Long-Term Outcomes in ICU Patients with Delirium: A Population-based Cohort Study.

Rationale: Delirium is common in the ICU and portends worse ICU and hospital outcomes. The effect of delirium in the ICU on post-hospital discharge mortality and health resource use is less well known. Objectives: To estimate mortality and health resource use 2.5 years after hospital discharge in critically ill patients admitted to the ICU. Methods: This was a population-based, propensity score-matched, retrospective cohort study of adult patients admitted to 1 of 14 medical-surgical ICUs from January 1, 2014, to June 30, 2016. Delirium was measured by using the 8-point Intensive Care Delirium Screening Checklist. The primary outcome was mortality. The secondary outcome was a composite measure of subsequent emergency department visits, hospital readmission, or mortality. Measurements and Main Results: There were 5,936 propensity score-matched patients with and without a history of incident delirium who survived to hospital discharge. Delirium was associated with increased mortality 0-30 days after hospital discharge (hazard ratio, 1.44 [95% confidence interval, 1.08-1.92]). There was no significant difference in mortality more than 30 days after hospital discharge (delirium: 3.9%, no delirium: 2.6%). There was a persistent increased risk of emergency department visits, hospital readmissions, or mortality after hospital discharge (hazard ratio, 1.12 [95% confidence interval, 1.07-1.17]) throughout the study period. Conclusions: ICU delirium is associated with increased mortality 0-30 days after hospital discharge.

Delirium diagnosis without a gold standard: Evaluating diagnostic accuracy of combined delirium assessment tools.

BACKGROUND: Fluctuating course of delirium and complexities of ICU care mean delirium symptoms are hard to identify or commonly confused with other disorders. Delirium is difficult to diagnose, and clinicians and researchers may combine assessments from multiple tools. We evaluated diagnostic accuracy of different combinations of delirium assessments performed in each enrolled patient. METHODS: Data were obtained from a previously conducted cross-sectional study. Eligible adult patients who remained admitted to ICU for >24 hours with at least one family member present were consecutively enrolled as patient-family dyads. Clinical delirium assessments (Intensive Care Delirium Screening Checklist [ICSDC] and Confusion Assessment Method-ICU [CAM-ICU]) were completed twice daily by bedside nurse or trained research assistant, respectively. Family delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily by family members. We pooled all delirium assessment tools in a single two-class latent model and pairwise (i.e., combined, clinical or family assessments) Bayesian analyses. RESULTS: Seventy-three patient-family dyads were included. Among clinical delirium assessments, the ICDSC had lower sensitivity (0.72; 95% Bayesian Credible [BC] interval 0.54-0.92) and higher specificity (0.90; 95%BC, 0.82-0.97) using Bayesian analyses compared to pooled latent class analysis and CAM-ICU had higher sensitivity (0.90; 95%BC, 0.70-1.00) and higher specificity (0.94; 95%BC, 0.80-1.00). Among family delirium assessments, the Family Confusion Assessment Method had higher sensitivity (0.83; 95%BC, 0.71-0.92) and higher specificity (0.93; 95%BC, 0.84-0.98) using Bayesian analyses compared to pooled latent class analysis and the Sour Seven had higher specificity (0.85; 95%BC, 0.67-0.99) but lower sensitivity (0.64; 95%BC 0.47-0.82). CONCLUSIONS: Results from delirium assessment tools are often combined owing to imperfect reference standards for delirium measurement. Pairwise Bayesian analyses that explicitly accounted for each tool's (performed within same patient) prior sensitivity and specificity indicate that two combined clinical or two combined family delirium assessment tools have fair diagnostic accuracy.