Validation of an automated delirium prediction model (DElirium MOdel (DEMO)): an observational study. Issue 11 (8th November 2017) - Mestres Gonzalvo, Carlota; de Wit, Hugo A J M; van Oijen, Brigit P C; Deben, Debbie S; Hurkens, Kim P G M; Mulder, Wubbo J; Janknegt, Rob; Schols, Jos M G A; Verhey, Frans R; Winkens, Bjorn; van der Kuy, Paul-Hugo M
Abstract : Objectives: Delirium is an underdiagnosed, severe and costly disorder, and 30%–40% of cases can be prevented. A fully automated model to predict delirium (DEMO) in older people has been developed, and the objective of this study is to validate the model in a hospital setting. Setting: Secondary care, one hospital with two locations. Design: Observational study. Participants: The study included 450 randomly selected patients over 60 years of age admitted to Zuyderland Medical Centre. Patients who presented with delirium on admission were excluded. Primary outcome measures: Development of delirium through chart review. Results: A total of 383 patients were included in this study. The analysis was performed for delirium within 1, 3 and 5 days after a DEMO score was obtained. Sensitivity was 87.1% (95% CI 0.756 to 0.939), 84.2% (95% CI 0.732 to 0.915) and 82.7% (95% CI 0.734 to 0.893) for 1, 3 and 5 days, respectively, after obtaining the DEMO score. Specificity was 77.9% (95% CI 0.729 to 0.882), 81.5% (95% CI 0.766 to 0.856) and 84.5% (95% CI 0.797 to 0.884) for 1, 3 and 5 days, respectively, after obtaining the DEMO score. Conclusion: DEMO is a satisfactory prediction model but needs further prospective validation with in-person delirium confirmation. In the future, DEMO will be applied in clinical practice so that physicians will be aware of when a patient is at an increased risk of developing delirium, which will facilitate earlier recognition and diagnosis, and thus will allow the implementation of prevention measures.