Fixed- Versus Variable-Dose Prothrombin Complex Concentrate for the Emergent Reversal of Vitamin K Antagonists: A Systematic Review and Meta-Analysis.

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.

External Validation of a Tool to Identify Low-Risk Patients With Isolated Subdural Hematoma and Preserved Consciousness.

STUDY OBJECTIVE: The SafeSDH Tool was derived to identify patients with isolated (no other type of intracranial hemorrhage) subdural hematoma who are at very low risk of neurologic deterioration, neurosurgical intervention, or death. Patients are low risk by the tool if they have none of the following: use of anticoagulant or nonaspirin antiplatelet agent, Glasgow Coma Score (GCS) <14, more than 1 discrete hematoma, hematoma thickness >5 mm, or midline shift. We attempted to externally validate the SafeSDH Tool. METHODS: We performed a retrospective chart review of patients aged ≥16 with a GCS ≥13 and isolated subdural hematoma who presented to 1 of 6 academic and community hospitals from 2005 to 2018. The primary outcome, a composite of neurologic deterioration (seizure, altered mental status, or symptoms requiring repeat imaging), neurosurgical intervention, discharge on hospice, and death, was abstracted from discharge summaries. Hematoma thickness, number of hematomas, and midline shift were abstracted from head imaging reports. Anticoagulant use, antiplatelet use, and GCS were gathered from the admission record. RESULTS: The validation data set included 753 patients with isolated subdural hematoma. Mortality during the index admission was 2.1%; 26% of patients underwent neurosurgical intervention. For the composite outcome, sensitivity was 99% (95% confidence interval [CI] 97 to 100), and specificity was 31% (95% CI 27 to 35). The tool identified 162 (21.5%) patients as low risk. Negative likelihood ratio was 0.03 (95% CI 0.01 to 0.11). CONCLUSION: The SafeSDH Tool identified patients with isolated subdural hematoma who are at low risk for poor outcomes with high sensitivity. With prospective validation, these low-risk patients could be safe for management in less intensive settings.

Recruitment in Acute Stroke Trials: Challenges and Potential Solutions.

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.

Effect of Magnesium on Deterioration and Symptomatic Hemorrhagic Transformation in Cerebral Ischemia: An Ancillary Analysis of the FAST-MAG Trial.

BACKGROUND: Magnesium (Mg) is a neuroprotectant in preclinical models. Lower serum Mg levels have been associated with symptomatic hemorrhagic transformation (HT) in patients with ischemic stroke. Early treatment of acute ischemic stroke with Mg may reduce rates of symptomatic HT. METHODS: In this post hoc study of the Field Administration of Stroke Therapy Magnesium (FAST-MAG) trial, 1,245 participants with a diagnosis of cerebral ischemia received 20 g of Mg or placebo initiated in the prehospital setting. Posttreatment serum Mg level was measured for 809 participants. Cases of clinical deterioration, defined as worsening by ≥4 points on the National Institute of Health Stroke Scale (NIHSS), were imaged and evaluated for etiology. Symptomatic HT was defined as deterioration with imaging showing new hemorrhage. RESULTS: Clinical deterioration occurred in 187 and symptomatic HT in 46 of 1,245 cases of cerebral ischemia. Rates of deterioration and symptomatic HT were not significantly lower in those who received Mg (15.7% vs. 14.4%, p = 0.591; 2.8% vs. 4.6%, p = 0.281). In cases where serum Mg level was obtained posttreatment, lower serum Mg level (<1.7 mg/dL) was associated with significantly higher rates of deterioration and symptomatic HT (27.5% vs. 15.5%, p = 0.0261; 11.6% vs. 3.65%, p = 0.00819). CONCLUSIONS: Treatment with Mg did not significantly reduce rates of clinical deterioration or symptomatic HT. Future analysis should address whether treatment with Mg could have influenced the subgroup with low serum Mg at baseline.

Fall Risk Prediction Models During the Initial COVID-19 Surge: Could Predictive Analytics Be Used in a Resource-Constrained Environment?

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.

Magnesium Sulfate and Hematoma Expansion: An Ancillary Analysis of the FAST-MAG Randomized Trial.

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.

Predicting Early Seizures After Intracerebral Hemorrhage with Machine Learning.

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.

Antiplatelet Medications and Biomarkers of Hemostasis May Explain the Association of Hematoma Appearance and Subsequent Hematoma Expansion After Intracerebral Hemorrhage.

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.

Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants.

BACKGROUND: Sepsis is one of the most life-threatening circumstances for critically ill patients in the United States, while diagnosis of sepsis is challenging as a standardized criteria for sepsis identification is still under development. Disparities in social determinants of sepsis patients can interfere with the risk prediction performances using machine learning. METHODS: We analyzed a cohort of critical care patients from the Medical Information Mart for Intensive Care (MIMIC)-III database. Disparities in social determinants, including race, sex, marital status, insurance types and languages, among patients identified by six available sepsis criteria were revealed by forest plots with 95% confidence intervals. Sepsis patients were then identified by the Sepsis-3 criteria. Sixteen machine learning classifiers were trained to predict in-hospital mortality for sepsis patients on a training set constructed by random selection. The performance was measured by area under the receiver operating characteristic curve (AUC). The performance of the trained model was tested on the entire randomly conducted test set and each sub-population built based on each of the following social determinants: race, sex, marital status, insurance type, and language. The fluctuations in performances were further examined by permutation tests. RESULTS: We analyzed a total of 11,791 critical care patients from the MIMIC-III database. Within the population identified by each sepsis identification method, significant differences were observed among sub-populations regarding race, marital status, insurance type, and language. On the 5783 sepsis patients identified by the Sepsis-3 criteria statistically significant performance decreases for mortality prediction were observed when applying the trained machine learning model on Asian and Hispanic patients, as well as the Spanish-speaking patients. With pairwise comparison, we detected performance discrepancies in mortality prediction between Asian and White patients, Asians and patients of other races, as well as English-speaking and Spanish-speaking patients. CONCLUSIONS: Disparities in proportions of patients identified by various sepsis criteria were detected among the different social determinant groups. The performances of mortality prediction for sepsis patients can be compromised when applying a universally trained model for each subpopulation. To achieve accurate diagnosis, a versatile diagnostic system for sepsis is needed to overcome the social determinant disparities of patients.

The Story of Intracerebral Hemorrhage: From Recalcitrant to Treatable Disease.

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.

Early Seizures Are Predictive of Worse Health-Related Quality of Life at Follow-Up After Intracerebral Hemorrhage.

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.

Using Tweets to Understand How COVID-19-Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study.

BACKGROUND: The emergence of SARS-CoV-2 (ie, COVID-19) has given rise to a global pandemic affecting 215 countries and over 40 million people as of October 2020. Meanwhile, we are also experiencing an infodemic induced by the overabundance of information, some accurate and some inaccurate, spreading rapidly across social media platforms. Social media has arguably shifted the information acquisition and dissemination of a considerably large population of internet users toward higher interactivities. OBJECTIVE: This study aimed to investigate COVID-19-related health beliefs on one of the mainstream social media platforms, Twitter, as well as potential impacting factors associated with fluctuations in health beliefs on social media. METHODS: We used COVID-19-related posts from the mainstream social media platform Twitter to monitor health beliefs. A total of 92,687,660 tweets corresponding to 8,967,986 unique users from January 6 to June 21, 2020, were retrieved. To quantify health beliefs, we employed the health belief model (HBM) with four core constructs: perceived susceptibility, perceived severity, perceived benefits, and perceived barriers. We utilized natural language processing and machine learning techniques to automate the process of judging the conformity of each tweet with each of the four HBM constructs. A total of 5000 tweets were manually annotated for training the machine learning architectures. RESULTS: The machine learning classifiers yielded areas under the receiver operating characteristic curves over 0.86 for the classification of all four HBM constructs. Our analyses revealed a basic reproduction number R0 of 7.62 for trends in the number of Twitter users posting health belief-related content over the study period. The fluctuations in the number of health belief-related tweets could reflect dynamics in case and death statistics, systematic interventions, and public events. Specifically, we observed that scientific events, such as scientific publications, and nonscientific events, such as politicians' speeches, were comparable in their ability to influence health belief trends on social media through a Kruskal-Wallis test (P=.78 and P=.92 for perceived benefits and perceived barriers, respectively). CONCLUSIONS: As an analogy of the classic epidemiology model where an infection is considered to be spreading in a population with an R0 greater than 1, we found that the number of users tweeting about COVID-19 health beliefs was amplifying in an epidemic manner and could partially intensify the infodemic. It is "unhealthy" that both scientific and nonscientific events constitute no disparity in impacting the health belief trends on Twitter, since nonscientific events, such as politicians' speeches, might not be endorsed by substantial evidence and could sometimes be misleading.

Identifying Modifiable Predictors of Patient Outcomes After Intracerebral Hemorrhage with Machine Learning.

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.

Prothrombin Complex Concentrate for Emergent Reversal of Intracranial Hemorrhage in Patients with Ventricular Assist Devices.

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.

Magnesium and Risk of Bleeding Complications From Ventriculostomy Insertion.

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.

Magnesium and Hemorrhage Volume in Patients With Aneurysmal Subarachnoid Hemorrhage.

OBJECTIVES: We tested the hypothesis that admission serum magnesium levels are associated with extent of hemorrhage in patients with aneurysmal subarachnoid hemorrhage. DESIGN: Single-center prospective observational study. SETTING: Tertiary hospital neurologic ICU. PATIENTS: Patients with aneurysmal subarachnoid hemorrhage. INTERVENTIONS: Clinically indicated CT scans and serum laboratory studies. MEASUREMENTS AND MAIN RESULTS: Demographic, clinical, laboratory, and radiographic data were analyzed. Extent of initial hemorrhage was graded semi-quantitatively on admission CT scans using the modified Fisher scale (grades: 0, no radiographic hemorrhage; 1, thin [< 1 mm in depth] subarachnoid hemorrhage; 2, thin subarachnoid hemorrhage with intraventricular hemorrhage; 3, thick [≥ 1 mm] subarachnoid hemorrhage; 4, thick subarachnoid hemorrhage with intraventricular hemorrhage). We used both ordinal (modified Fisher scale) and dichotomized (thick vs thin subarachnoid hemorrhage) univariate and adjusted logistic regression models to assess associations between serum magnesium and radiographic subarachnoid hemorrhage severity. Data from 354 patients (mean age 55 ± 14 yr, 28.5% male, median admission Glasgow Coma Scale 14 [10-15]) were analyzed. Mean magnesium was lower in patients with thick versus thin subarachnoid hemorrhage (1.92 vs 1.99 mg/dL; p = 0.022). A monotonic trend across categories of modified Fisher scale was found using analysis of variance and Spearman rank correlation (p = 0.015 and p = 0.008, respectively). In adjusted ordinal and binary regression models, lower magnesium levels were associated with higher modified Fisher scale (odds ratio 0.33 per 1 mg/dL increase; 95% CI, 0.14-0.77; p = 0.011) and with thick subarachnoid hemorrhage (odds ratio 0.29 per 1 mg/dL increase; 95% CI, 0.10-0.78; p = 0.015). CONCLUSIONS: These data support the hypothesis that magnesium influences hemorrhage severity in patients with aneurysmal subarachnoid hemorrhage, potentially through a hemostatic mechanism.

Factors Disrupting Melatonin Secretion Rhythms During Critical Illness.

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.

Serum osmolality, cerebrospinal fluid specific gravity and overt hepatic encephalopathy severity in patients with liver failure.

BACKGROUND AND AIMS: Hepatic encephalopathy (HE) is a leading contributor to morbidity in liver disease. While hyperammonaemia plays a key role, the mechanisms of cerebral toxicity are unclear. We hypothesized that serum hyperosmolality contributes to HE during acute (ALF) and acute-on-chronic liver failure (ACLF) through mechanisms that affect the water and solute composition of the cerebral environment. METHODS: We performed a retrospective analysis of serum osmolality, cerebral spinal fluid (CSF) solute density (specific gravity, determined from computed tomography attenuation) and clinical HE severity (Glasgow Coma Score [GCS]) at the time of intensive care admission in a prospectively identified cohort of liver failure patients with overt HE. RESULTS: Seventy-three patients (39 ALF and 34 ACLF) were included, of whom 28 (38%) were comatose. Serum osmolality (303.9 ± 15.4 mOsm/kg) was elevated despite normal serum sodium (136.6 ± 6.3 mEq/L). Increased osmolality was independently associated with more severe encephalopathy (ordinal adjusted OR 0.26 [95% CI 0.22, 0.31] for higher GCS per standard deviation increase in osmolality) and lower CSF-specific gravity (linear adjusted ß = -0.039 [95% CI -0.069, -0.009] Hounsfield unit per 1 mOsm/kg). CONCLUSIONS: In the context of related research, these data suggest that hyperosmolality increases brain exposure to metabolic toxins by blood-brain barrier alteration and may be a unique therapeutic target.

Trade-Offs in Quality-of-Life Assessment Between the Modified Rankin Scale and Neuro-QoL Measures.

INTRODUCTION: We aimed to describe the physical and cognitive health of patients with differing levels of post-stroke disability, as defined by modified Rankin Scale (mRS) scores. We also compared cross-sectional correlations between the mRS and the Quality of Life in Neurological Disorders (Neuro-QoL) T-scores to longitudinal correlations of change estimates from each measure. METHODS: Mean Neuro-QoL T-scores representing mobility, dexterity, executive function, and cognitive concerns were compared among mRS subgroups. Fixed-effects regression models with robust standard errors estimated correlations among mRS and Neuro-QoL domain scores and correlations among longitudinal change estimates. These change estimates were then compared to distribution-based estimates of minimal clinically important differences. RESULTS: Seven hundred forty-five patients with ischemic stroke (79%) or transient ischemic attack (21%) were enrolled in this longitudinal observational study of post-stroke outcomes. Larger differences in cognitive function were observed in the severe mRS groups (ie, 4-5) while larger differences in physical function were observed in the mild-moderate mRS groups (ie, 0-2). Cross-sectional correlations among mRS and Neuro-QoL T-scores were high (r = 0.61-0.83), but correlations among longitudinal change estimates were weak (r = 0.14-0.44). CONCLUSIONS: Findings from this study undermine the validity and utility of the mRS as an outcome measure in longitudinal studies in ischemic stroke patients. Nevertheless, strong correlations indicate that the mRS score, obtained with a single interview, is efficient at capturing important differences in patient-reported quality of life, and is useful for identifying meaningful cross-sectional differences among clinical subgroups.

Differential Effects of Time to Initiation of Therapy on Disability and Quality of Life in Patients With Mild and Moderate to Severe Ischemic Stroke.

OBJECTIVE: To assess the effect of time to acute therapy on health-related quality of life (HRQoL) and disability after ischemic stroke. DESIGN: Prospective cohort study. SETTING: Comprehensive stroke care center in a large metropolitan city. PARTICIPANTS: Patients (N=553; mean age, 67 y; 51.9% male; 64.4% white; 88.8% ischemic stroke) with ischemic stroke or transient ischemic attack (TIA) enrolled in a longitudinal observational study between August 2012 to January 2014 who received rehabilitation services. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Disability status was assessed with the modified Rankin Scale (mRS) and Barthel Index (BI). HRQoL was assessed using the Quality of Life in Neurological Disorders measures of executive function, general cognitive concerns, upper extremity dexterity, and lower extremity mobility. Time to therapy consult and treatment were defined as the number of days from hospital admission to initial consult by a therapist and number of days from hospital admission to initial treatment, respectively. RESULTS: Among the participants, the median number of days from hospital admission to acute therapy consult was 2 days (interquartile range, 1-3d). Multivariable linear and logistic regression models indicated that for those with the National Institutes of Health Stroke Scale (NIHSS) score<5, longer time to therapy consult was associated with worse BI scores (BI=100; odds ratio [OR], 0.818; P=.008), executive function T scores (b=-0.865; P=.001), and general cognitive concerns T scores (b=-0.609; P=.009) at 1-month in adjusted analyses. In those with NIHSS score≥5, longer time to therapy treatment led to increased disability (ie, mRS≥ 2; OR, 1.15; P=.039) and lower extremity mobility T scores (b=-0.591; P=.046) at 1 month in adjusted analyses. CONCLUSIONS: Longer time to initiation of acute therapy has differential effects on poststroke disability and HRQoL up to 1-month after ischemic stroke and TIA. The effect of acute therapy consult is more notable for those with mild deficits, while the effect of acute therapy treatment is more notable for those with moderate to severe deficits. Minimizing time to therapy consults and treatments in the acute hospital period might improve outcomes after ischemic stroke and TIA.