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Intracranial hemorrhage is a life-threatening condition, the outcome of which can be improved by intensive care. Intracranial hemorrhage may be spontaneous, precipitated by an underlying vascular malformation, induced by trauma, or related to therapeutic anticoagulation. The goals of critical care are to assess the proximate cause, minimize the risks of hemorrhage expansion through blood pressure control and correction of coagulopathy, and obliterate vascular lesions with a high risk of acute rebleeding. Simple bedside scales and interpretation of computed tomography scans assess the severity of neurological injury. Myocardial stunning and pulmonary edema related to neurological injury should be anticipated, and can usually be managed. Fever (often not from infection) is common and can be effectively treated, although therapeutic cooling has not been shown to improve outcomes after intracranial hemorrhage. Most functional and cognitive recovery takes place weeks to months after discharge; expected levels of functional independence (no disability, disability but independence with a device, dependence) may guide conversations with patient representatives. Goals of care impact mortality, with do-not-resuscitate status increasing the predicted mortality for any level of severity of intraparenchymal hemorrhage. Future directions include refining the use of bedside neuro-monitoring (electroencephalogram, invasive monitors), novel approaches to reduce intracranial hemorrhage expansion, minimizing vasospasm, and refining the assessment of quality of life to guide rehabilitation and therapy. [ABSTRACT FROM AUTHOR]

Background: Many ICUs have implemented protocols for tight glucose control, but there are few data on hypoglycemia and neurologic outcomes in patients with subarachnoid hemorrhage (SAH).Methods: We prospectively ascertained 172 patients with SAH, who were treated according to a standard protocol for target glucose 80-110 mg/dl. Outcomes were assessed with the modified Rankin scale (mRS) at 14 days, 28 days, and 3 months.Results: Worse neurologic injury at admission (P < 0.001) and a history of diabetes (P = 0.002) were associated with increased glucose variance. There was lower nadir glucose in patients with radiographic cerebral infarction (81 +/- 15 vs. 87 +/- 16 mg/dl, P = 0.02), symptomatic vasospasm (78 +/- 12 vs. 84 +/- 16 mg/dl, P = 0.04) and angiographic vasospasm (79 +/- 14 vs. 86 +/- 16 mg/dl, P = 0.01), but maximum and mean glucose values were not different. Glucose < 80 mg/dl was earlier and more frequent in patients with worse functional outcome at 3 months (P < 0.001). Progressive reductions in nadir glucose were associated with increasing functional disability at 3 months (P = 0.001) after accounting for neurologic grade and mean glucose. Severe hypoglycemia (<40 mg/dl) occurred in one patient.Conclusions: In patients with SAH, nadir glucose < 80 mg/dl is associated with cerebral infarction, vasospasm, and worse functional outcomes in multivariate models. Protocols for target glucose 80-110 mg/dl effectively control hyperglycemia, but may place patients with SAH at risk for vasospasm, cerebral infarction, and poor outcome even when severe hypoglycemia does not occur. [ABSTRACT FROM AUTHOR]

Introduction: There are few predictors of acute lung injury (ALI) or the acute respiratory distress syndrome (ARDS) after subarachnoid hemorrhage (SAH). We hypothesized that cardiac troponin I, which is associated with cardiovascular morbidity, would also predict ALI.Methods: We prospectively enrolled 171 consecutive patients with SAH. Troponin was routinely measured on admission and the next day and subsequently if abnormal. We prospectively recorded the maximum troponin, in-hospital events, and clinical endpoints. ALI and ARDS were defined by standard criteria.Results: Acute lung injury was found in 10 patients (6%), ARDS in an additional 14 (8%), and pulmonary edema without lung injury in 9 (5%). Maximum troponin was different in patients without lung injury or pulmonary edema (0.03 [0.02-0.12] mcg/l), ALI (0.17 [0.04-1.4]), or ARDS (0.31 [0.9-1.8], P < 0.001). In ROC analysis, a cutoff of 0.04 mcg/l had 91% sensitivity and 42% specificity for ALI or ARDS (AUC = 0.75, P < 0.001). Troponin was associated with ALI or ARDS after accounting for neurologic grade in multivariate models without further contribution from pneumonia, packed red cell transfusion, gender, tobacco use, coronary artery disease, vasospasm, depressed ejection fraction on echocardiography, or CT grade. Lung injury was associated with worse functional outcome at 14 days, but not at 28 days or 3 months.Conclusion: Troponin I is associated with the development of ALI after SAH. [ABSTRACT FROM AUTHOR]

Introduction: Severity of illness scores predict all-cause mortality after intracerebral hemorrhage (ICH), but do not differentiate between proximate mechanisms or predict the timing. We hypothesized that death by neurologic criteria [brain death (BD)], withdrawal of life support, and cardiovascular death would be distinct after ICH.Methods: We prospectively enrolled patients with spontaneous ICH without underlying vascular malformation or neoplasm. We recorded clinical data and the proximate mechanism of death (BD, withdrawal of life support, cardiovascular death, or other cause). Time to death was compared with Kaplan-Meier methods (log-rank test). Data are median (IQR).Results: Among 89 patients, 15 had withdrawal of life support, 5 had BD, 2 died from cardiac arrest, and 3 died from other causes. Among patients who died, ICH score, age, Glasgow Coma Scale, NIH Stroke Scale, and proximate cause were not associated with the proximate mechanism of death. The time to death was different (P < 0.001) depending on the proximate mechanism. Patients with BD died 1 [0-1] 1 day after ICH, withdrawal of life support led to death 5 [1-13] days after ICH, cardiac death occurred 35 [35-85] days after ICH, and other causes led to death 33 [26-33] days after ICH. Among patients where life support was withdrawn, a higher ICH score on admission was related to earlier death (P = 0.002).Conclusions: Proximate mechanisms of death after ICH occur at distinct times. Withdrawal of life support leads to earlier death in patients with a higher severity of injury. Medical causes of death can be effectively prevented after ICH. [ABSTRACT FROM AUTHOR]

OBJECTIVE: There are few data regarding anemia and transfusion after subarachnoid hemorrhage (SAH). We addressed the hypothesis that higher hemoglobin (HGB) levels are associated with less death and disability after SAH. DESIGN: Prospective registry with automated data retrieval. PATIENTS: Six hundred eleven patients enrolled in the Columbia University SAH Outcomes Project between August 1996 and June 2002. SETTING: Neurologic intensive care unit. INTERVENTIONS: Patients were treated according to standard management protocols. MEASUREMENTS AND MAIN RESULTS: We electronically retrieved all HGB readings during the acute hospital stay for 611 consecutively admitted SAH patients. Outcomes were measured with the modified Rankin Scale at 14 days or discharge, and at 3 months. Patients who were independent (modified Rankin Scale, 0-3) at discharge or 14 days had higher mean (11.7 +/- 1.5 vs. 10.9 +/- 1.2, p < .001) and nadir (9.9 +/- 2.1 vs. 8.6 +/- 1.8, p < .001) HGB, and had higher HGB values every day in the hospital. There were similar results when patients were stratified by mortality. Higher HGB was associated with reduced risk of poor outcome (modified Rankin Scale, 4-6) at 14 days/discharge and 3 months after correcting for Hunt and Hess grade, age, history of diabetes, and cerebral infarction. Length of stay and HGB interacted such that lower HGB has a more pronounced effect with length of stay > 14 days. CONCLUSIONS: Higher HGB values are associated with improved outcomes after SAH at 14 days/discharge and 3 months. In contrast to general critical care patients, SAH patients may benefit from higher HGB. Determination of the optimal goal HGB after SAH will require separate prospective research. [ABSTRACT FROM AUTHOR]

Purpose To develop a highly generalizable weakly supervised model to automatically detect and localize image-level intracranial hemorrhage (ICH) by using study-level labels. Materials and Methods In this retrospective study, the proposed model was pretrained on the image-level Radiological Society of North America dataset and fine-tuned on a local dataset by using attention-based bidirectional long short-term memory networks. This local training dataset included 10 699 noncontrast head CT scans in 7469 patients, with ICH study-level labels extracted from radiology reports. Model performance was compared with that of two senior neuroradiologists on 100 random test scans using the McNemar test, and its generalizability was evaluated on an external independent dataset. Results The model achieved a positive predictive value (PPV) of 85.7% (95% CI: 84.0, 87.4) and an area under the receiver operating characteristic curve of 0.96 (95% CI: 0.96, 0.97) on the held-out local test set ( n = 7243, 3721 female) and 89.3% (95% CI: 87.8, 90.7) and 0.96 (95% CI: 0.96, 0.97), respectively, on the external test set ( n = 491, 178 female). For 100 randomly selected samples, the model achieved performance on par with two neuroradiologists, but with a significantly faster ( P < .05) diagnostic time of 5.04 seconds per scan (vs 86 seconds and 22.2 seconds for the two neuroradiologists, respectively). The model's attention weights and heatmaps visually aligned with neuroradiologists' interpretations. Conclusion The proposed model demonstrated high generalizability and high PPVs, offering a valuable tool for expedited ICH detection and prioritization while reducing false-positive interruptions in radiologists' workflows. Keywords: Computer-Aided Diagnosis (CAD), Brain/Brain Stem, Hemorrhage, Convolutional Neural Network (CNN), Transfer Learning Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Akinci D'Antonoli and Rudie in this issue.

Background: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning., Methods: We used patient data from two US medical centers and the Antihypertensive Treatment of Acute Cerebral Hemorrhage-II clinical trial. We used k-prototypes to partition patient admission data. We then used silhouette method calculations and elbow method heuristics to optimize the clusters. Associations between phenotypes, complications (e.g., seizures), and functional outcomes were assessed using the Kruskal-Wallis H-test or χ 2 test., Results: There were 916 patients; the mean age was 63.8 ± 14.1 years, and 426 patients were female (46.5%). Three distinct clinical phenotypes emerged: patients with small hematomas, elevated blood pressure, and Glasgow Coma Scale scores > 12 (n = 141, 26.6%); patients with hematoma expansion and elevated international normalized ratio (n = 204, 38.4%); and patients with median hematoma volumes of 24 (interquartile range 8.2-59.5) mL, who were more frequently Black or African American, and who were likely to have intraventricular hemorrhage (n = 186, 35.0%). There were associations between clinical phenotype and seizure (P = 0.024), length of stay (P = 0.001), discharge disposition (P < 0.001), and death or disability (modified Rankin Scale scores 4-6) at 3-months' follow-up (P < 0.001). We reproduced these three clinical phenotypes of ICH in an independent cohort (n = 385) for external validation., Conclusions: Machine learning identified three phenotypes of ICH that are clinically significant, associated with patient complications, and associated with functional outcomes. Cerebellar hematomas are an additional phenotype underrepresented in our data sources., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Objective: Hematoma expansion (HE) predicts disability and death after acute intracerebral hemorrhage (ICH). Aspirin and anticoagulants have been associated with HE. We tested the hypothesis that P2Y12 inhibitors predict subsequent HE in patients. We explored laboratory measures of P2Y12 inhibition and dual antiplatelet therapy with aspirin (DAPT)., Methods: We prospectively identified patients with ICH. Platelet activity was measured with the VerifyNow-P2Y12 assay. Hematoma volumes for initial and follow-up CTs were calculated using a validated semi-automated technique. HE was defined as the difference between hematoma volumes on the initial and follow-up CT scans. Nonparametric statistics were performed with Kruskal-Wallis H, and correction for multiple comparisons performed with Dunn's test., Results: In 194 patients, 15 (7.7%) were known to take a P2Y12 inhibitor (clopidogrel in all but one). Patients taking a P2Y12 inhibitor had more HE compared to patients not taking a P2Y12 inhibitor (3.5 [1.2-11.9] vs. 0.1 [-0.8-1.4] mL, p = 0.004). Patients taking DAPT experienced the most HE (7.2 [2.6-13.8] vs. 0.0 [-1.0-1.1] mL, p = 0.04). The use of P2Y12 inhibitors was associated with less P2Y12 activity (178 [149-203] vs. 288 [246-319] P2Y12 reaction units, p = 0.005)., Interpretation: Patients taking a P2Y12 inhibitor had more HE and less P2Y12 activity. The effect was most pronounced in patients on DAPT, suggesting a synergistic effect of P2Y12 inhibitors and aspirin with respect to HE. Acute reversal of P2Y12 inhibitors in acute ICH requires further study., (© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Objectives: Four-factor prothrombin complex concentrate (4-PCC) is recommended for rapid reversal of vitamin K antagonists (VKAs) such as warfarin, yet optimal dosing remains uncertain., Data Sources: A systematic review was conducted of PubMed, Embase, and Ovid MEDLINE (Wolters Kluwer) databases from January 2000 to August 2023 for clinical studies comparing fixed- vs. variable-dose 4-PCC for emergent VKA reversal with at least one reported clinical outcome., Study Selection: Abstracts and full texts were assessed independently and in duplicate by two reviewers., Data Extraction: Data were extracted independently and in duplicate by two reviewers using predefined extraction forms., Data Synthesis: The analysis comprised three randomized trials and 16 cohort studies comprising a total of 323 participants in randomized trials (161 in fixed dosage and 162 in variable dosage) and 1912 patients in cohort studies (858 in fixed-dose and 1054 in variable dose). Extracranial bleeding was the predominant indication, while intracranial hemorrhage varied. Overall, a fixed-dose regimen may be associated with a lower dose of 4-PCC and results in a reduction in 4-PCC administration time compared with a variable-dose regimen. A fixed-dose regimen also likely results in increased clinical hemostasis. While there is no clear difference between the two regimens in terms of achieving a goal international normalized ratio (INR) less than 2, a fixed-dose regimen is less likely to achieve a goal INR less than 1.5. High certainty evidence indicates that the fixed-dose regimen reduces both mortality and the occurrence of thromboembolic events. Additional subgroup analyses provides exploratory data to guide future studies., Conclusions: A fixed-dose regimen for 4-PCC administration provides benefits over a variable-dose regimen in terms of dose reduction, faster administration time, improved clinical hemostasis, and reduced mortality and thromboembolic events. Further studies are warranted to better refine the optimal fixed-dose regimen., Competing Interests: Dr. Naidech’s institution received funding from the National Institute of Neurological Disorders; he received funding from the National Institutes of Health (NIH); he disclosed that they participated in a Society of Critical Care Medicine board review course; and he received support for article research from the NIH. Dr. Potts disclosed that he has stock in a biomedical device company. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.)

During the first COVID surge, multiple changes in nurse staffing and workflows were made to support care delivery in a resource-constrained environment. We hypothesized that there was a higher rate of inpatient falls during the COVID surge. Furthermore, we predicted that an automated predictive analytic algorithm would perform as well as the Johns Hopkins Fall Risk Assessment. A retrospective review of falls for 3 months before and the first 3 months of the first COVID surge was conducted. We determined the total number of falls and the overall fall rate and examined the distribution of scores and accuracy of fall predictive models for both groups. There was a statistically significant increase in fall rate during the first 3 months of the COVID surge compared with the 3 prior months (2.48/1000 patient-days vs 1.89/1000 patient-days respectively; P = .041). The Johns Hopkins instrument had a greater sensitivity of 78.9% compared with 57.0% for the predictive analytic model. Specificity and accuracy of the predictive analytic model were higher than the Johns Hopkins instrument (71.3% vs 54.1% and 71.2% vs 54.3%, respectively). These findings suggest that the automated predictive analytic model could be used in a resource-constrained environment to accurately classify patients' risk of fall., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Acute blood pressure (BP) reduction is standard of care after acute intracerebral haemorrhage (ICH). More acute BP reduction is associated with acute kidney injury (AKI). It is not known if the choice of antihypertensive medications affects the risk of AKI., Methods: We analysed data from the ATACH-II clinical trial. AKI was defined by the Kidney Disease: Improving Global Outcomes criteria. We analysed antihypertensive medication from two sources. The first was a case report form that specified the use of labetalol, diltiazem, urapidil or other. We tested the hypothesis that the secondary medication was associated with AKI with χ 2 test. Second, we tested the hypotheses the dosage of diltiazem was associated with AKI using Mann-Whitney U test., Results: AKI occurred in 109 of 1000 patients (10.9%). A higher proportion of patients with AKI received diltiazem after nicardipine (12 (29%) vs 21 (12%), p=0.03). The 95%ile (90%-99% ile) of administered diltiazem was 18 (0-130) mg in patients with AKI vs 0 (0-30) mg in patients without AKI (p=0.002). There was no apparent confounding by indication for diltiazem use., Conclusions: The use of diltiazem, and more diltiazem, was associated with AKI in patients with acute ICH., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The last decade has seen significant advances in the accumulation of medical data, the computational techniques to analyze that data, and corresponding improvements in management. Interventions such as thrombolytics and mechanical thrombectomy improve patient outcomes after stroke in selected patients; however, significant gaps remain in our ability to select patients, predict complications, and understand outcomes. Big data and the computational methods needed to analyze it can address these gaps. For example, automated analysis of neuroimaging to estimate the volume of brain tissue that is ischemic and salvageable can help triage patients for acute interventions. Data-intensive computational techniques can perform complex risk calculations that are too cumbersome to be completed by humans, resulting in more accurate and timely prediction of which patients require increased vigilance for adverse events such as treatment complications. To handle the accumulation of complex medical data, a variety of advanced computational techniques referred to as machine learning and artificial intelligence now routinely complement traditional statistical inference. In this narrative review, we explore data-intensive techniques in stroke research, how it has informed the management of stroke patients, and how current work could shape clinical practice in the future., (© 2023. The American Society for Experimental Neurotherapeutics, Inc.)

Randomized clinical trials of acute stroke have led to major advances in acute stroke therapy over the past decade. Despite these successes, recruitment in acute trials is often difficult. We outline challenges in recruitment for acute stroke trials and present potential solutions, which can increase the speed and decrease the cost of identifying new treatments for acute stroke. One of the largest opportunities to increase the speed of enrollment and make trials more generalizable is expansion of inclusion criteria whose impact on expected recruitment can be assessed by epidemiologic and registry databases. Another barrier to recruitment besides the number of eligible patients is availability of study investigators limited to business hours, which may be helped by financial support for after-hours call. The wider use of telemedicine has accelerated quicker stroke treatment at many hospitals and has the potential to accelerate research enrollment but requires training of clinical investigators who are often inexperienced with this approach. Other potential solutions to enhance recruitment include rapid prehospital notification of clinical investigators of potential patients, use of mobile stroke units, advances in the process of emergency informed consent, storage of study medication in the emergency department, simplification of study treatments and data collection, education of physicians to improve equipoise and enthusiasm for randomization of patients within a trial, and clear recruitment plans, and even potentially coenrollment, when there are competing trials at sites. Without successful recruitment, scientific advances and clinical benefit for acute stroke patients will lag.

Background: Seizures are a harmful complication of acute intracerebral hemorrhage (ICH). "Early" seizures in the first week after ICH are a risk factor for deterioration, later seizures, and herniation. Ideally, seizure medications after ICH would only be administered to patients with a high likelihood to have seizures. We developed and validated machine learning (ML) models to predict early seizures after ICH., Methods: We used two large datasets to train and then validate our models in an entirely independent test set. The first model ("CAV") predicted early seizures from a subset of variables of the CAVE score (a prediction rule for later seizures)-cortical hematoma location, age less than 65 years, and hematoma volume greater than 10 mL-whereas early seizure was the dependent variable. We attempted to improve on the "CAV" model by adding anticoagulant use, antiplatelet use, Glasgow Coma Scale, international normalized ratio, and systolic blood pressure ("CAV + "). For each model we used logistic regression, lasso regression, support vector machines, boosted trees (Xgboost), and random forest models. Final model performance was reported as the area under the receiver operating characteristic curve (AUC) using receiver operating characteristic models for the test data. The setting of the study was two large academic institutions: institution 1, 634 patients; institution 2, 230 patients. There were no interventions., Results: Early seizures were predicted across the ML models by the CAV score in test data, (AUC 0.72, 95% confidence interval 0.62-0.82). The ML model that predicted early seizure better in the test data was Xgboost (AUC 0.79, 95% confidence interval 0.71-0.87, p = 0.04) compared with the CAV model AUC., Conclusions: Early seizures after ICH are predictable. Models using cortical hematoma location, age less than 65 years, and hematoma volume greater than 10 mL had a good accuracy rate, and performance improved with more independent variables. Additional methods to predict seizures could improve patient selection for monitoring and prophylactic seizure medications., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Introduction: Intracerebral hemorrhage is the deadliest form of stroke. Hematoma expansion, growth of the hematoma between the baseline computed tomography scan and a follow-up computed tomography scan at 24 ± 6 h, predicts long-term disability or death. Recombinant factor VIIa (rFVIIa) has reduced hematoma expansion in previous clinical trials with a variable effect on clinical outcomes, with the greatest impact on hematoma expansion and potential benefit when administered within 2 h of symptom onset., Methods: Factor VIIa for Hemorrhagic Stroke Treatment at Earliest Possible Time (FASTEST, NCT03496883) is a randomized controlled trial that will enroll 860 patients at ∼100 emergency departments and mobile stroke units in five countries. Patients are eligible for enrollment if they have acute intracerebral hemorrhage within 2 h of symptom onset confirmed by computed tomography, a hematoma volume of 2 to 60 mL, no or small volumes of intraventricular hemorrhage, do not take anticoagulant medications or concurrent heparin/heparinoids (antiplatelet medications are permissible), and are not deeply comatose. Enrolled patients will receive rFVIIa 80 µg/kg or placebo intravenously over 2 min. The primary outcome measure is the distribution of the ordinal modified Rankin Scale at 180 days. FASTEST is monitored by a Data Safety Monitoring Board. Safety endpoints include thrombotic events (e.g. myocardial infarction). Human subjects research is monitored by an external Institutional Review Board in participating countries., Discussion: In the US, FASTEST will be first NIH StrokeNet Trial with an Exception from Informed Consent which allows enrollment of non-communicative patients without an immediately identifiable proxy.

Background: To test the hypothesis that appearances of intracranial hematomas on diagnostic computed tomography (CT) are not idiosyncratic and reflect a biologically plausible mechanism, we evaluated the association between hematoma appearance on CT, biomarkers of platelet activity, and antiplatelet or anticoagulant medication use prior to admission., Methods: We studied 330 consecutively identified patients from 2006 to 2019. Biomarkers of platelet activity (platelet aspirin assay) and medication history (aspirin, clopidogrel) were prospectively recorded on admission. A blinded interpreter recorded the presence of hematoma appearances from the diagnostic scan. Associations were tested with parametric or nonparametric statistics, as appropriate., Results: The black hole sign (101, 30%) was most prevalent, followed by the island sign (57, 17%) and blend sign (32, 10%). There was reduced platelet activity in patients with a black hole sign (511 [430-610] vs. 562 [472-628] aspirin reaction units, P = 0.01) or island sign (505 [434-574] vs. 559 [462-629] aspirin reaction units, P = 0.004). Clopidogrel use prior to admission was associated with the black hole sign (odds ratio 2.25, 95% confidence interval 1.02-4.98, P = 0.04)., Conclusions: In patients with acute intracerebral hemorrhage, hematoma appearances on CT are associated with biomarkers of platelet activity and clopidogrel use prior to admission. Appearances of intracranial hematomas on CT may reflect reduced hemostasis from antiplatelet medication use., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Background and Purpose: Prioritizing reading of noncontrast head CT examinations through an automated triage system may improve time to care for patients with acute neuroradiologic findings. We present a natural language-processing approach for labeling findings in noncontrast head CT reports, which permits creation of a large, labeled dataset of head CT images for development of emergent-finding detection and reading-prioritization algorithms., Materials and Methods: In this retrospective study, 1002 clinical radiology reports from noncontrast head CTs collected between 2008 and 2013 were manually labeled across 12 common neuroradiologic finding categories. Each report was then encoded using an n-gram model of unigrams, bigrams, and trigrams. A logistic regression model was then trained to label each report for every common finding. Models were trained and assessed using a combination of L2 regularization and 5-fold cross-validation., Results: Model performance was strongest for the fracture, hemorrhage, herniation, mass effect, pneumocephalus, postoperative status, and volume loss models in which the area under the receiver operating characteristic curve exceeded 0.95. Performance was relatively weaker for the edema, hydrocephalus, infarct, tumor, and white-matter disease models (area under the receiver operating characteristic curve > 0.85). Analysis of coefficients revealed finding-specific words among the top coefficients in each model. Class output probabilities were found to be a useful indicator of predictive error on individual report examples in higher-performing models., Conclusions: Combining logistic regression with n-gram encoding is a robust approach to labeling common findings in noncontrast head CT reports., (© 2022 by American Journal of Neuroradiology.)

Background: Intracerebral hemorrhage (ICH) is the deadliest form of stroke. In observational studies, lower serum magnesium has been linked to more hematoma expansion (HE) and intracranial hemorrhage, implying that supplemental magnesium sulfate is a potential acute treatment for patients with ICH and could reduce HE. FAST-MAG (Field Administration of Stroke Therapy - Magnesium) was a clinical trial of magnesium sulfate started prehospital in patients with acute stroke within 2 hours of last known well enrolled. CT was not required prior to enrollment, and several hundred patients with acute ICH were enrolled. In this ancillary analysis, we assessed the effect of magnesium sulfate treatment upon HE in patients with acute ICH., Methods: We retrospectively analyzed data that were prospectively collected in the FAST-MAG study. Patients received intravenous magnesium sulfate or matched placebo within 2 hours of onset. We compared HE among patients allocated to intravenous magnesium sulfate or placebo with a Mann-Whitney U . We used the same method to compare neurological deficit severity (National Institutes of Health Stroke Scale) and global disability (modified Rankin Scale) at 3 months., Results: Among 268 patients with ICH meeting study entry criteria, mean 65.4±13/4 years, 33% were female, and 211 (79%) had a history of hypertension. Initial deficit severities were median (interquartile range) of 4 (3-5) on the Los Angeles Motor Scale in the field and National Institutes of Health Stroke Scale score of 16 (9.5-25.5) early after hospital arrival. Follow-up brain imaging was performed a median of 17.1 (11.3-22.7) hours after first scan. The magnesium and placebo groups did not statistically differ in hematoma volume on arrival, 10.1 (5.6-28.7) versus 12.4 (5.6-28.7) mL ( P =0.6), or HE, 2.0 (0.1-7.4) versus 1.5 (-0.2 to 8) mL ( P =0.5). There was no difference in functional outcomes (modified Rankin Scale score of 3-6), 59% versus 50% ( P =0.5)., Conclusions: Magnesium sulfate did not reduce HE or improve functional outcomes at 90 days. A benefit for patients with initial hypomagnesemia was not addressed., Registration: URL: https://www., Clinicaltrials: gov; Unique identifier: NCT00059332.

Background: Fall prevention is a patient safety and economic priority for health care organizations. An automated model within the electronic medical record (EMR) that accurately predicts risk for falling would be valuable for mitigation of inpatient falls. The aim of this study was to validate the reliability of an EMR-based computerized predictive model (ROF Model) for inpatient falls. The hypothesis was that the ROF Model would be similar to the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in predicting fall events in the inpatient setting at a large academic medical center., Methods: This observational study compared the falls predicted by each model against actual falls over an eight-month period in a single institution. Descriptive statistics were used to compare the distribution of scores and accuracy of fall risk categorization for each model immediately preceding a fall., Results: For 35,709 inpatient encounters, the total fall rate was 0.92%. Of the 329 patients who fell, 60.8% were high risk by ROF Model (fall rate 1.82%), and 75.4% were high risk by JHFRAT (fall rate 1.39%). The ROF Model had a better specificity than the JHFRAT (69.7% vs. 49.2%) but a similar C-statistic (0.717 vs. 0.702) and a lower sensitivity (60.8% vs. 79.3%)., Conclusion: The performance of the ROF Model was similar to that of the JHFRAT in predicting inpatient falls. This comparison provides evidence to support a transition to a more automated process. Future studies will determine prospectively if implementation of the ROF Model will reduce falls in the inpatient setting., (Copyright © 2021. Published by Elsevier Inc.)

Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine whether these circuits converge, we studied depression severity after brain lesions (n = 461, five datasets), transcranial magnetic stimulation (n = 151, four datasets) and deep brain stimulation (n = 101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets (P < 0.001). Circuits derived from lesions, deep brain stimulation and transcranial magnetic stimulation were similar (P < 0.0005), as were circuits derived from patients with major depression versus other diagnoses (P < 0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of transcranial magnetic stimulation and deep brain stimulation sites (P < 0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson's disease (P < 0.05). We conclude that lesions, transcranial magnetic stimulation and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Intracranial hemorrhage (ICH) is a devastating complication for patients with ventricular assist devices (VADs). The safety of emergent anticoagulation reversal with four-factor prothrombin complex concentrate (PCC) and optimal timing of anticoagulation resumption are not clear. In addition, lactate dehydrogenase (LDH) is used as a biomarker for thromboembolic risk, but its utility in guiding anticoagulation management after reversal with PCC has not be described., Methods: We retrospectively reviewed a consecutive series of patients with VADs presenting with ICH between 2014 and 2020 who received four-factor PCC for rapid anticoagulation reversal. We collected the timing of PCC administration, timing of resumption of anticoagulation, survival, occurrence of thromboembolic events, and LDH levels throughout hospitalization., Results: We identified 16 ICH events in 14 patients with VADs treated with rapid anticoagulation reversal using four-factor PCC (11 intraparenchymal, 4 subdural, 1 subarachnoid hemorrhage). PCC was administered at a mean of 3.3 ± 0.3 h after imaging diagnosis of ICH. Overall mortality was 63%. Survivors had higher presenting Glasgow Coma Scale (median 15, interquartile range [IQR] 15-15 versus 14, IQR 8-14.7, P = 0.041). In all six instances where the patient survived, anticoagulation was resumed on average 9.16 ± 1.62 days after reversal. There were no thromboembolic events prior to resumption of anticoagulation. Three events occurred after anticoagulation resumption and within 3 months of reversal: VAD thrombosis in a patient with thrombosis at the time of reversal, ischemic stroke, and readmission for elevated LDH in the setting of subtherapeutic international normalized ratio., Conclusions: Our limited series found no thromboembolic complications immediately following anticoagulation reversal with PCC prior to resumption of anticoagulation. LDH trends may be useful to monitor thromboembolic risk after reversal., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Patients with aneurysmal subarachnoid hemorrhage (ruptured brain aneurysm) often have reduced health-related quality of life at follow-up in multiple domains (e.g., cognitive function and social function). We tested the hypothesis that there are distinct patterns of patient outcomes across domains of health-related quality of life, "complex patient outcomes," in survivors of subarachnoid hemorrhage., Design: Patients with subarachnoid hemorrhage were prospectively identified. Clinical data were prospectively recorded. Health-related quality of life was prospectively assessed at 3-month follow-up using the National Institutes of Health Patient Reported Outcomes Measurement Information System and neuro-quality of life in the domains of mobility, cognitive function, satisfaction with social roles, and depression. We used k-means clustering to analyze prospectively recorded health-related quality of life data, identifying clusters of complex patient outcomes. Decision tree analysis identified index hospital stay factors predictive of a patient having a particular complex patient outcome at follow-up., Setting: Academic medical center., Patients: One hundred three survivors of subarachnoid hemorrhage., Interventions: None., Measurements and Main Results: We analyzed 103 patients, of whom 75 (72.8%) were female, and mean age was 53.6 ± 13.4 years. There were three complex patient outcomes: health-related quality of life greater than 1 sd better than the U.S. mean across all domains ( n = 23, 22.3%), health-related quality of life greater than 1 sd worse than U.S. mean across all domains ( n = 26, 25.2%), and satisfaction with social roles greater than 0.5 sd worse than U.S. mean with cognitive function, depression, and mobility scores near the U.S. mean ( n = 54, 52.4%). In decision tree analysis, hospital disposition and Hunt and Hess Grade were associated with complex patient outcome., Conclusions: Complex patient outcomes across multiple domains of health-related quality of life at follow-up after subarachnoid hemorrhage are distinct and may be predictable., Competing Interests: Ms. Murphy reports funding from T32 LM012203, Ms. Wang reports funding from UL1 TR001422, Dr. Luo reports funding from R01 LM013337 and GM105688, and Dr. Naidech reports funding from National Institutes of Health R01 NS110779 and U01 NS110772. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)

Background and Purpose: This study aims to determine whether machine learning (ML) and natural language processing (NLP) from electronic health records (EHR) improve the prediction of 30-day readmission after stroke. Methods: Among index stroke admissions between 2011 and 2016 at an academic medical center, we abstracted discrete data from the EHR on demographics, risk factors, medications, hospital complications, and discharge destination and unstructured textual data from clinician notes. Readmission was defined as any unplanned hospital admission within 30 days of discharge. We developed models to predict two separate outcomes, as follows: (1) 30-day all-cause readmission and (2) 30-day stroke readmission. We compared the performance of logistic regression with advanced ML algorithms. We used several NLP methods to generate additional features from unstructured textual reports. We evaluated the performance of prediction models using a five-fold validation and tested the best model in a held-out test dataset. Areas under the curve (AUCs) were used to compare discrimination of each model. Results: In a held-out test dataset, advanced ML methods along with NLP features out performed logistic regression for all-cause readmission (AUC, 0.64 vs. 0.58; p < 0.001) and stroke readmission prediction (AUC, 0.62 vs. 0.52; p < 0.001). Conclusion: NLP-enhanced machine learning models potentially advance our ability to predict readmission after stroke. However, further improvement is necessary before being implemented in clinical practice given the weak discrimination., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lineback, Garg, Oh, Naidech, Holl and Prabhakaran.)

Objectives: Early seizures are a common complication of intracerebral hemorrhage, occurring in ~10% of patients. However, the independent effect of early seizures on patient outcomes, particularly health-related quality of life, is unclear. Without a potential benefit to patient outcomes, the widespread use (~40%) of prophylactic seizure medications has no reasonable chance of improving patient outcomes. We tested the hypothesis that health-related quality of life at follow-up is different between patients with and without early seizures (and secondarily, with nonconvulsive status epilepticus) after intracerebral hemorrhage., Design: Patients with intracerebral hemorrhage were enrolled in an observational cohort study that prospectively collected clinical data and health-related quality of life at follow-up., Setting: Academic medical center., Patients: One-hundred thirty-three patients whose health-related quality of life was assessed 3 months after intracerebral hemorrhage onset., Measurements and Main Results: Health-related quality of life was obtained at 3 months after intracerebral hemorrhage onset. T Scores of health-related quality of life were modeled with multivariable linear models accounting for severity with the intracerebral hemorrhage Score and hematoma location. Health-related quality of life was measured with National Institutes of Health Patient Reported Outcomes Measurement Information System/Neuroquality of life, expressed in T Scores (U.S. normal 50 ± 10). The modified Rankin Scale (a global measure) was a secondary outcome. There were 12 patients (9%) with early seizures. T Scores of health-related quality of life at follow-up were lower (worse) in patients with early seizure compared with patients without an early seizure (44 [32.75-51.85] vs 30.25 [18.9-39.15]; p = 0.04); results for other domains of health-related quality of life were similar. The association persisted in multivariable models. There was no association between early seizures and prophylactic seizure medications (p = 0.4). Results for patients with nonconvulsive status epilepticus were similar. There was no association between early seizures and the modified Rankin Scale at 3 months., Conclusions: Early seizures and nonconvulsive status epilepticus were associated with lower health-related quality of life at follow-up in survivors of intracerebral hemorrhage., (Copyright © 2021 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Penetrating brain injury (PBI) is the most devastating type of traumatic brain injury. Development of coagulopathy in the acute setting of PBI, though common, remains of unclear significance as does its reversal. The aim of this study is to investigate the relationship between coagulopathy and clinical presentation, radiographical features, and outcome in civilian patients with PBI. Eighty-nine adult patients with PBI at a Level I trauma center in Chicago, Illinois who survived acute resuscitation and with available coagulation profile were analyzed. Coagulopathy was defined as international normalized ratio [INR] >1.3, platelet count <100,000 /μL, or partial thromboplastin time >37 sec. Median age (interquartile range; IQR) of our cohort was 27 (21-35) years, and 74 (83%) were male. The intent was assault in 74 cases (83%). The mechanism of PBI was gunshot wound in all patients. Forty patients (45%) were coagulopathic at presentation. In a multiple regression model, coagulopathy was associated with lower Glasgow Coma Scale (GCS)-Motor score (odds ratio [OR], 0.67; confidence interval [CI], 0.48-0.94; p  = 0.02) and transfusion of blood products (OR, 3.91; CI, 1.2-12.5; p  = 0.02). Effacement of basal cisterns was the only significant radiographical features associated with coagulopathy (OR, 3.34; CI, 1.08-10.37; p  = 0.04). Mortality was found to be significantly more common in coagulopathic patients (73% vs. 25%; p  < 0.001). However, in our limited sample, reversal of coagulopathy at 24 h was not associated with a statistically significant improvement in outcome. The triad of coagulopathy, low post-resuscitation GCS, and radiographical effacement of basal cisterns identify a particularly ominous phenotype of PBI. The role, and potential reversal of, coagulopathy in this group warrants further investigation.

This invited special report is based on an award presentation at the World Stroke Organization/European Stroke Organization Conference in November of 2020 outlining progress in the acute management of intracerebral hemorrhage (ICH) over the past 35 years. ICH is the second most common and the deadliest type of stroke for which there is no scientifically proven medical or surgical treatment. Prospective studies from the 1990s onward have demonstrated that most growth of spontaneous ICH occurs within the first 2 to 3 hours and that growth of ICH and resulting volumes of ICH and intraventricular hemorrhage are modifiable factors that can improve outcome. Trials focusing on early treatment of elevated blood pressure have suggested a target systolic blood pressure of 140 mm Hg, but none of the trials were positive by their primary end point. Hemostatic agents to decrease bleeding in spontaneous ICH have included desmopressin, tranexamic acid, and rFVIIa (recombinant factor VIIa) without clear benefit, and platelet infusions which were associated with harm. Hemostatic agents delivered within the first several hours have the greatest impact on growth of ICH and potentially on outcome. No large Phase III surgical ICH trial has been positive by primary end point, but pooled analyses suggest that earlier ICH removal is more likely to be beneficial. Recent trials emphasize maximization of clot removal and minimizing brain injury from the surgical approach. The future of ICH therapy must focus on delivery of medical and surgical therapies as soon as possible if we are to improve outcomes.

Background/objective: Demonstrating a benefit of acute treatment to patients with intracerebral hemorrhage (ICH) requires identifying which patients have a potentially modifiable outcome, where treatment could favorably shift a patient's expected outcome. A decision rule for which patients have a modifiable outcome could improve the targeting of treatments. We sought to determine which patients with ICH have a modifiable outcome., Methods: Patients with ICH were prospectively identified at two institutions. Data on hematoma volumes, medication histories, and other variables of interest were collected. ICH outcomes were evaluated using the modified Rankin Scale (mRS), assessed at 14 days and 3 months after ICH, with "good outcome" defined as 0-3 (independence or better) and "poor outcome" defined as 4-6 (dependence or worse). Supervised machine learning models identified the best predictors of good versus poor outcomes at Institution 1. Models were validated using repeated fivefold cross-validation as well as testing on the entirely independent sample at Institution 2. Model fit was assessed with area under the ROC curve (AUC)., Results: Model performance at Institution 1 was strong for both 14-day (AUC of 0.79 [0.77, 0.81] for decision tree, 0.85 [0.84, 0.87] for random forest) and 3 month (AUC of 0.75 [0.73, 0.77] for decision tree, 0.82 [0.80, 0.84] for random forest) outcomes. Independent predictors of functional outcome selected by the algorithms as important included hematoma volume at hospital admission, hematoma expansion, intraventricular hemorrhage, overall ICH Score, and Glasgow Coma Scale. Hematoma expansion was the only potentially modifiable independent predictor of outcome and was compatible with "good" or "poor" outcome in a subset of patients with low hematoma volumes, good Glasgow Coma scale and premorbid modified Rankin Scale scores. Models trained on harmonized data also predicted patient outcomes well at Institution 2 using decision tree (AUC 0.69 [0.63, 0.75]) and random forests (AUC 0.78 [0.72, 0.84])., Conclusions: Patient outcomes are predictable to a high level in patients with ICH, and hematoma expansion is the sole-modifiable predictor of these outcomes across two outcome types and modeling approaches. According to decision tree analyses predicting outcome at 3 months, patients with a high Glasgow Coma Scale score, less than 44.5 mL hematoma volume at admission, and relatively low premorbid modified Rankin Score in particular have a modifiable outcome and appear to be candidates for future interventions to improve outcomes after ICH.

Allergy mention normalization is challenging because of the wide range of possible allergens including medications, foods, plants, animals, and consumer products. This paper describes the process of mapping free-text allergy information from an electronic health record (EHR) system in a university hospital to standard terminologies and migration of those data into an enterprise EHR system. The review, mapping, and migration revealed interesting issues and challenges with the free-text allergy information and the mapping in preparation for implementation in the new EHR system. These findings provide insights that can form the basis of guidelines for future mapping and migration efforts involving free-text allergy data. As part of this process, we generate and make freely available AllergyMap, a mapping between free-text entered allergy medication to standard non-proprietary ontologies. To our knowledge, this is the first such mapping available and could serve as a public resource for allergy mention normalization and system evaluation., (©2020 AMIA - All rights reserved.)

Objective: Learning healthcare systems use routinely collected data to generate new evidence that informs future practice. While implementing an electronic health record (EHR) system can facilitate this goal for individual institutions, meaningfully aggregating data from multiple institutions can be more empowering. Cosmos is a cross-institution, single EHR vendor-facilitated data aggregation tool. This work aims to describe the initiative and illustrate its potential utility through several use cases., Methods: Cosmos is designed to scale rapidly by leveraging preexisting agreements, clinical health information exchange networks, and data standards. Data are stored centrally as a limited dataset, but the customer facing query tool limits results to prevent patient reidentification., Results: In 2 years, Cosmos grew to contain EHR data of more than 60 million patients. We present practical examples illustrating how Cosmos could further efforts in chronic disease surveillance (asthma and obesity), syndromic surveillance (seasonal influenza and the 2019 novel coronavirus), immunization adherence and adverse event reporting (human papilloma virus and measles, mumps, rubella, and varicella vaccination), and health services research (antibiotic usage for upper respiratory infection)., Discussion: A low barrier of entry for Cosmos allows for the rapid accumulation of multi-institutional and mostly de-duplicated EHR data to power research and quality improvement queries characteristic of learning healthcare systems. Limitations are being vendor-specific, an "all or none" contribution model, and the lack of control over queries run on an institution's healthcare data., Conclusion: Cosmos provides a model for within-vendor data standardization and aggregation and a steppingstone for broader intervendor interoperability., Competing Interests: Conflict of Interest C.H., A.F., and S.H. reports other from Epic during the conduct of the study; employed by this company and developed the tool described as part of the role in this corporation. A.M.N. reports grants from NIH, from null, during the conduct of the study; other from Bedside Intelligence, LLC, from null, outside the submitted work.

Background: An association between spontaneous hyperventilation, delayed cerebral ischemia, and poor clinical outcomes has been reported in subarachnoid hemorrhage. We evaluated the relationship between early pCO 2 changes, ischemic lesions and outcomes in patients with intracerebral hemorrhage (ICH)., Methods: Consecutive patients with spontaneous ICH were enrolled in an observational cohort study conducted between 2006 and 2019. Patient characteristics and discharge outcome were prospectively recorded. Arterial blood gas (ABG) measurements and mechanical ventilation settings in the first 72 h of admission were retrospectively collected. MRI images were adjudicated for diffusion-restricted lesions consistent with ischemia and distant from the hematoma. We examined the associations between pCO 2 changes, ischemic lesions, and discharge outcomes by univariate and adjusted analyses., Results: ABG data were available for 220 patients. Hyperventilation occurred in 52 (28%) cases and was not associated with clinical severity. Lower initial pCO 2 was associated with greater risk of in-hospital death (OR 0.94 per mmHg, 95%CI [0.89, 0.996], p = 0.042) after adjustment for ICH Score, pneumonia and mechanical ventilation requirements. MRI data were available for 33 patients. Lower pCO 2 was associated with a higher risk of ischemic lesions, except in patients with low initial systolic blood pressure (p < 0.05 for main and blood pressure interaction effects), after adjustment for other predictors., Conclusions: In ICH patients with spontaneous ventilation, lower pCO 2 was independently associated with greater risk of in-hospital death. In patients with elevated initial blood pressure, who undergo blood pressure reduction per guideline recommendations, lower pCO 2 was associated with increased risk to develop ischemic lesions., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003-2007, N = 1,869; 3 h, 2009-2016, N = 13,086, and 4.5 h, 2009-2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold., (Copyright © 2020 Naidech, Lawlor, Xu, Fonarow, Xian, Smith, Schwamm, Matsouaka, Prabhakaran, Marinescu and Kording.)

Background and Purpose: Hemorrhages are a serious complication of brain surgery, and magnesium has shown hemostatic properties in hemorrhagic stroke and non-neurological surgeries. External ventricular drain (EVD) insertion is an advantageous model of emergency neurosurgical hemorrhage risk because it is common, standardized, and the operator is blinded to the outcome during the procedure. We tested the hypothesis that low magnesium is associated with risk of hemorrhagic complications from EVD insertion., Methods: Patients with spontaneous intracerebral hemorrhage and aneurysmal subarachnoid hemorrhage were enrolled in a prospective, observational study. Demographic and clinical variables were prospectively recorded, including serum magnesium measurements. Catheter tract hemorrhage (CTH) was measured on postoperative head computed tomography within 48 hours of EVD insertion., Results: We observed 50 CTH among 327 EVD procedures (15.3%) distributed similarly among intracerebral hemorrhage (21/116 [18.1%]) and subarachnoid hemorrhage (29/211 [13.7%]). Magnesium was lower in patients with CTH compared with those without (median 1.8 versus 2.0 mg/dL, P <0.0001). Higher magnesium was associated with lower odds of CTH (odds ratio 0.67 per 0.1 mg/dL magnesium [95% CI, 0.56-0.78], P <0.0001) after adjustment for other risk factors, with similar effect in the intracerebral hemorrhage and subarachnoid hemorrhage subgroups. Preprocedural increase in magnesium (odds ratio 0.68 [0.52-0.85]) and dose of preprocedural magnesium sulfate (odds ratio 0.67 [0.40-0.97]) were associated with reduced CTH risk after adjustment for initial magnesium and other risk factors., Conclusions: Lower magnesium at the time of EVD insertion was an independent predictor of hemorrhagic complications. Baseline risk was attenuated by preprocedural increases in magnesium, suggesting a therapeutic opportunity.

Objectives: The circadian system modulates many important physiologic processes, synchronizing tissue-specific functions throughout the body. We sought to characterize acute alterations of circadian rhythms in critically ill patients and to evaluate associations between brain dysfunction, systemic multiple organ dysfunction, environmental stimuli that entrain the circadian rhythm (zeitgebers), rest-activity rhythms, and the central circadian rhythm-controlled melatonin secretion profile., Design: Prospective study observing a cohort for 24-48 hours beginning within the first day of ICU admission., Setting: Multiple specialized ICUs within an academic medical center., Patients: Patients presenting from the community with acute onset of either intracerebral hemorrhage as a representative neurologic critical illness or sepsis as a representative systemic critical illness. Healthy control patients were studied in using modified constant routine in a clinical research unit., Interventions: None., Measurements and Main Results: Light, feeding, activity, medications, and other treatment exposures were evaluated along with validated measures of encephalopathy (Glasgow Coma Scale), multiple organ system function (Sequential Organ Failure Assessment score), and circadian rhythms (profiles of serum melatonin and its urinary metabolite 6-sulphatoxymelatonin). We studied 112 critically ill patients, including 53 with sepsis and 59 with intracerebral hemorrhage. Environmental exposures were abnormal, including light (dim), nutritional intake (reduced or absent and mistimed), and arousal stimuli (increased and mistimed). Melatonin amplitude and acrophase timing were generally preserved in awake patients but dampened and delayed with increasing encephalopathy severity. Melatonin hypersecretion was observed in patients exposed to catecholamine vasopressor infusions, but unaffected by sedatives. Change in vasopressor exposure was the only factor associated with changes in melatonin rhythms between days 1 and 2., Conclusions: Encephalopathy severity and adrenergic agonist medication exposure were the primary factors contributing to abnormal melatonin rhythms. Improvements in encephalopathy and medical stabilization did not rapidly normalize rhythms. Urinary 6-sulphatoxymelatonin is not a reliable measure of the central circadian rhythm in critically ill patients.