Characteristic Adverse Events and Their Incidence Among Patients Participating in Acute Ischemic Stroke Trials

BACKGROUND AND PURPOSE: Adverse events (AE) in trial populations present a major burden to researchers and patients, yet most events are unrelated to investigational treatment. We aimed to develop a coherent list of expected AEs, whose incidence can be predicted by patient characteristics that will inform future trials and perhaps general poststroke care. METHODS: We analyzed raw AE data from patients participating in acute ischemic stroke trials. We identified events that occurred with a lower 99% confidence bound greater than nil. Among these, we applied receiver operating characteristic principles to select the fewest types of events that together represented the greatest number of reports. Using ordinal logistic regression, we modeled the incidence of these events as a function of patient age, sex, baseline National Institutes of Health Stroke Scale, and multimorbidity status, defining P<0.05 as statistically significant. RESULTS: We analyzed 5775 placebo-treated patients, reporting 21 217 AEs. Among 756 types of AEs, 132 accounted for 82.7%, of which 80% began within 10 days after stroke. Right hemisphere (odds ratio [OR], 1.67), increasing baseline National Institutes of Health Stroke Scale (OR, 1.11), multimorbidity status (OR, 1.09 per disease), patient age (OR, 1.01 per year), height (OR, 1.01 per centimeter), diastolic blood pressure (OR, 0.99 per mm Hg), and smoking (OR, 0.82) were independently associated with developing more AEs but together explained only 13% of the variation. CONCLUSIONS: A list of 132 expected AEs after acute ischemic stroke may be used to simplify interpretation and reporting of complications. AEs can be modestly predicted by patient characteristics, facilitating stratification of patients by risk for poststroke complications.