Journal article
Evaluation of emergency department derived delirium prediction models using a hospital-wide cohort
Journal of psychosomatic research, Vol.127, pp.109850-109850
12/2019
DOI: 10.1016/j.jpsychores.2019.109850
PMID: 31678811
Abstract
Delirium is acute disorder of attention and cognition. We conducted an observational study using a hospital-wide database to validate three delirium prediction models that were developed to predict prevalent delirium within the first day of hospitalization after ED visit.
This was a retrospective cohort study at the academic medical center to evaluate the predictive ability of three previously developed prediction models for delirium from 2014 to 2017. We included patients aged 65 years and older who were hospitalized from ED. Nurses used the Delirium Observation Screening Scale (DOSS) twice daily while hospitalized. We extracted variables to examine the three prediction models with a positive DOSS screen within the first day of admission. The predictive ability was summarized using the area under the curve (AUC).
We identified 2582 visits with a positive DOSS screen and 877 visits with a diagnosis of delirium from ICD9/10 codes among 12,082 encounters. The AUC of these prediction models ranged from 0.71 to 0.80 when predicting a positive DOSS screen, and 0.68 to 0.72 when predicting a ICD9/10 diagnosis of delirium. In our cohort, the delirium risk score which uses the cutoff of positive or negative predicted DOSS positive delirium with the AUC of 0.8 (p < .0001). The model demonstrated the sensitivity and the specificity of 91.2 (95% CI 90.0–92.3) and 50.3 (95% CI 49.3–51.3).
In this study, the delirium risk score had the highest predictive ability for prevalent delirium defined by a positive DOSS within the first day of hospitalization.
•Delirium is a common and serious brain dysfunction among older adults.•About 18% of hospitalized older adults screened positive for delirium.•The delirium risk score showed the highest ability to predict delirium.
Details
- Title: Subtitle
- Evaluation of emergency department derived delirium prediction models using a hospital-wide cohort
- Creators
- Sangil Lee - Department of Emergency Medicine, University of Iowa Carver College of Medicine, United States of AmericaKarisa Harland - Department of Emergency Medicine, University of Iowa Carver College of Medicine, United States of AmericaNicholas M Mohr - Department of Emergency Medicine, Anesthesia and Critical Care, University of Iowa Carver College of Medicine, United States of AmericaGrace Matthews - University of Iowa Hospitals and Clinics, United States of AmericaErik P Hess - Department of Emergency Medicine, University of Alabama at Birmingham, United States of AmericaM. Fernanda Bellolio - Department of Emergency Medicine, Mayo Clinic, United States of AmericaJin H Han - Department of Emergency Medicine, Vanderbilt University School of Medicine, United States of AmericaMichelle Weckmann - Department of Family Medicine and Psychiatry, University of Iowa Carver College of Medicine, United States of AmericaRyan Carnahan - University of Iowa College of Public Health, United States of America
- Resource Type
- Journal article
- Publication Details
- Journal of psychosomatic research, Vol.127, pp.109850-109850
- DOI
- 10.1016/j.jpsychores.2019.109850
- PMID
- 31678811
- NLM abbreviation
- J Psychosom Res
- ISSN
- 0022-3999
- eISSN
- 1879-1360
- Publisher
- Elsevier Inc
- Grant note
- name: University of Iowa Carver College of Medicine
- Language
- English
- Date published
- 12/2019
- Academic Unit
- Psychiatry; Epidemiology; Emergency Medicine; Family and Community Medicine; Nursing; Anesthesia; Injury Prevention Research Center; Law Faculty
- Record Identifier
- 9984214785702771
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