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Objective The intracerebral hemorrhage (ICH) score was developed to enhance provider communication and facilitate early severity assessment. We examined the association of the ICH score with mortality and withdrawal of life‐sustaining treatment (WLST) in a large, multicenter stroke registry, and evaluated temporal trends in these associations. Methods We identified ICH patients from the Florida Stroke Registry from 2013 to 2022. Outcomes were WLST and in‐hospital mortality. ICH scores were grouped as 0–2, 3–4, and 5–6. Importance plots identified key predictors of WLST. Model performance was assessed using AUC‐ROC for logistic regression and random forest, adjusted for relevant confounders. Secondary analyses compared outcomes between 2015–2018 and 2019–2022 using stratified univariate logistic regression. Results In total, 12,426 patients were included (mean age 69, 55% male, 56% white). The most predictive factors associated with WLST were ICH score, age, state region, presenting level of consciousness, insurance status, and race (RF AUC = 0.94, LR AUC = 0.82). Mortality was 6.6%, 41.5%, and 66% for ICH score 0–2, 3–4, and 5–6. WLST occurred more frequently in higher ICH score groups (OR 9.35 [95% CI: 8.5–10.3] for scores 3–4; OR 18.64 [95% CI: 15.28–22.74] for scores 5–6). Early WLST (< 48 h) was more common in higher score groups (OR 2.97 [95% CI: 2.48–3.55] for 3–4; OR 9.51 [95% CI: 7.33–12.35] for 5–6). Interpretation Higher ICH scores were strongly associated with mortality and WLST, including early withdrawal decisions. These associations remained largely consistent over time. These observational findings underscore the need for continued attention to how prognostic scores may influence WLST decisions.

Background Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI. Methods This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine. Results We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50 years, p  = 0.01). Patients who recovered also had higher Kolcom ( U  = 1688, p  = 0.01), increased beta power ( U  = 1,652 p  = 0.003) with higher variability across channels ( U  = 1534, p  = 0.034) and epochs ( U  = 1711, p  = 0.004), lower delta power ( U  = 981, p  = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band ( U  = 1636, p  = 0.026; U  = 1639, p  = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p  < 0.001). Conclusions We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.