Rest-activity patterns associated with delirium in patients with intracerebral hemorrhage.

BACKGROUND: Delirium is an acute cognitive disturbance frequently characterized by abnormal psychomotor activity and sleep-wake cycle disruption. However, the degree to which delirium affects activity patterns in the acute period after stroke is unclear. We aimed to examine these patterns in a cohort of patients with intracerebral hemorrhage (ICH). METHODS: We enrolled 40 patients with intracerebral hemorrhage (ICH) who had daily DSM-5-based delirium assessments. Continuous activity measurements were captured using bilateral wrist actigraphs throughout each patient's admission. Activity data were collected in 1-min intervals, with "rest" defined as periods with zero activity. We compared differences in activity based on delirium status across multiple time intervals using multivariable models adjusted for age, ICH severity, and mechanical ventilation. RESULTS: There were 279 days of actigraphy monitoring, of which 199 (71%) were rated as days with delirium. In multivariable analyses, delirium was associated with 98.4 (95% CI 10.4-186.4) fewer daily minutes of rest, including 5.3% (95% CI -0.1-10.1%) fewer minutes during daytime periods (06:00-21:59) and 10.2% (95% CI 1.9-18.4%) fewer minutes during nocturnal periods (22:00-5:59), with higher levels of activity across multiple individual hourly intervals (18:00-21:00, 23:00-03:00, and 04:00-08:00). These differences were even more pronounced in hyperactive or mixed delirium, although even hypoactive delirium was associated with more activity during multiple time periods. CONCLUSIONS: Post-stroke delirium is associated with less rest and higher overall levels of activity, especially during nocturnal periods.

Delirium detection using wearable sensors and machine learning in patients with intracerebral hemorrhage.

Objective: Delirium is associated with worse outcomes in patients with stroke and neurocritical illness, but delirium detection in these patients can be challenging with existing screening tools. To address this gap, we aimed to develop and evaluate machine learning models that detect episodes of post-stroke delirium based on data from wearable activity monitors in conjunction with stroke-related clinical features. Design: Prospective observational cohort study. Setting: Neurocritical Care and Stroke Units at an academic medical center. Patients: We recruited 39 patients with moderate-to-severe acute intracerebral hemorrhage (ICH) and hemiparesis over a 1-year period [mean (SD) age 71.3 (12.20), 54% male, median (IQR) initial NIH Stroke Scale 14.5 (6), median (IQR) ICH score 2 (1)]. Measurements and main results: Each patient received daily assessments for delirium by an attending neurologist, while activity data were recorded throughout each patient's hospitalization using wrist-worn actigraph devices (on both paretic and non-paretic arms). We compared the predictive accuracy of Random Forest, SVM and XGBoost machine learning methods in classifying daily delirium status using clinical information alone and combined with actigraph data. Among our study cohort, 85% of patients (n = 33) had at least one delirium episode, while 71% of monitoring days (n = 209) were rated as days with delirium. Clinical information alone had a low accuracy in detecting delirium on a day-to-day basis [accuracy mean (SD) 62% (18%), F1 score mean (SD) 50% (17%)]. Prediction performance improved significantly (p < 0.001) with the addition of actigraph data [accuracy mean (SD) 74% (10%), F1 score 65% (10%)]. Among actigraphy features, night-time actigraph data were especially relevant for classification accuracy. Conclusions: We found that actigraphy in conjunction with machine learning models improves clinical detection of delirium in patients with stroke, thus paving the way to make actigraph-assisted predictions clinically actionable.

Radiographic predictors of aneurysmal etiology in patients with aneurysmal pattern subarachnoid hemorrhage.

OBJECTIVE: Spontaneous angiogram-negative nonperimesencephalic subarachnoid hemorrhage (an-NPSAH) can represent a diagnostic and management dilemma. The authors sought to determine radiographic predictors of aneurysmal etiology based on admission noncontrast head CT scans. METHODS: The authors performed a retrospective cohort study of prospectively collected data from consecutive patients who were admitted for spontaneous subarachnoid hemorrhage (SAH) with suspected aneurysmal etiology to an academic center from 2016 to 2021. They compared blood thickness in the basal cisterns and sylvian fissures and modified Graeb scores on admission head CT scans between the two groups and subsequently developed a predictive model to identify aneurysmal etiology. RESULTS: Of 259 included patients (mean age 56 years [SD 12.7 years]; 55% female), 209 had aneurysmal SAH (aSAH) and 50 had an-NPSAH. The median modified Graeb scores were similar for aSAH and an-NPSAH (6 [IQR 2-10] vs 3.5 [IQR 0-8.5], p = 0.33). The mean blood thickness was greater in the sylvian fissure (p = 0.010) and interhemispheric cisterns (p = 0.002), and there was a greater median degree of extension of blood in the sylvian fissures (p = 0.001) in aSAH than in an-NPSAH patients, but the mean blood thickness was less in the prepontine cistern (p = 0.014). The authors' scoring model was constructed based on differences in radiographic features. Receiver operating characteristic curve analysis showed acceptable accuracy in predicting aneurysmal etiology (area under the curve 0.71, 95% CI 0.62-0.79). CONCLUSIONS: There are differences in radiographic features on admission head CT between an-NPSAH and aSAH patients. The authors' proposed risk stratification model may be considered for further development and use in clinical practice in the future.

Cisternal Score: A Radiographic Score to Predict Ventriculoperitoneal Shunt Requirement in Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Persistent hydrocephalus requiring a ventriculoperitoneal shunt (VPS) can complicate the management of aneurysmal subarachnoid hemorrhage (aSAH). Identification of high-risk patients may guide external ventricular drain management. OBJECTIVE: To identify early radiographic predictors for persistent hydrocephalus requiring VPS placement. METHODS: In a 2-center retrospective study, we compared radiographic features on admission noncontrast head computed tomography scans of patients with aSAH requiring a VPS to those who did not, at 2 referral academic centers from 2016 through 2021. We quantified blood clot thickness in the basal cisterns including interpeduncular, ambient, crural, prepontine, interhemispheric cisterns, and bilateral Sylvian fissures. We then created the cisternal score (CISCO) using features that were significantly different between groups. RESULTS: We included 229 survivors (mean age 55.6 years [SD 13.1]; 63% female) of whom 50 (22%) required VPS. CISCO was greater in patients who required a VPS than those who did not (median 4, IQR 3-6 vs 2, IQR 1-4; P < .001). Higher CISCO was associated with higher odds of developing persistent hydrocephalus with VPS requirement (odds ratio 1.6 per point increase, 95% CI 1.34-1.9; P < .001), independent of age, Hunt and Hess grades, and modified GRAEB scores. CISCO had higher accuracy in predicting VPS requirement (area under the curve 0.75, 95% CI 0.68-0.82) compared with other predictors present on admission. CONCLUSION: Cisternal blood clot quantification on admission noncontrast head computed tomography scan is feasible and can be used in predicting persistent hydrocephalus with VPS requirement in patients with aSAH. Future prospective studies are recommended to further validate this tool.

A quantitative model to differentiate nonaneurysmal perimesencephalic subarachnoid hemorrhage from aneurysmal etiology.

OBJECTIVE: Nonaneurysmal perimesencephalic subarachnoid hemorrhage (pmSAH) is considered to have a lower-risk pattern than other types of subarachnoid hemorrhage (SAH). However, a minority of patients with pmSAH may harbor a causative posterior circulation aneurysm. To exclude this possibility, many institutions pursue exhaustive imaging. In this study the authors aimed to develop a novel predictive model based on initial noncontrast head CT (NCHCT) features to differentiate pmSAH from aneurysmal causes. METHODS: The authors retrospectively reviewed patients admitted to an academic center for treatment of a suspected aneurysmal SAH (aSAH) during the period from 2016 to 2021. Patients with a final diagnosis of pmSAH or posterior circulation aSAH were included. Using NCHCT, the thickness (continuous variable) and location of blood in basal cisterns and sylvian fissures (categorical variables) were compared between groups. A scoring system was created using features that were significantly different between groups. Receiver operating characteristic curve analysis was used to measure the accuracy of this model in predicting aneurysmal etiology. A separate patient cohort was used for external validation of this model. RESULTS: Of 420 SAH cases, 48 patients with pmSAH and 37 with posterior circulation aSAH were identified. Blood thickness measurements in the crural and ambient cisterns and interhemispheric and sylvian fissures and degree of extension into the sylvian fissure were all significantly different between groups (all p < 0.001). The authors developed a 10-point scoring model to predict aneurysmal causes with high accuracy (area under the curve [AUC] 0.99; 95% CI 0.98-1.00; OR per point increase 10; 95% CI 2.18-46.4). External validation resulted in persistently high accuracy (AUC 0.97; 95% CI 0.92-1.00) of this model. CONCLUSIONS: A risk stratification score using initial blood clot burden may accurately differentiate between aneurysmal and nonaneurysmal pmSAH. Larger prospective studies are encouraged to further validate this quantitative tool.

A Pilot Study of the Fluctuating Mental Status Evaluation: A Novel Delirium Screening Tool for Neurocritical Care Patients.

BACKGROUND: Delirium occurs frequently in patients with stroke and neurocritical illness but is often underrecognized. We developed a novel delirium screening tool designed specifically for neurocritical care patients called the fluctuating mental status evaluation (FMSE) and aimed to test its usability and accuracy in a representative cohort of patients with intracerebral hemorrhage (ICH). METHODS: We performed a single-center prospective study in a pilot cohort of patients with ICH who had daily delirium assessments throughout their admission. Reference-standard expert ratings were performed each afternoon using criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and were derived from bedside assessments and clinical data from the preceding 24 h. Paired FMSE assessments were performed by patients' clinical nurses after receiving brief one-on-one training from research staff. Nursing assessments were aggregated over 24-h periods (including day and night shifts), and accuracy of the FMSE was analyzed in patients who were not comatose to determine optimal scoring thresholds. RESULTS: We enrolled 40 patients with ICH (mean age 71.1 ± 12.2, 55% male, median National Institutes of Health Stroke Scale score 16.5 [interquartile range 12-20]), of whom 85% (n = 34) experienced delirium during their hospitalization. Of 308 total coma-free days with paired assessments, 208 (68%) were rated by experts as days with delirium. Compared with expert ratings, FMSE scores ≥ 1 had 86% sensitivity and 73% specificity on a per-day basis, whereas FMSE scores ≥ 2 had 68% sensitivity and 82% specificity. Accuracy remained high in patients with aphasia (FMSE scores ≥ 1: 83% sensitivity, 77% specificity; FMSE scores ≥ 2: 68% sensitivity, 85% specificity) and decreased arousal (FMSE scores ≥ 1: 80% sensitivity, 100% specificity; FMSE scores ≥ 2: 73% sensitivity, 100% specificity). CONCLUSIONS: In this pilot study, the FMSE achieved a high sensitivity and specificity in detecting delirium. Follow-up validation studies in a larger more diverse cohort of neurocritical care patients will use score cutoffs of ≥ 1 as "possible" delirium and ≥ 2 as "probable" delirium.

Short- and long-term opioid use in survivors of subarachnoid hemorrhage.

OBJECTIVES: Opioids are frequently used for analgesia in patients with acute subarachnoid hemorrhage (SAH) due to a high prevalence of headache and neck pain. However, it is unclear if this practice may pose a risk for opioid dependence, as long-term opioid use in this population remains unknown. We sought to determine the prevalence of opioid use in SAH survivors, and to identify potential risk factors for opioid utilization. METHODS: We analyzed a cohort of consecutive patients admitted with non-traumatic and suspected aneurysmal SAH to an academic referral center. We included patients who survived hospitalization and excluded those who were not opioid-naïve. Potential risk factors for opioid prescription at discharge, 3 and 12 months post-discharge were assessed. RESULTS: Of 240 SAH patients who met our inclusion criteria (mean age 58.4 years [SD 14.8], 58% women), 233 (97%) received opioids during hospitalization and 152 (63%) received opioid prescription at discharge. Twenty-eight patients (12%) still continued to use opioids at 3 months post-discharge, and 13 patients (6%) at 12-month follow up. Although patients with poor Hunt and Hess grades (odds ratio 0.19, 95% CI 0.06-0.57) and those with intraventricular hemorrhage (odds ratio 0.38, 95% CI 0.18-0.87) were less likely to receive opioid prescriptions at discharge, we did not find significant differences between patients who had long-term opioid use and those who did not. CONCLUSION: Opioids are regularly used in both the acute SAH setting and immediately after discharge. A considerable number of patients also continue to use opioids in the long-term. Opioid-sparing pain control strategies should be explored in the future.

Association of Early White Blood Cell Trend with Outcomes in Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: An increasing white blood cell (WBC) count in early course of aneurysmal subarachnoid hemorrhage (SAH) can indicate a systemic inflammatory state triggered by the initial insult. We sought to determine the significance of the early WBC trend as a potential predictor of outcomes. METHODS: We analyzed a cohort of consecutive patients with aneurysmal SAH. The WBC values in first 5 days of admission, plus relevant clinical and imaging data, and modified Rankin Scale (mRS) at 3 months after hospital discharge were retrieved and analyzed. Favorable outcome was defined as mRS 0-3. The association between WBC counts and outcomes including mRS and delayed cerebral ischemia (DCI) was determined using binary logistic regression models. We used receiver operating characteristic curve analysis to assess accuracy of WBC in predicting outcomes. RESULTS: We included 167 patients in final analysis. Mean age was 56.4 (standard deviation [SD] 14.8) years, and 65% (109) of patients were female. Peak WBC was greater in patients with poor functional outcome (mean 17 × 109 cells/L, SD 6.4 vs. 13.5 × 109 cells/L SD 4.7). Combining peak WBC with modified Fisher scale slightly increased accuracy in predicting DCI (area under the curve 0.670, 95% confidence interval 0.586-0.755) compared with each component alone. CONCLUSIONS: WBC count in the early course of SAH may have prognostic values in predicting DCI and functional outcome. WBC count monitoring may be used in conjunction with other clinical and radiographic tools to stratify patients with SAH into high- and low-risk groups to tailor neuromonitoring and treatment strategies.

Common biomarkers of physiologic stress and associations with delirium in patients with intracerebral hemorrhage.

PURPOSE: To examine associations between physiologic stress and delirium in the setting of a direct neurologic injury. MATERIALS AND METHODS: We obtained initial neutrophil-to-lymphocyte ratio (NLR), glucose, and troponin in consecutive non-comatose patients with non-traumatic intracerebral hemorrhage (ICH) over 1 year, then used multivariable regression models to determine associations between each biomarker and incident delirium. Delirium diagnoses were established using DSM-5-based methods, with exploratory analyses further categorizing delirium as first occurring <24 h ("early-onset") or > 24 h after presentation ("later-onset"). RESULTS: Of 284 patients, delirium occurred in 55% (early-onset: 39% [n = 111]; later-onset: 16% [n = 46]). Patients with delirium had higher NLR (mean 9.0 ± 10.4 vs. 6.4 ± 5.5; p = 0.01), glucose (mean 146.5 ± 59.6 vs. 129.9 ± 41.4 mg/dL; p = 0.008), and a higher frequency of elevated troponin (>0.05 ng/mL; 21% vs. 10%, p = 0.02). In adjusted models, elevated NLR (highest quartile: OR 3.4 [95% CI 1.5-7.8]), glucose (>180 mg/dL: OR 3.1 [95% CI 1.1-8.2]), and troponin (OR 3.0 [95% CI 1.2-7.2]) were each associated with delirium, but only initial NLR was specifically associated with later-onset delirium and with delirium in non-mechanically ventilated patients. CONCLUSIONS: Stress-related biomarkers corresponding to multiple organ systems are associated with ICH-related delirium. Early NLR elevation may also predict delayed-onset delirium, potentially implicating systemic inflammation as a contributory delirium mechanism.

The impact of delirium on withdrawal of life-sustaining treatment after intracerebral hemorrhage.

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 patients with ICH 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 Glasgow Coma Scale score), then used logistic regression with receiver operating characteristic 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 [interquartile range 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 hazard ratio 8.9 [95% confidence interval (CI) 2.1-37.6]), with high rates of WLST in both early (occurring ≤24 hours from admission) and later delirium groups. An ICH score-based model was strongly predictive of WLST (area under the curve [AUC] 0.902 [95% CI 0.863-0.941]), and 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.

Arrival blood pressure in hypertensive and non-hypertensive spontaneous intracerebral hemorrhage.

BACKGROUND AND PURPOSE: Hypertension is a known risk factor for intracerebral hemorrhage (ICH), but it is unclear whether blood pressure (BP) at hospital arrival can be used to distinguish hypertensive ICH from non-hypertensive etiologies. PATIENTS AND METHODS: We performed a single-center cohort study using data from consecutive ICH patients over 12 months. ICH characteristics including etiology were prospectively adjudicated by two attending neurologists. Using adjusted linear regression models, we compared first recorded systolic BPs (SBP) and mean arterial pressures (MAP) in patients with hypertensive vs. other ICH etiologies. We then used area under the ROC curve (AUC) analysis to determine the accuracy of admission BP in differentiating between hypertensive and non-hypertensive ICH. RESULTS: Of 311 patients in our cohort (mean age 70.6 ± 15.6, 50% male, 83% white), the most frequent ICH etiologies were hypertension (50%) and cerebral amyloid angiopathy (CAA; 22%). Mean SBP and MAP for patients with hypertensive ICH was 175.1 ± 32.9 mmHg and 120.4 ± 22.9 mmHg, respectively, compared to 156.4 ± 28.0 mmHg and 109.6 ± 20.3 mmHg in non-hypertensive ICH (p < .001). Adjusted models showed that hypertensive ICH patients had higher BPs than those with CAA (mean SBP difference 10.7 mmHg [95% CI 0.8-20.5]; mean MAP difference 8.1 mmHg [1.1-15.0]) and especially patients with other non-CAA causes (mean SBP difference 23.9 mmHg [15.3-32.4]; mean MAP difference 14.5 mmHg [8.5-20.6]). However, on a patient-level, arrival BP did not reliably discriminate between hypertensive and non-hypertensive etiologies (AUC 0.660 [0.599-0.720]). CONCLUSIONS: Arrival BP differs between hypertensive and non-hypertensive ICH but should not be used as a primary determinant of etiology, as hypertension may be implicated in various subtypes of ICH.

Serum alpha-1 antitrypsin in acute ischemic stroke: A prospective pilot study.

BACKGROUND: Alpha-1 antitrypsin (AAT) is a potent anti-protease enzyme which may play a role in arterial wall stability. A variant of its encoding gene has been recently linked to ischemic stroke due to large artery atherosclerosis (LAA). We sought to explore potential relationships between ischemic stroke mechanisms, atherosclerosis burden and serum AAT levels. METHODS: We performed a prospective observational study of consecutive patients with acute ischemic stroke who were admitted to an academic comprehensive stroke center over a three-month period. Blood samples were collected within 24 h of hospital admission, and stroke subtype classification was determined based on modified TOAST criteria. Modified Woodcock scoring system was used to quantify calcification of major cervico-cranial arteries as a surrogate for atherosclerosis burden. Linear regression analysis was used to assess the association between serum AAT levels and calcification scores, both as continuous variables. RESULTS: Among eighteen patients met our inclusion criteria and were enrolled in our study, 10 patients (56%) were men; mean age was 66 (SD 12.5); median NIH stroke scale was 4 (IQR 9.5); 8 patients (44%) had stroke due to LAA. The median serum level of AAT was 140 mg/dl (IQR 41.7) for patients with LAA-related stroke, and 148.5 mg/dl (IQR 37.7) for patients with other stroke mechanisms (p = 0.26). Higher serum AAT levels was associated with lower modified Woodcock calcification scores. (p-value = 0.038) CONCLUSIONS: Measurement of AAT levels in patients with acute stroke is feasible, and there may be associations between AAT levels and stroke mechanism that warrant further study in larger samples.

Deconstructing Poststroke Delirium in a Prospective Cohort of Patients With Intracerebral Hemorrhage.

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.

An overlooked connection: serotonergic mediation of estrogen-related physiology and pathology.

BACKGROUND: In humans, serotonin has typically been investigated as a neurotransmitter. However, serotonin also functions as a hormone across animal phyla, including those lacking an organized central nervous system. This hormonal action allows serotonin to have physiological consequences in systems outside the central nervous system. Fluctuations in estrogen levels over the lifespan and during ovarian cycles cause predictable changes in serotonin systems in female mammals. DISCUSSION: We hypothesize that some of the physiological effects attributed to estrogen may be a consequence of estrogen-related changes in serotonin efficacy and receptor distribution. Here, we integrate data from endocrinology, molecular biology, neuroscience, and epidemiology to propose that serotonin may mediate the effects of estrogen. In the central nervous system, estrogen influences pain transmission, headache, dizziness, nausea, and depression, all of which are known to be a consequence of serotonergic signaling. Outside of the central nervous system, estrogen produces changes in bone density, vascular function, and immune cell self-recognition and activation that are consistent with serotonin's effects. For breast cancer risk, our hypothesis predicts heretofore unexplained observations of the opposing effects of obesity pre- and post-menopause and the increase following treatment with hormone replacement therapy using medroxyprogesterone. SUMMARY: Serotonergic mediation of estrogen has important clinical implications and warrants further evaluation.