcare personnel who received their vaccinations within the Mass General Brigham (MGB) healthcare system.
Interventions:
Vaccination.
Main Measures:
Allergic and non-allergic AE for 1-3 days after each of two COVID-19 vaccinations.
Key Results:
Trajectories models identified distinct groups with different trajectories after intervention: two groups after the first vaccination and five groups after the second vaccination. These groups differed by demographics, age, prior prescription for epinephrine auto-injectors, prior COVID-19 history, time-of-day of vaccination, and vaccine manufacturer.
Conclusion:
Several different time-based trajectories after the intervention (e.g., first two COVID-19 vaccinations) were noted; individuals in these groups varied by demographic and clinical criteria. These time-based methods may be able to identify groups at higher risk of future adverse reactions, provide a basis for future studies of the physiology underlying these risk differentials, and improve counseling surrounding interventions associated with AEs. We suggest that trajectory-based methods be added to post-intervention surveillance.
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