Targeting RTN4/NoGo-Receptor reduces levels of ALS protein ataxin-2.

Gene-based therapeutic strategies to lower ataxin-2 levels are emerging for the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and spinocerebellar ataxia type 2 (SCA2). Additional strategies to lower levels of ataxin-2 could be beneficial. Here, we perform a genome-wide arrayed small interfering RNA (siRNA) screen in human cells and identify RTN4R, the gene encoding the RTN4/NoGo-Receptor, as a potent modifier of ataxin-2 levels. RTN4R knockdown, or treatment with a peptide inhibitor, is sufficient to lower ataxin-2 protein levels in mouse and human neurons in vitro, and Rtn4r knockout mice have reduced ataxin-2 levels in vivo. We provide evidence that ataxin-2 shares a role with the RTN4/NoGo-Receptor in limiting axonal regeneration. Reduction of either protein increases axonal regrowth following axotomy. These data define the RTN4/NoGo-Receptor as a novel therapeutic target for ALS and SCA2 and implicate the targeting of ataxin-2 as a potential treatment following nerve injury.

Severe Gastrointestinal Involvement in Pediatric Stevens-Johnson Syndrome: A Case Report and Review of the Literature.

Stevens-Johnson syndrome and toxic epidermal necrolysis form a rare but severe disease spectrum characterized by widespread epidermal detachment. Gastrointestinal manifestations of the disease, however, are rarely described in the pediatric literature and have a high mortality among adults. There are limited data on the treatment of these cases, with conflicting evidence regarding the benefit of steroids, IVIG, or other immunosuppressive agents. We review previous instances of gastrointestinal involvement in children and report the case of a previously healthy 13-year-old who presented with the typical ocular and skin findings of Stevens-Johnson syndrome, subsequently developed severe life-threatening diarrhea, and was found to have severe esophagitis, duodenitis, and colitis on endoscopic evaluation. Treatment was initiated with an immediate, short course of steroids along with early introduction of an enteral diet via nasogastric tube, and resulted in full gastrointestinal recovery. This case highlights successful medical treatment of the first reported pediatric case of SJS/TEN with both upper and lower gastrointestinal tract involvement.

Erratum: Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients.

[This corrects the article DOI: 10.1117/1.NPh.5.4.045005.].

Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients.

Monitoring of cerebral blood flow (CBF) and autoregulation are essential components of neurocritical care, but continuous noninvasive methods for CBF monitoring are lacking. Diffuse correlation spectroscopy (DCS) is a noninvasive diffuse optical modality that measures a CBF index ( CBF i ) in the cortex microvasculature by monitoring the rapid fluctuations of near-infrared light diffusing through moving red blood cells. We tested the feasibility of monitoring CBF i with DCS in at-risk patients in the Neurosciences Intensive Care Unit. DCS data were acquired continuously for up to 20 h in six patients with aneurysmal subarachnoid hemorrhage, as permitted by clinical care. Mean arterial blood pressure was recorded synchronously, allowing us to derive autoregulation curves and to compute an autoregulation index. The autoregulation curves suggest disrupted cerebral autoregulation in most patients, with the severity of disruption and the limits of preserved autoregulation varying between subjects. Our findings suggest the potential of the DCS modality for noninvasive, long-term monitoring of cerebral perfusion, and autoregulation.

Effect of epileptiform abnormality burden on neurologic outcome and antiepileptic drug management after subarachnoid hemorrhage.

OBJECTIVE: To quantify the burden of epileptiform abnormalities (EAs) including seizures, periodic and rhythmic activity, and sporadic discharges in patients with aneurysmal subarachnoid hemorrhage (aSAH), and assess the effect of EA burden and treatment on outcomes. METHODS: Retrospective analysis of 136 high-grade aSAH patients. EAs were defined using the American Clinical Neurophysiology Society nomenclature. Burden was defined as prevalence of <1%, 1-9%, 10-49%, 50-89%, and >90% for each 18-24 hour epoch. Our outcome measure was 3-month Glasgow Outcome Score. RESULTS: 47.8% patients had EAs. After adjusting for clinical covariates EA burden on first day of recording and maximum daily burden were associated with worse outcomes. Patients with higher EA burden were more likely to be treated with anti-epileptic drugs (AEDs) beyond the standard prophylactic protocol. There was no difference in outcomes between patients continued on AEDs beyond standard prophylaxis compared to those who were not. CONCLUSIONS: Higher burden of EAs in aSAH independently predicts worse outcome. Although nearly half of these patients received treatment, our data suggest current AED management practices may not influence outcome. SIGNIFICANCE: EA burden predicts worse outcomes and may serve as a target for prospective interventional controlled studies to directly assess the impact of AEDs, and create evidence-based treatment protocols.

Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy.

OBJECTIVE: Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. METHODS: We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. RESULTS: One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. INTERPRETATION: cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018;83:958-969.

Electronic Health Data Predict Outcomes After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUD: Using electronic health data, we sought to identify clinical and physiological parameters that in combination predict neurologic outcomes after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: We conducted a single-center retrospective cohort study of patients admitted with aSAH between 2011 and 2016. A set of 473 predictor variables was evaluated. Our outcome measure was discharge Glasgow Outcome Scale (GOS). For laboratory and physiological data, we computed the minimum, maximum, median, and variance for the first three admission days. We created a penalized logistic regression model to determine predictors of outcome and a multivariate multilevel prediction model to predict poor (GOS 1-2), intermediate (GOS 3), or good (GOS 4-5) outcomes. RESULTS: One hundred and fifty-three patients met inclusion criteria; most were discharged with a GOS of 3. Multivariate analysis predictors of mortality (AUC 0.9198) included APACHE II score, Glasgow Come Scale (GCS), white blood cell (WBC) count, mean arterial pressure, variance of serum glucose, intracranial pressure (ICP), and serum sodium. Predictors of death/dependence versus independence (GOS 4-5)(AUC 0.9456) were levetiracetam, mechanical ventilation, WBC count, heart rate, ICP variance, GCS, APACHE II, and epileptiform discharges. The multiclass prediction model selected GCS, admission APACHE II, periodic discharges, lacosamide, and rebleeding as significant predictors; model performance exceeded 80% accuracy in predicting poor or good outcome and exceeded 70% accuracy for predicting intermediate outcome. CONCLUSIONS: Variance in early physiologic data can impact patient outcomes and may serve as targets for early goal-directed therapy. Electronically retrievable features such as ICP, glucose levels, and electroencephalography patterns should be considered in disease severity and risk stratification scores.

Clinical Development and Implementation of an Institutional Guideline for Prospective EEG Monitoring and Reporting of Delayed Cerebral Ischemia.

Delayed cerebral ischemia (DCI) is the most common and disabling complication among patients admitted to the hospital for subarachnoid hemorrhage (SAH). Clinical and radiographic methods often fail to detect DCI early enough to avert irreversible injury. We assessed the clinical feasibility of implementing a continuous EEG (cEEG) ischemia monitoring service for early DCI detection as part of an institutional guideline. An institutional neuromonitoring guideline was designed by an interdisciplinary team of neurocritical care, clinical neurophysiology, and neurosurgery physicians and nursing staff and cEEG technologists. The interdisciplinary team focused on (1) selection criteria of high-risk patients, (2) minimization of safety concerns related to prolonged monitoring, (3) technical selection of quantitative and qualitative neurophysiologic parameters based on expert consensus and review of the literature, (4) a structured interpretation and reporting methodology, prompting direct patient evaluation and iterative neurocritical care, and (5) a two-layered quality assurance process including structured clinician interviews assessing events of neurologic worsening and an adjudicated consensus review of neuroimaging and medical records. The resulting guideline's clinical feasibility was then prospectively evaluated. The institutional SAH monitoring guideline used transcranial Doppler ultrasound and cEEG monitoring for vasospasm and ischemia monitoring in patients with either Fisher group 3 or Hunt-Hess grade IV or V SAH. Safety criteria focused on prevention of skin breakdown and agitation. Technical components included monitoring of transcranial Doppler ultrasound velocities and cEEG features, including quantitative alpha:delta ratio and percent alpha variability, qualitative evidence of new focal slowing, late-onset epileptiform activity, or overall worsening of background. Structured cEEG reports were introduced including verbal communication for findings concerning neurologic decline. The guideline was successfully implemented over 27 months, during which neurocritical care physicians referred 71 SAH patients for combined transcranial Doppler ultrasound and cEEG monitoring. The quality assurance process determined a DCI rate of 48% among the monitored population, more than 90% of which occurred during the duration of cEEG monitoring (mean 6.9 days) beginning 2.7 days after symptom onset. An institutional guideline implementing cEEG for SAH ischemia monitoring and reporting is feasible to implement and efficiently identify patients at high baseline risk of DCI during the period of monitoring.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.