Delirium prediction in the intensive care unit: Comparison of two delirium prediction models

BACKGROUND: Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. METHODS: This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults... Mehr ...

Verfasser: Wassenaar, Annelies
Schoonhoven, Lisette
Devlin, John W.
van Haren, Frank M.P.
Slooter, Arjen J.C.
Jorens, Philippe G.
van der Jagt, Mathieu
Simons, Koen S.
Egerod, Ingrid
Burry, Lisa D.
Beishuizen, Albertus
Matos, Joaquim
Donders, A. Rogier T.
Pickkers, Peter
van den Boogaard, Mark
Dokumenttyp: Artikel
Erscheinungsdatum: 2018
Schlagwörter: Adult / Clinical prediction / Critical illness / Delirium / Intensive care unit / Prospective Studies / Area Under Curve / United States / Humans / Middle Aged / Male / Portugal / Netherlands / Female / Decision Support Techniques / Canada / Belgium / Intensive Care Units/organization & administration / Denmark / ROC Curve / Aged / Australia / Delirium/diagnosis / APACHE / Cohort Studies / Critical Care and Intensive Care Medicine / Clinical Trial / Multicenter Study / Journal Article
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27352925
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://dspace.library.uu.nl/handle/1874/374224

BACKGROUND: Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. METHODS: This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h. RESULTS: In total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71-0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66-0.71)) (z score of - 2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible. CONCLUSIONS: While both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02518646 . Registered on 21 July 2015.