TY - JOUR
T1 - Validation of an automated delirium prediction model (DElirium MOdel (DEMO))
T2 - an observational study
AU - Gonzalvo, Carlota Mestres
AU - de Wit, Hugo A. J. M.
AU - van Oijen, Brigit P. C.
AU - Deben, Debbie S.
AU - Hurkens, Kim P. G. M.
AU - Mulder, Wubbo J.
AU - Janknegt, Rob
AU - Schols, Jos M. G. A.
AU - Verhey, Frans R.
AU - Winkens, Bjorn
AU - van der Kuy, Paul-Hugo M.
PY - 2017/11
Y1 - 2017/11
N2 - 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.
AB - 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.
KW - HOSPITALIZED OLDER PATIENTS
KW - CONFUSION ASSESSMENT METHOD
KW - CRITICALLY-ILL PATIENTS
KW - ANTIPSYCHOTIC MEDICATION
KW - PRECIPITATING FACTORS
KW - METAANALYSIS
KW - RISK
KW - PROPHYLAXIS
KW - INSTRUMENTS
KW - POPULATION
U2 - 10.1136/bmjopen-2017-016654
DO - 10.1136/bmjopen-2017-016654
M3 - Article
C2 - 29122789
SN - 2044-6055
VL - 7
JO - BMJ Open
JF - BMJ Open
IS - 11
M1 - 016654
ER -