Prediction of ICU Delirium: Validation of Current Delirium Predictive Models in Routine Clinical Practice*

Prediction of ICU Delirium: Validation of Current Delirium Predictive Models in Routine Clinical Practice*

by Green, Cameron; Bonavia, William; Toh, Candice; Tiruvoipati, Ravindranath  

Critical Care Medicine: March 2019 - Volume 47 - Issue 3 - p 428–435

Objectives: To investigate the ability of available delirium risk assessment tools to identify patients at risk of delirium in an Australian tertiary ICU.

Design: Prospective observational study.

Setting: An Australian tertiary ICU. Patients: All patients admitted to the study ICU between May 8, 2017, and December 31, 2017, were assessed bid for delirium throughout their ICU stay using the Confusion Assessment Method for ICU. Patients were included in this study if they remained in ICU for over 24 hours and were excluded if they were delirious on ICU admission, or if they were unable to be assessed using the Confusion Assessment Method for ICU during their ICU stay. Delirium risk was calculated for each patient using the prediction of delirium in ICU patients, early prediction of delirium in ICU patients, and Lanzhou models. Data required for delirium predictor models were obtained retrospectively from patients medical records. Interventions: None.

Measurements and Main Results: There were 803 ICU admissions during the study period, of which 455 met inclusion criteria. 35.2% (n = 160) were Confusion Assessment Method for ICU positive during their ICU admission. Delirious patients had significantly higher Acute Physiology and Chronic Health Evaluation III scores (median, 72 vs 54; p < 0.001), longer ICU (median, 4.8 vs 1.8 d; p < 0.001) and hospital stay (16.0 vs 8.16 d; p < 0.001), greater requirement of invasive mechanical ventilation (70% vs 21.4%; p < 0.001), and increased ICU mortality (6.3% vs 2.4%; p = 0.037). All models included in this study displayed moderate to good discriminative ability. Area under the receiver operating curve for the prediction of delirium in ICU patients was 0.79 (95% CI, 0.75–0.83); recalibrated prediction of delirium in ICU patients was 0.79 (95% CI, 0.75–0.83); early prediction of delirium in ICU patients was 0.72 (95% CI, 0.67–0.77); and the Lanzhou model was 0.77 (95% CI, 0.72–0.81). Conclusions: The predictive models evaluated in this study demonstrated moderate to good discriminative ability to predict ICU patients’ risk of developing delirium. Models calculated at 24-hours post-ICU admission appear to be more accurate but may have limited utility in practice.