Polymyxin-induced neuromuscular weakness: a case report.

Polymyxin-induced neuromuscular blockade is a rare but potentially fatal condition, with majority of cases that were reported between 1962 and 1973. We describe a patient who developed hypercapnic respiratory failure after initiation of polymyxin for multi-drug resistant Escherichia Coli bacteremia, due to polymyxin-induced neuromuscular dysfunction. After cessation of polymyxin, he regained full strength, had complete resolution of ptosis, and was successfully extubated. In light of the renewed use of polymyxin in this era of antimicrobial-resistance, this case aims to raise awareness about this rare but life-threatening condition, which is easily reversible with early recognition and prompt discontinuation of the drug.

Bridging the Gap: Tailoring an Approach to Treatment in Febrile Infection-Related Epilepsy Syndrome.

Cytokine profiling before immunotherapy is increasingly prevalent in febrile infection-related epilepsy syndrome (FIRES). In this case, an 18-year-old man presented with first-onset seizure after a nonspecific febrile illness. He developed super-refractory status epilepticus requiring multiple antiseizure medications and general anesthetic infusions. He was treated with pulsed methylprednisolone and plasma exchange and started on ketogenic diet. Contrast-enhanced MRI brain revealed postictal changes. EEG findings showed multifocal ictal runs and generalized periodic epileptiform discharges. CSF analysis, autoantibody testing, and malignancy screening were unremarkable. Genetic testing revealed variants of uncertain significance in the CNKSR2 and OPN1LW genes. Initial serum and CSF cytokine analyses performed on days 6 and 21 revealed that interleukin (IL)-6, IL-1RA, monocyte chemoattractant protein-1, macrophage inflammatory protein 1ß, and interferon γ were elevated predominantly in the CNS, a profile consistent with cytokine release syndrome. Tofacitinib was initially trialed on day 30 of admission. There was no clinical improvement, and IL-6 continued to rise. Tocilizumab was given on day 51 with significant clinical and electrographic response. Anakinra was subsequently trialed from days 99 to 103 because clinical ictal activity re-emerged on weaning anesthetics but stopped because of poor response. Serial cytokine profiles showed improvement after 7 doses of tocilizumab. There was corresponding improved seizure control. This case illustrates how personalized immunomonitoring may be helpful in cases of FIRES, where proinflammatory cytokines are postulated to act in epileptogenesis. There is an emerging role for cytokine profiling and close collaboration with immunologists for the treatment of FIRES. The use of tocilizumab may be considered in patients with FIRES with upregulated IL-6.

Combined balloon guide catheter, aspiration catheter, and stent retriever technique versus balloon guide catheter and stent retriever alone technique: a systematic review and meta-analysis.

BACKGROUND: The use of a combination of balloon guide catheter (BGC), aspiration catheter, and stent retriever in acute ischemic stroke thrombectomy has not been shown to be better than a stent retriever and BGC alone, but this may be due to a lack of power in these studies. We therefore performed a meta-analysis on this subject. METHODS: A systematic literature search was performed on PubMed, Scopus, Embase/Ovid, and the Cochrane Library from inception to October 20, 2021. Our primary outcomes were the rate of successful final reperfusion (Treatment in Cerebral Ischemia (TICI) 2c-3) and first pass effect (FPE, defined as TICI 2c-3 in a single pass). Secondary outcomes were 3 month functional independence (modified Rankin Scale score of 0-2), mortality, procedural complications, embolic complications, and symptomatic intracranial hemorrhage (SICH). A meta-analysis was performed using RevMan 5,4, and heterogeneity was assessed using the I2 test. RESULTS: Of 1629 studies identified, five articles with 2091 patients were included. For the primary outcomes, FPE (44.9% vs 45.4%, OR 1.04 (95% CI 0.90 to 1.22), I2=57%) or final successful reperfusion (64.5% vs 68.6%, OR 0.98 (95% CI 0.81% to 1.20%), I2=85%) was similar between the combination technique and stent retriever only groups. However, the combination technique had significantly less rescue treatment (18.8% vs 26.9%; OR 0.70 (95% CI 0.54 to 0.91), I2=0%). This did not translate into significant differences in secondary outcomes in functional outcomes, mortality, emboli, complications, or SICH. CONCLUSION: There was no significant difference in successful reperfusion and FPE between the combined techniques and the stent retriever and BGC alone groups. Neither was there any difference in functional outcomes, complications, or mortality.

Effect of perioperative seizures on mortality and recurrence in patients with brain metastases.

Objective: To identify the independent risk factors for 30-day perioperative seizures, as well as to evaluate the effect of perioperative seizures on overall mortality and tumor recurrence among patients who underwent surgical resection of brain metastases. Methods: Patients who underwent surgical resection of brain metastases at our institution between 2011 and 2019 were included. 30-day perioperative seizures were defined as the presence of any preoperative or postoperative seizures diagnosed by a neurosurgeon or neurologist within 30 days of metastases resection. Independent risk factors for 30-day perioperative seizures were evaluated using multivariate logistic regression models. Kaplan-Meier plots and Cox regression models were constructed to evaluate the effects of 30-day perioperative seizures on overall mortality and tumor recurrence. Subgroup analyses were conducted for 30-day preoperative and 30-day postoperative seizures. Results: A total of 158 patients were included in the analysis. The mean (SD) age was 59.3 (12.0) years, and 20 (12.7%) patients had 30-day perioperative seizures. The presence of 30-day preoperative seizures (OR=41.4; 95% CI=4.76, 924; p=0.002) was an independent risk factor for 30-day postoperative seizures. Multivariate Cox regression revealed that any 30-day perioperative seizure (HR=3.25; 95% CI=1.60, 6.62; p=0.001) was independently and significantly associated with overall mortality but not tumor recurrence (HR=1.95; 95% CI=0.78, 4.91; p=0.154). Conclusions: Among patients with resected brain metastases, the presence of any 30-day perioperative seizure was independently associated with overall mortality. This suggests that 30-day perioperative seizures may be a prognostic marker of poor outcome. Further research evaluating this association as well as the effect of perioperative antiepileptic drugs in patients with resected brain metastases may be warranted.

Improving automated diagnosis of epilepsy from EEGs beyond IEDs.

Objective.Clinical diagnosis of epilepsy relies partially on identifying interictal epileptiform discharges (IEDs) in scalp electroencephalograms (EEGs). This process is expert-biased, tedious, and can delay the diagnosis procedure. Beyond automatically detecting IEDs, there are far fewer studies on automated methods to differentiate epileptic EEGs (potentially without IEDs) from normal EEGs. In addition, the diagnosis of epilepsy based on a single EEG tends to be low. Consequently, there is a strong need for automated systems for EEG interpretation. Traditionally, epilepsy diagnosis relies heavily on IEDs. However, since not all epileptic EEGs exhibit IEDs, it is essential to explore IED-independent EEG measures for epilepsy diagnosis. The main objective is to develop an automated system for detecting epileptic EEGs, both with or without IEDs. In order to detect epileptic EEGs without IEDs, it is crucial to include EEG features in the algorithm that are not directly related to IEDs.Approach.In this study, we explore the background characteristics of interictal EEG for automated and more reliable diagnosis of epilepsy. Specifically, we investigate features based on univariate temporal measures (UTMs), spectral, wavelet, Stockwell, connectivity, and graph metrics of EEGs, besides patient-related information (age and vigilance state). The evaluation is performed on a sizeable cohort of routine scalp EEGs (685 epileptic EEGs and 1229 normal EEGs) from five centers across Singapore, USA, and India.Main results.In comparison with the current literature, we obtained an improved Leave-One-Subject-Out (LOSO) cross-validation (CV) area under the curve (AUC) of 0.871 (Balanced Accuracy (BAC) of 80.9%) with a combination of three features (IED rate, and Daubechies and Morlet wavelets) for the classification of EEGs with IEDs vs. normal EEGs. The IED-independent feature UTM achieved a LOSO CV AUC of 0.809 (BAC of 74.4%). The inclusion of IED-independent features also helps to improve the EEG-level classification of epileptic EEGs with and without IEDs vs. normal EEGs, achieving an AUC of 0.822 (BAC of 77.6%) compared to 0.688 (BAC of 59.6%) for classification only based on the IED rate. Specifically, the addition of IED-independent features improved the BAC by 21% in detecting epileptic EEGs that do not contain IEDs.Significance.These results pave the way towards automated detection of epilepsy. We are one of the first to analyze epileptic EEGs without IEDs, thereby opening up an underexplored option in epilepsy diagnosis.

Sodium-glucose cotransporter 2 inhibitors and neurological disorders: a scoping review.

Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are a group of antidiabetic medications with a favourable cardiovascular, renal and overall safety profile. Given the limited treatment options available for neurological disorders, it is important to determine whether the pleiotropic effects of SGLT2i can be utilised in their prevention and management. Methods: All articles published before 20 March 2021 were systematically searched in MEDLINE, EMBASE, Scopus, Web of Science, APA PsycINFO and ClinicalTrials.gov. Overall, 1395 titles were screened, ultimately resulting in 160 articles being included in the qualitative analysis. Screening and data extraction were conducted by two independent authors and studies were excluded if they were not an original research study. Findings: Of the 160 studies, 134 addressed stroke, 19 cognitive impairment, 4 epilepsy and 4 movement disorders, encompassing a range from systematic reviews and randomised controlled trials to bioinformatic and animal studies. Most animal studies demonstrated significant improvements in behavioural and neurological deficits, which were reflected in beneficial changes in neurovascular units, synaptogenesis, neurotransmitter levels and target receptors' docking energies. The evidence from the minority clinical literature was conflicting and many studies did not reach statistical significance. Interpretation: SGLT2i may exert neurological benefits through three mechanisms: reduction in cardiovascular risk factors, augmentation of ketogenesis and anti-inflammatory pathways. Most clinical studies were observational, meaning that a causal relationship could not be established, while randomised controlled trials were heterogeneous and powered to detect cardiovascular or renal outcomes. We suggest that a longitudinal study should be conducted and specifically powered to detect neurological outcomes.

Vagus nerve stimulation for treatment of drug-resistant epilepsy: a systematic review and meta-analysis.

To analyze the efficacy and safety of high-frequency VNS versus control (low-frequency VNS or no VNS) in patients with DRE using data from randomized controlled trials (RCTs). An electronic literature search was conducted on PubMed, EMBASE, and Cochrane Controlled Register of Trials (CENTRAL); 12 RCTs reporting seizure frequency or treatment response in studies containing a high-frequency VNS treatment arm (conventional VNS or transcutaneous VNS [tVNS]) compared to control (low-frequency VNS or no VNS) were included. Seizure frequency, treatment response (number of patients with ≥ 50% reduction in seizure frequency), quality of life (QOL), and adverse effects were analyzed. Seizure frequency was reported in 9 studies (718 patients). Meta-analysis with random-effects models favored high-frequency VNS over control (standardized mean difference = 0.82, 95%-CI = 0.39-1.24, p < .001). This remained significant for subgroup analyses of low-frequency VNS as the control, VNS modality, and after removing studies with moderate-to-high risk of bias. Treatment response was reported in 8 studies (758 patients). Random-effects models favored high-frequency VNS over control (risk ratio = 1.57, 95%-CI = 1.19-2.07, p < .001). QOL outcomes were reported descriptively in 4 studies (363 patients), and adverse events were reported in 11 studies (875 patients). Major side effects and death were not observed to be more common in high-frequency VNS compared to control. High-frequency VNS results in reduced seizure frequency and improved treatment response compared to control (low-frequency VNS or no VNS) in patients with drug-resistant epilepsy. Greater consideration for VNS in patients with DRE may be warranted to decrease seizure frequency in the management of these patients.

Time-Frequency Decomposition of Scalp Electroencephalograms Improves Deep Learning-Based Epilepsy Diagnosis.

Epilepsy diagnosis based on Interictal Epileptiform Discharges (IEDs) in scalp electroencephalograms (EEGs) is laborious and often subjective. Therefore, it is necessary to build an effective IED detector and an automatic method to classify IED-free versus IED EEGs. In this study, we evaluate features that may provide reliable IED detection and EEG classification. Specifically, we investigate the IED detector based on convolutional neural network (ConvNet) with different input features (temporal, spectral, and wavelet features). We explore different ConvNet architectures and types, including 1D (one-dimensional) ConvNet, 2D (two-dimensional) ConvNet, and noise injection at various layers. We evaluate the EEG classification performance on five independent datasets. The 1D ConvNet with preprocessed full-frequency EEG signal and frequency bands (delta, theta, alpha, beta) with Gaussian additive noise at the output layer achieved the best IED detection results with a false detection rate of 0.23/min at 90% sensitivity. The EEG classification system obtained a mean EEG classification Leave-One-Institution-Out (LOIO) cross-validation (CV) balanced accuracy (BAC) of 78.1% (area under the curve (AUC) of 0.839) and Leave-One-Subject-Out (LOSO) CV BAC of 79.5% (AUC of 0.856). Since the proposed classification system only takes a few seconds to analyze a 30-min routine EEG, it may help in reducing the human effort required for epilepsy diagnosis.

Multi-Center Validation Study of Automated Classification of Pathological Slowing in Adult Scalp Electroencephalograms Via Frequency Features.

Pathological slowing in the electroencephalogram (EEG) is widely investigated for the diagnosis of neurological disorders. Currently, the gold standard for slowing detection is the visual inspection of the EEG by experts, which is time-consuming and subjective. To address those issues, we propose three automated approaches to detect slowing in EEG: Threshold-based Detection System (TDS), Shallow Learning-based Detection System (SLDS), and Deep Learning-based Detection System (DLDS). These systems are evaluated on channel-, segment-, and EEG-level. The three systems perform prediction via detecting slowing at individual channels, and those detections are arranged in histograms for detection of slowing at the segment- and EEG-level. We evaluate the systems through Leave-One-Subject-Out (LOSO) cross-validation (CV) and Leave-One-Institution-Out (LOIO) CV on four datasets from the US, Singapore, and India. The DLDS achieved the best overall results: LOIO CV mean balanced accuracy (BAC) of 71.9%, 75.5%, and 82.0% at channel-, segment- and EEG-level, and LOSO CV mean BAC of 73.6%, 77.2%, and 81.8% at channel-, segment-, and EEG-level. The channel- and segment-level performance is comparable to the intra-rater agreement (IRA) of an expert of 72.4% and 82%. The DLDS can process a 30 min EEG in 4 s and can be deployed to assist clinicians in interpreting EEGs.

Automated Adult Epilepsy Diagnostic Tool Based on Interictal Scalp Electroencephalogram Characteristics: A Six-Center Study.

The diagnosis of epilepsy often relies on a reading of routine scalp electroencephalograms (EEGs). Since seizures are highly unlikely to be detected in a routine scalp EEG, the primary diagnosis depends heavily on the visual evaluation of Interictal Epileptiform Discharges (IEDs). This process is tedious, expert-centered, and delays the treatment plan. Consequently, the development of an automated, fast, and reliable epileptic EEG diagnostic system is essential. In this study, we propose a system to classify EEG as epileptic or normal based on multiple modalities extracted from the interictal EEG. The ensemble system consists of three components: a Convolutional Neural Network (CNN)-based IED detector, a Template Matching (TM)-based IED detector, and a spectral feature-based classifier. We evaluate the system on datasets from six centers from the USA, Singapore, and India. The system yields a mean Leave-One-Institution-Out (LOIO) cross-validation (CV) area under curve (AUC) of 0.826 (balanced accuracy (BAC) of 76.1%) and Leave-One-Subject-Out (LOSO) CV AUC of 0.812 (BAC of 74.8%). The LOIO results are found to be similar to the interrater agreement (IRA) reported in the literature for epileptic EEG classification. Moreover, as the proposed system can process routine EEGs in a few seconds, it may aid the clinicians in diagnosing epilepsy efficiently.

Deep Learning for Interictal Epileptiform Spike Detection from scalp EEG frequency sub bands.

Epilepsy diagnosis through visual examination of interictal epileptiform discharges (IEDs) in scalp electroencephalogram (EEG) signals is a challenging problem. Deep learning methods can be an automated way to perform this task. In this work, we present a new approach based on convolutional neural network (CNN) to detect IEDs from EEGs automatically. The input to CNN is a combination of raw EEG and frequency sub-bands, namely delta, theta, alpha and, beta arranged as a vector for one-dimensional (1D) CNN or matrix for two-dimensional (2D) CNN. The proposed method is evaluated on 554 scalp EEGs. The database consists of 18,164 IEDs marked by two neurologists. Five-fold cross-validation was performed to assess the IED detectors. The resulting 1D CNN based IED detector with multiple sub-bands achieved a false positive rate per minute of 0.23 and a precision of 0.79 at 90% sensitivity. Further, the proposed system is evaluated on datasets from three other clinics, and the features extracted from CNN outputs could significantly discriminate (p-values <; 0.05) the EEGs with and without IEDs. We have proposed an optimized method with better performance than the literature that could aid clinicians to diagnose epilepsy expeditiously, and thereby devise proper treatment.

Automated Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms by Convolutional Neural Networks.

Visual evaluation of electroencephalogram (EEG) for Interictal Epileptiform Discharges (IEDs) as distinctive biomarkers of epilepsy has various limitations, including time-consuming reviews, steep learning curves, interobserver variability, and the need for specialized experts. The development of an automated IED detector is necessary to provide a faster and reliable diagnosis of epilepsy. In this paper, we propose an automated IED detector based on Convolutional Neural Networks (CNNs). We have evaluated the proposed IED detector on a sizable database of 554 scalp EEG recordings (84 epileptic patients and 461 nonepileptic subjects) recorded at Massachusetts General Hospital (MGH), Boston. The proposed CNN IED detector has achieved superior performance in comparison with conventional methods with a mean cross-validation area under the precision-recall curve (AUPRC) of 0.838[Formula: see text]±[Formula: see text]0.040 and false detection rate of 0.2[Formula: see text]±[Formula: see text]0.11 per minute for a sensitivity of 80%. We demonstrated the proposed system to be noninferior to 30 neurologists on a dataset from the Medical University of South Carolina (MUSC). Further, we clinically validated the system at National University Hospital (NUH), Singapore, with an agreement accuracy of 81.41% with a clinical expert. Moreover, the proposed system can be applied to EEG recordings with any arbitrary number of channels.

A Meta-Analysis of the Rates of Suicide Ideation, Attempts and Deaths in People with Epilepsy.

This meta-analysis aimed to evaluate the association between epilepsy and suicide. We systematically searched PubMed, PsycINFO, Embase and Web of Science for studies that reported the prevalence of suicidality in the form of suicide ideation, attempts and deaths among people with epilepsy (PWE). Studies were included if they reported the numbers of patients who died by suicide and concurrently suffered from epilepsy, assessed suicide ideation, or studied suicide attempts in PWE by validated instruments or diagnostic interviews. We used the random effects model to calculate the pooled odds ratios (OR) and standard mean differences (SMDs). We performed subgroup analyses. Seven case-control studies were included in the comparison of rates of suicide attempts between PWE and controls, with a total of 821,594 participants. Our analyses demonstrated a positive association between epilepsy and suicide attempts (pooled OR = 3.25, 95% confidence interval (CI): 2.69-3.92, p < 0.001), indicating that PWE have an elevated risk of suicide. The pooled prevalence for suicide ideation (24 studies) and suicide attempts (18 studies) were 23.2% (95% CI: 0.176-0.301) and 7.4% (95% CI: 0.031-0.169) respectively. The pooled rate of death due to suicide (10 studies) was 0.5% (95% CI: 0.002-0.016). Meta-regression showed that mean age and proportion of male gender were significant moderators for prevalence of suicide attempts and death due to suicide in PWE. Young PWE could be triggered by relationship problems and male PWE might use more lethal methods to attempt suicide. This meta-analysis provides the most up-to-date information on the prevalence of suicide among people with epilepsy and guidance on strategies to improve current psychiatric services provided for this population.

Rationale and design of a randomized trial of early intensive blood pressure lowering on cerebral perfusion parameters in thrombolysed acute ischemic stroke patients.

BACKGROUND AND RATIONALE: Uncertainty persists over the optimal management of blood pressure (BP) in the early phase of acute ischemic stroke (AIS). This study aims to determine the safety and effects of intensive BP lowering on cerebral blood flow (CBF) and functional in AIS patients treated with intravenous thrombolysis. METHODS: In a randomized controlled trial, 54 thrombolysed AIS patients with a systolic BP of 160 to 180 mm Hg will be randomized to early intensive BP lowering (systolic target range 140-160 mm Hg) or guideline-based BP management (systolic range 160-180 mm Hg) during first 72-hours using primarily intravenous labetalol. We hypothesize that early intensive BP lowering will not reduce CBF by 20% and/or increase the volume of hypoperfused tissue by >20% on computed tomographic perfusion. Clinical outcome will be assessed using a dichotomized modified Rankin scale (scores 0-1 as excellent outcome vs scores 2-6 as dead or dependent) at 90 days. Other outcome would be symptomatic intracerebral hemorrhage. The trial is registered at ClinicalTrials.gov, NCT03443596. CONCLUSION: This randomized study will provide important information about the physiological effects of BP reduction on cerebral perfusion after intravenous thrombolysis in AIS.

Validation of Serial Alberta Stroke Program Early CT Score as an Outcome Predictor in Thrombolyzed Stroke Patients.

BACKGROUND: The Alberta Stroke Program Early CT Score (ASPECTS) on baseline imaging is an established predictor of functional outcome in anterior circulation acute ischemic stroke (AIS). We studied ASPECTS before intravenous thrombolysis (IVT) and at 24 hours to assess its prognostic value. METHODS: Data for consecutive anterior circulation AIS patients treated with IVT from 2006 to 2013 were extracted from a prospectively managed registry at our tertiary center. Pre-thrombolysis and 24-hour ASPECTS were evaluated by 2 independent neuroradiologists. Outcome measures included symptomatic intracranial hemorrhage (SICH), modified Rankin Scale (mRS) at 90 days, and mortality. Unfavorable functional outcome was defined by mRS >1. Dramatic ASPECTS progression (DAP) was defined as deterioration in ASPECTS by 6 points or more. RESULTS: Of 554 AIS patients thrombolyzed during the study period, 400 suffered from anterior circulation infarction. The median age was 65 years (interquartile range (IQR): 59-70) and the median National Institutes of Health Stroke Scale score was 18 points (IQR: 12-22). Compared with the pre-IVT ASPECTS (area under the curve [AUC] = .64, 95% confidence interval [CI]: .54-.65, P = .001), ASPECTS on the 24-hour CT scan (AUC = .78, 95% CI: .73-.82, P < .001), and change in ASPECTS (AUC = .69, 95% CI: .64-.74, P < .001) were better predictors of unfavorable functional outcome at 3 months. DAP, noted in 34 (14.4%) patients with good baseline ASPECTS (8-10 points), was significantly associated with unfavorable functional outcome (odds ratio [OR]: 9.91, 95% CI: 3.37-29.19, P ≤ .001), mortality (OR: 21.99, 95% CI: 7.98-60.58, P < .001), and SICH (OR: 8.57, 95% CI: 2.87-25.59, P < .001). CONCLUSION: Compared with the pre-thrombolysis score, ASPECTS measured at 24 hours as well as serial change in ASPECTS is a better predictor of 3-month functional outcome.

Good Intracranial Collaterals Trump Poor ASPECTS (Alberta Stroke Program Early CT Score) for Intravenous Thrombolysis in Anterior Circulation Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: In acute ischemic stroke, large early infarct size estimated by the Alberta Stroke Program Early CT Score (ASPECTS) is associated with poorer outcomes and is a relative contraindication for recanalization therapies. The state of the intracranial collateral circulation influences the functional outcome and may be a variable to consider before thrombolysis. We evaluated the prognostic effect of the collateral circulation in patients with thrombolyzed acute ischemic stroke who have large early infarct sizes as indicated by low ASPECTS. MATERIALS AND METHODS: Patients with anterior circulation acute ischemic stroke who received a computed tomographic angiogram and subsequent treatment with intravenous tissue-type plasminogen activator from 2010 to 2013 were studied. Two independent neuroradiologists determined their ASPECTS. We stratified patients using ASPECTS into 2 groups: large volume infarcts (ASPECTS≤7 points) and small volume infarcts (ASPECTS 8-10). In addition, we evaluated a third group with very large volume infarcts (ASPECTS≤5 points). We then analyzed the 3 subgroups using the Maas, Tan, and ASPECTS-collaterals grading systems of the computed tomographic angiogram intracranial collaterals. Good outcomes were defined by modified Rankin Scale score of 0 to 2 at 3 months. RESULTS: A total of 300 patients were included in the final analysis. For patients with very large volume infarcts (ASPECTS≤5 points), univariable analysis showed that younger age, male sex, lower National Institute of Health Stroke Scale (NIHSS), lower systolic blood pressure, and good collaterals by Maas, Tan, or ASPECTS-collaterals grading were predictors of good outcomes. On multivariate analysis, younger age (odds ratio, 0.93; 95% confidence interval, 0.89-0.97; P=0.002) and good collaterals by ASPECTS-collaterals system (odds ratio, 1.34; 95% confidence interval, 1.15-1.57; P<0.001) were associated with good outcomes. CONCLUSIONS: In patients with large and very large volume infarcts, good collaterals as measured by the ASPECTS-collaterals system is associated with improved outcomes and can help select patients for intravenous thrombolysis.

Intravenous Thrombolysis for Acute Ischemic Stroke due to Cervical Internal Carotid Artery Occlusion.

BACKGROUND: Internal carotid artery (ICA) occlusions are poorly responsive to intravenous thrombolysis with tissue plasminogen activator (IV-tPA) in acute ischemic stroke (AIS). Most study populations have combined intracranial and extracranial ICA occlusions for analysis; few have studied purely cervical ICA occlusions. We evaluated AIS patients with acute cervical ICA occlusion treated with IV-tPA to identify predictors of outcomes. METHODS: We studied 550 consecutive patients with AIS who received IV-tPA and identified 100 with pure acute cervical ICA occlusion. We evaluated the associations of vascular risk factors, National Institutes of Health Stroke Scale (NIHSS) score, and leptomeningeal collateral vessel status via 3 different grading systems, with functional recovery at 90 days, mortality, recanalization of the primary occlusion, and symptomatic intracranial hemorrhage (SICH). Modified Rankin Scale score 0-1 was defined as an excellent outcome. RESULTS: The 100 patients had mean age of 67.8 (range 32-96) and median NIHSS score of 19 (range 4-33). Excellent outcomes were observed in 27% of the patients, SICH in 8%, and mortality in 21%. Up to 54% of the patients achieved recanalization at 24 hours. On ordinal regression, good collaterals showed a significant shift in favorable outcomes by Maas, Tan, or ASPECTS collateral grading systems. On multivariate analysis, good collaterals also showed reduced mortality (OR .721, 95% CI .588-.888, P = .002) and a trend to less SICH (OR .81, 95% CI .65-1.007, P = .058). Interestingly, faster treatment was also associated with favorable functional recovery (OR 1.028 per minute, 95% CI 1.010-1.047, P = .001). CONCLUSIONS: Improved outcomes are seen in patients with early acute cervical ICA occlusion and better collateral circulation. This could be a valuable biomarker for decision making.

How temporal evolution of intracranial collaterals in acute stroke affects clinical outcomes.

OBJECTIVE: We compared intracranial collaterals on pretreatment and day 2 brain CT angiograms (CTA) to assess their evolution and relationship with functional outcomes in acute ischemic stroke (AIS) patients treated with IV tissue plasminogen activator (tPA). METHODS: Consecutive AIS patients who underwent pretreatment and day 2 CTA and received IV tPA during 2010-2013 were included. Collaterals were evaluated by 2 independent neuroradiologists using 3 predefined criteria: the Miteff system, the Maas system, and 20-point collateral scale by the Alberta Stroke Program Early CT Score methodology. We stratified our cohort by baseline pre-tPA state of their collaterals and by recanalization status of the primary vessel for analysis. Good outcomes at 3 months were defined by a modified Rankin Scale score of 0-1. RESULTS: This study included 209 patients. Delayed collateral recruitment by any grading system was not associated with good outcomes. All 3 scoring systems showed that collateral recruitment on the follow-up CTA from a baseline poor collateral state was significantly associated with poor outcome and increased bleeding risk. When the primary vessel remained persistently occluded, collateral recruitment was significantly associated with worse outcomes. Interestingly, collateral recruitment was significantly associated with increased mortality in 2 of the 3 grading systems. CONCLUSIONS: Not all collateral recruitment is beneficial; delayed collateral recruitment may be different from early recruitment and can result in worse outcomes and higher mortality. Prethrombolysis collateral status and recanalization are determinants of how intracranial collateral evolution affects functional outcomes.