Predicting delirium in acute ischemic stroke: the PREDELIS score

Background: Delirium, defined as an acute, fluctuating disturbance in consciousness, attention and cognition, is a common stroke complication and associated with poor functional outcome. Although resource-intensive prevention strategies could reduce delirium rates, their implementation in unselected stroke patients is challenging. This study aimed to develop a risk score for predicting delirium in acute ischemic stroke (PREDELIS). Methods: We retrospectively included all ischemic stroke patients admitted to five stroke units of Styria, Austria, between 2013 and 2021. Data were retrieved from a comprehensive medical information system using semi-automated data extraction. The PREDELIS score was based on multivariable logistic regression analysis to identify admission variables associated with delirium. Results: 14,475 acute ischemic stroke patients (median age: 76 years, 46% women) were split in a 40% derivation (n = 6151; delirium = 398, 6.5%) and a 60% validation cohort (n = 8324; delirium: 568, 6.8%). Previous delirium (4 points), chronic alcohol consumption (3), age > 70 years (2), male sex (2), infection (2), admission NIHSS > 7 (1), non-lacunar stroke (1) and vision/hearing impairment (1) were associated with delirium (all p < 0.05) and included in our score (median: 5 points). The score´s area under the curve was 0.72 in both the derivation (95% CI 0.69–0.75) and the validation cohort (95% CI 0.70–0.74). While patients with a score of ≤ 5 had a low delirium risk (2.5%), a score of ≥ 9 indicated a high risk (30.9%). Discussion and conclusion: This study introduces a novel score for early delirium risk estimation in ischemic stroke patients, aiding clinicians in identifying high-risk individuals for targeted screening and prevention.