Objectives: Poststroke delirium may be underdiagnosed due to the challenges of disentangling delirium symptoms from underlying neurologic deficits. We aimed to determine the prevalence of individual delirium features and the frequency with which they could not be assessed in patients with intracerebral hemorrhage. Design: Prospective observational cohort study. Setting: Neurocritical Care and Stroke Units at a university hospital. Patients: Consecutive patients with intracerebral hemorrhage from February 2018 to May 2018. Interventions: None. Measurements and Main Results: An attending neurointensivist performed 257 total daily assessments for delirium on 60 patients (mean age 68.0 [sd 18.4], 62% male, median intracerebral hemorrhage score 1.5 [interquartile range 1–2], delirium prevalence 57% [n = 34]). Each assessment included the Confusion Assessment Method for the ICU, Intensive Care Delirium Screening Checklist, a focused bedside cognitive examination, chart review, and nurse interview. We characterized individual symptom prevalence and established delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria, then compared performance of the Confusion Assessment Method for the ICU and Intensive Care Delirium Screening Checklist against reference-standard expert diagnosis. Symptom fluctuation (61% of all assessments), psychomotor changes (46%), sleep-wake disturbances (46%), and impaired arousal (37%) had the highest prevalence and were never rated “unable to assess,” while inattention (36%), disorientation (27%), and disorganized thinking (18%) were also common but were often rated "unable to assess" (32%, 43%, and 44% of assessments, respectively), most frequently due to aphasia (32% of patients). Including nonverbal assessments of attention decreased the frequency of "unable to assess" ratings to 11%. Since the Intensive Care Delirium Screening Checklist may be positive without the presence of symptoms that require verbal assessment, it was more accurate (sensitivity = 77%, specificity = 97%, area under the receiver operating characteristic curve, 0.87) than the Confusion Assessment Method for the ICU (sensitivity = 41%, specificity = 88%, area under the receiver operating characteristic curve, 0.64). Conclusions: Delirium is common after intracerebral hemorrhage, but severe neurologic deficits may confound its assessment and lead to underdiagnosis. The Intensive Care Delirium Screening Checklist’s inclusion of nonverbal features may make it more accurate than the Confusion Assessment Method for the ICU in patients with neurologic deficits, but novel tools designed for such patients may be warranted.

Objective:To determine the impact of delirium on withdrawal of life-sustaining treatment (WLST) after intracerebral hemorrhage (ICH) in the context of established predictors of poor outcome, using data from an institutional ICH registry.Methods:We performed a single-center cohort study on consecutive ICH patients admitted over 12 months. ICH features were prospectively adjudicated, and WLST and corresponding hospital day were recorded retrospectively. Patients were categorized using DSM-5 criteria as never delirious, ever delirious (either on admission or later during hospitalization), or persistently comatose. We determined the impact of delirium on WLST using Cox regression models adjusted for demographics and ICH predictors (including GCS score), then used logistic regression with ROC curve analysis to compare the accuracy of ICH score-based models with and without delirium category in predicting WLST.Results:Of 311 patients (mean age 70.6±15.6, median ICH score 1 [IQR 1-2]), 50% had delirium. WLST occurred in 26%, and median time-to-WLST was 1 day (0-6). WLST was more frequent in patients who developed delirium (adjusted HR 8.9 [95% CI 2.1-37.6]), with high rates of WLST in both “early” (occurring ≤24 hours from admission) and “later” delirium groups. While an ICH score-based model was strongly predictive of WLST (AUC 0.902 [95% CI 0.863-0.941]), the addition of delirium category further improved the model’s accuracy (AUC 0.936 [95% CI 0.909-0.962], p=0.004).Conclusion:Delirium is associated with WLST after ICH regardless of when it occurs. Further study on the impact of delirium on clinician and surrogate decision-making is warranted.