Individuals with chronic epilepsy have elevated P-wave heterogeneity comparable to patients with atrial fibrillation.

OBJECTIVE: Identification of epilepsy patients with elevated risk for atrial fibrillation (AF) is critical given the heightened morbidity and premature mortality associated with this arrhythmia. Epilepsy is a worldwide health problem affecting nearly 3.4 million people in the United States alone. The potential for increased risk for AF in patients with epilepsy is not well appreciated, despite recent evidence from a national survey of 1.4 million hospitalizations indicating that AF is the most common arrhythmia in people with epilepsy. METHODS: We analyzed inter-lead heterogeneity of P-wave morphology, a marker reflecting arrhythmogenic nonuniformities of activation/conduction in atrial tissue. The study groups consisted of 96 patients with epilepsy and 44 consecutive patients with AF in sinus rhythm before clinically indicated ablation. Individuals without cardiovascular or neurological conditions (n = 77) were also assessed. We calculated P-wave heterogeneity (PWH) by second central moment analysis of simultaneous beats from leads II, III, and aVR ("atrial dedicated leads") from standard 12-lead electrocardiography (ECG) recordings from admission day to the epilepsy monitoring unit (EMU). RESULTS: Female patients composed 62.5%, 59.6%, and 57.1% of the epilepsy, AF, and control subjects, respectively. The AF cohort was older (66 ± 1.1 years) than the epilepsy group (44 ± 1.8 years, p < .001). The level of PWH was greater in the epilepsy group than in the control group (67 ± 2.6 vs. 57 ± 2.5 µV, p = .046) and reached levels observed in AF patients (67 ± 2.6 vs. 68 ± 4.9 µV, p = .99). In multiple linear regression analysis, PWH levels in individuals with epilepsy were mainly correlated with the PR interval and could be related to sympathetic tone. Epilepsy remained associated with PWH after adjustments for cardiac risk factors, age, and sex. SIGNIFICANCE: Patients with chronic epilepsy have increased PWH comparable to levels observed in patients with AF, while being ~20 years younger, suggesting an acceleration in structural change and/or cardiac electrical instability. These observations are consistent with emerging evidence of an "epileptic heart" condition.

Automation of Quantifying Axonal Loss in Patients with Peripheral Neuropathies through Deep Learning Derived Muscle Fat Fraction.

BACKGROUND: Axonal loss denervates muscle, leading to an increase of fat accumulation in the muscle. Therefore, fat fraction (FF) in whole limb muscle using MRI has emerged as a monitoring biomarker for axonal loss in patients with peripheral neuropathies. In this study, we are testing whether deep learning-based model can automate quantification of the FF in individual muscles. While individual muscle is smaller with irregular shape, manually segmented muscle MRI images have been accumulated in this lab; and make the deep learning feasible. PURPOSE: To automate segmentation on muscle MRI images through deep learning for quantifying individual muscle FF in patients with peripheral neuropathies. STUDY TYPE: Retrospective. SUBJECTS: 24 patients and 19 healthy controls. FIELD STRENGTH/SEQUENCES: 3T; Interleaved 3D GRE. ASSESSMENT: A 3D U-Net model was implemented in segmenting muscle MRI images. This was enabled by leveraging a large set of manually segmented muscle MRI images. B1+ and B1- maps were used to correct image inhomogeneity. Accuracy of the automation was evaluated using Pixel Accuracy (PA), Dice Coefficient (DC) in binary masks; and Bland-Altman and Pearson correlation by comparing FF values between manual and automated methods. STATISTICAL TESTS: PA and DC were reported with their median value and standard deviation. Two methods were compared using the ± 95% confidence intervals (CI) of Bland-Altman analysis and the Pearson's coefficient (r2 ). RESULTS: DC values were from 0.83 ± 0.17 to 0.98 ± 0.02 in thigh and from 0.63 ± 0.18 to 0.96 ± 0.02 in calf muscles. For FF values, the overall ± 95% CI and r2 were [0.49, -0.56] and 0.989 in thigh and [0.84, -0.71] and 0.971 in the calf. DATA CONCLUSION: Automated results well agreed with the manual results in quantifying FF for individual muscles. This method mitigates the formidable time consumption and intense labor in manual segmentations; and enables the use of individual muscle FF as outcome measures in upcoming longitudinal studies. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 1.

Comparing the efficacy and safety of direct oral anticoagulants with vitamin K antagonist in cerebral venous thrombosis.

Cerebral venous thrombosis (CVT) causes significant disability and mortality. Current guidelines for CVT management support the initial use of unfractionated heparin or low molecular weight heparin followed by longer-term oral vitamin K antagonist (VKA). There has been increasing, albeit limited, evidence for the use of direct oral anticoagulants (DOAC) as an alternative to VKA. We performed a systematic review and meta-analysis of studies that compared the safety and efficacy of DOACs to VKA in treating CVT. A comprehensive literature search was carried out in Medline, Embase and Cochrane Stroke Group Trials Register using a suitable keyword/MeSH term search strategy. All studies published in English comparing outcomes of patients with CVT treated with DOAC or VKA were included. In total, 6 studies (5 observational studies and 1 randomized clinical trial) comprising 412 patients (age range 16-83 years) were analyzed. DOAC was used in 151 patients, while 261 received VKA. The follow-up period was 3-11 months. The efficacy of DOACs was comparable with VKA in terms of partial or full thrombus recanalization (RR 1.02, 95% CI 0.89-1.16) and excellent functional recovery with modified Rankin scale < 2 (RR 1.02, 95% CI 0.93-1.13). Patients treated with DOAC developed lower major bleeding events when compared to VKA, although this did not reach statistical significance (RR 0.44, 95% CI 0.12-1.59). We provide preliminary evidence to support DOAC as effective and safe alternatives to VKA in CVT treatment. We await the results of upcoming randomized trials to further support our results and validate the use of DOAC.

Intracranial Artery Calcium Burden Predicts Recurrent Cerebrovascular Events in Transient Ischaemic Attack Patients.

BACKGROUND: Patients with initial transient ischaemic attack (TIA) subsequently have a higher risk of recurrent TIA or acute ischemic stroke (AIS). The role of scoring intracranial arterial calcification (IAC) in predicting the prevalence of stroke remains unclear. We aim to evaluate if radiological CT calcium score measuring IAC burden could predict future ischemic events in a cohort of TIA patients. METHODS: We studied consecutive patients from July 2014 to December 2015 who presented with first episode of TIA. All patients had noncontrasted CT or CT-angiogram of the brain on admission. CT calcium score (cm3) was quantified by measuring calcium deposition in the bilateral internal carotid arteries, middle cerebral arteries, and vertebrobasilar system. Patients were followed up for 2 years and ischemic events for either recurrent TIA or AIS were recorded. We compared patients in terms of clinical profile at presentation and CT calcium score using appropriate univariate and multivariable analyses. RESULTS: Of 156 TIA patients studied, 22% (n = 35) had recurrent TIA or AIS within 2 years of follow-up. On univariate analyses, recurrent TIA/AIS was associated with gender (OR 0.61; 95%CI 0.40-0.95; P = .038), hypertension (mean difference 2.49; 95%CI 1.08-5.75; P = .030) and higher CT calcium score (mean difference 0.84 95%CI 0.16-1.52 P = .016). On multivariable logistic regression, a higher CT calcium score was significantly associated with recurrent TIA/AIS (adjusted OR 1.25 95%CI 1.01-1.55 P = .042). CONCLUSIONS: In TIA patients, higher IAC burden by measurement of a quantitative CT calcium score may be associated with recurrent ischemic events.

Improvement in Door-to-Needle Time in Patients with Acute Ischemic Stroke via a Simple Stroke Activation Protocol.

BACKGROUND: In acute ischemic stroke (AIS), treatment with intravenous tissue-type plasminogen activator (IV-tPA) is time-sensitive. All stroke centers make continual efforts to reduce door-to-needle time (DNT) with varying success. We present the impact of modifications to our stroke activation protocol on DNT. METHODS: We included 404 consecutive patients with AIS receiving IV-tPA between January 2014 and December 2016. First changes in stroke activation protocol were made in March 2015 in the form of prenotification by paramedics, direct transfer from ambulance to computed tomography (CT) scanner, and rapid en route neurological assessment by an emergency physician and neurologist. In March 2016, a second amendment was made where a stroke nurse accompanied the patient to expedite various steps in the treatment pathway, including endovascular treatment in eligible cases. RESULTS: Both protocol amendments resulted in improvement in DNT and door-to-CT time from 84 ± 47 minutes before intervention to 69 ± 33 minutes after protocol amendment 1 to 59 ± 37 minutes after protocol amendment 2. In particular, the second amendment (144 patients) showed significant shortening of DNT compared with the 137 patients before (59 ± 37 minutes versus 69 ± 33 minutes, P = .020), with a higher percentage achieving the target of 60 minutes (68.1% versus 48.2%, P < .001). This finding was attributed to a reduction in both door-to-CT time and CT-to-needle time. This improvement remained consistent over subsequent months. CONCLUSIONS: The application of a simple systems-based, multidisciplinary stroke activation protocol may help in significant reduction in DNT. Encouraging increased patient ownership by stroke nurses appeared to be a promising approach for timely administration of definitive acute therapies.

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.

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.

A randomized controlled educational pilot trial of interictal epileptiform discharge identification for neurology residents.

OBJECTIVE: To assess the effectiveness of an educational program leveraging technology-enhanced learning and retrieval practice to teach trainees how to correctly identify interictal epileptiform discharges (IEDs). METHODS: This was a bi-institutional prospective randomized controlled educational trial involving junior neurology residents. The intervention consisted of three video tutorials focused on the six IFCN criteria for IED identification and rating 500 candidate IEDs with instant feedback either on a web browser (intervention 1) or an iOS app (intervention 2). The control group underwent no educational intervention ("inactive control"). All residents completed a survey and a test at the onset and offset of the study. Performance metrics were calculated for each participant. RESULTS: Twenty-one residents completed the study: control (n = 8); intervention 1 (n = 6); intervention 2 (n = 7). All but two had no prior EEG experience. Intervention 1 residents improved from baseline (mean) in multiple metrics including AUC (.74; .85; p < .05), sensitivity (.53; .75; p < .05), and level of confidence (LOC) in identifying IEDs/committing patients to therapy (1.33; 2.33; p < .05). Intervention 2 residents improved in multiple metrics including AUC (.81; .86; p < .05) and LOC in identifying IEDs (2.00; 3.14; p < .05) and spike-wave discharges (2.00; 3.14; p < .05). Controls had no significant improvements in any measure. SIGNIFICANCE: This program led to significant subjective and objective improvements in IED identification. Rating candidate IEDs with instant feedback on a web browser (intervention 1) generated greater objective improvement in comparison to rating candidate IEDs on an iOS app (intervention 2). This program can complement trainee education concerning IED identification.

Improving Clinician Performance in Classifying EEG Patterns on the Ictal-Interictal Injury Continuum Using Interpretable Machine Learning.

BACKGROUND: In intensive care units (ICUs), critically ill patients are monitored with electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is constrained by clinician availability, and EEG interpretation can be subjective and prone to interobserver variability. Automated deep-learning systems for EEG could reduce human bias and accelerate the diagnostic process. However, existing uninterpretable (black-box) deep-learning models are untrustworthy, difficult to troubleshoot, and lack accountability in real-world applications, leading to a lack of both trust and adoption by clinicians. METHODS: We developed an interpretable deep-learning system that accurately classifies six patterns of potentially harmful EEG activity - seizure, lateralized periodic discharges (LPDs), generalized periodic discharges (GPDs), lateralized rhythmic delta activity (LRDA), generalized rhythmic delta activity (GRDA), and other patterns - while providing faithful case-based explanations of its predictions. The model was trained on 50,697 total 50-second continuous EEG samples collected from 2711 patients in the ICU between July 2006 and March 2020 at Massachusetts General Hospital. EEG samples were labeled as one of the six EEG patterns by 124 domain experts and trained annotators. To evaluate the model, we asked eight medical professionals with relevant backgrounds to classify 100 EEG samples into the six pattern categories - once with and once without artificial intelligence (AI) assistance - and we assessed the assistive power of this interpretable system by comparing the diagnostic accuracy of the two methods. The model's discriminatory performance was evaluated with area under the receiver-operating characteristic curve (AUROC) and area under the precision-recall curve. The model's interpretability was measured with task-specific neighborhood agreement statistics that interrogated the similarities of samples and features. In a separate analysis, the latent space of the neural network was visualized by using dimension reduction techniques to examine whether the ictal-interictal injury continuum hypothesis, which asserts that seizures and seizure-like patterns of brain activity lie along a spectrum, is supported by data. RESULTS: The performance of all users significantly improved when provided with AI assistance. Mean user diagnostic accuracy improved from 47 to 71% (P<0.04). The model achieved AUROCs of 0.87, 0.93, 0.96, 0.92, 0.93, and 0.80 for the classes seizure, LPD, GPD, LRDA, GRDA, and other patterns, respectively. This performance was significantly higher than that of a corresponding uninterpretable black-box model (with P<0.0001). Videos traversing the ictal-interictal injury manifold from dimension reduction (a two-dimensional representation of the original high-dimensional feature space) give insight into the layout of EEG patterns within the network's latent space and illuminate relationships between EEG patterns that were previously hypothesized but had not yet been shown explicitly. These results indicate that the ictal-interictal injury continuum hypothesis is supported by data. CONCLUSIONS: Users showed significant pattern classification accuracy improvement with the assistance of this interpretable deep-learning model. The interpretable design facilitates effective human-AI collaboration; this system may improve diagnosis and patient care in clinical settings. The model may also provide a better understanding of how EEG patterns relate to each other along the ictal-interictal injury continuum. (Funded by the National Science Foundation, National Institutes of Health, and others.).

Polymorphisms of the serotonin transporter gene and post-stroke depression: a meta-analysis.

BACKGROUND: Polymorphisms of the gene encoding the serotonin transporter-specifically, length variation in the serotonin--transporter-linked polymorphic region (5-HTTLPR), a single-nucleotide polymorphism in the 5-HTTLPR (rs25531), and variable number of tandem repeats (VNTR) in the second intron 2 (STin2)--have been implicated in the development of post-stroke depression (PSD). OBJECTIVE: To evaluate the association between polymorphisms of the serotonin transporter gene and PSD in the medical literature. METHODS: Random-effects meta-analyses were conducted on cross-sectional, case-control and cohort studies examining relations between polymorphisms of the gene encoding the serotonin transporter and the risk of developing PSD. RESULTS: Four studies comprising 260 stroke patients with PSD and 381 without were included. Our analyses showed a significant and positive association between the homozygous short variation (S) allele genotype of the 5-HTTLPR (SS) and PSD (random-effects pooled OR 2.05, 95% CI 1.41 to 2.98, z=3.79, p<0.001). Our analyses also showed a significant and negative association between the homozygous long variation (L) allele genotype of the 5-HTTLPR (LL) and PSD (random-effects OR 0.52, 95% CI 0.27 to 0.97, z=-2.07, p=0.039). No statistically significant association of PSD with heterozygous S and L allele genotype for 5-HTTLPR or other polymorphisms with rs25531 and STin2 VNTR was found. Heterogeneity and publication bias were not statistically significant. The major limitation of this meta-analysis is that we could not assess the interaction between stroke, environmental stress and PSD. CONCLUSIONS: The 5-HTTLPR SS genotype may be a risk factor for PSD. The 5-HTTLPR LL genotype showed a significant negative association with PSD. Further research to assess the sensitivity and specificity of predicting the risk of developing PSD by screening for the 5-HTTLPR genotype in stroke patients is required.

Acute symptomatic seizures and status epilepticus in older adults: A narrative review focusing on management and outcomes.

A clear narrative of acute symptomatic seizures (ASyS) in older adults is lacking. Older adults (≥60 years) have the highest incidence of seizures of all age groups and necessitate a tailored approach. ASyS has a bimodal peak in infancy and old age (82.3-123.2/100,000/year after 65 years of age). ASyS can represent half of the new-onset seizures in older adults and can progress to acute symptomatic status epilepticus (ASySE) in 52-72% of the patients. Common etiologies for ASyS in older adults include acute stroke and metabolic disturbances. For ASySE, common etiologies are acute stroke and anoxic brain injury (ABI). Initial testing for ASyS should be consistent with the most common and urgent etiologies. A 20-min electroencephalogram (EEG) is less sensitive in older adults than in younger adults and might not help predict chronic epilepsy. The prolonged postictal phase is an additional challenge for acute management. Studies note that 30% of older adults with ASyS subsequently develop epilepsy. The risk of wrongly equating ASyS as the first seizure of epilepsy is higher in older adults due to the increased long-term challenges with chronic anti-seizure medication (ASM) treatment. Specific challenges to managing ASyS in older adults are related to their chronic comorbidities and polypharmacy. It is unclear if the prognosis of ASyS is dependent on the underlying etiology. Short-term mortality is 1.6 to 3.6 times higher than younger adults. ASySE has high short-term mortality, especially when it is secondary to acute stroke. An acute symptomatic etiology of ASySE had five times increased risk of short-term mortality compared to other types of etiology.

Racial and ethnic trends in antiseizure medications trial enrolment: A systematic review using ClinicalTrials.gov.

OBJECTIVE: To describe the racial and gender distribution in antiseizure medications (ASM) clinical trials using a systemic review of clinical trial registry database. METHODS: We searched ClinicalTrials.gov database for ASM trials registered from September 1988 to January 2019. All randomized and non-randomized trials investigating ASM for epilepsy were included. Trials with intervention other than ASM or condition other than epilepsy were excluded. Data on age, race, ethnicity, and gender were extracted directly from database and from published data where available. Study location, trial identifier, year of completion, and funding sources were also collected. Meta-analysis of proportions was conducted using R software. RESULT: Two hundred and thirty studies conducted globally with 39,576 participants were included. Overall, there are 53 % male on all registered ASM studies globally. For trials conducted in the United States (61 studies/5126 participants), 52 % of the participants were male with the following weighted racial distribution (80 % White 13 % Black 3% Asian 7% Hispanic). Subgroup analysis revealed that non-pharma-sponsored studies (50 studies, 4296 participants) have a higher representation of minorities as compared to pharma-sponsored studies (180 studies, 35,280 participants), including Hispanic (9% vs 3% respectively) and Black (18 % vs 11 % respectively). Temporal trends in racial distribution were noted when the duration of 2007-2019 was split into two groups: 2007-2013 (0% Asian, 5% Hispanic, 20 % Black); 2014-2019 (4% Asian, 7% Hispanic, 8% Black). CONCLUSION: In this systematic review, participation of racial and ethnic minorities of Asian and Hispanic background was under-represented. Disparities of all minorities including Black participants was more notable over time and in studies sponsored by industry. Generalizability of ASM clinical trials to certain subgroups should be further examined.

Predicting Clinical Outcomes in Acute Ischemic Stroke Patients Undergoing Endovascular Thrombectomy with Machine Learning : A Systematic Review and Meta-analysis.

PURPOSE: Conventional predictive models are based on a combination of clinical and neuroimaging parameters using traditional statistical approaches. Emerging studies have shown that the machine learning (ML) prediction models with multiple pretreatment clinical variables have the potential to accurately prognosticate the outcomes in acute ischemic stroke (AIS) patients undergoing thrombectomy, and hence identify patients suitable for thrombectomy. This article summarizes the published studies on ML models in large vessel occlusion AIS patients undergoing thrombectomy. METHODS: We searched electronic databases including PubMed from 1 January 2000 up to 14 October 2019 for studies that evaluated ML algorithms for the prediction of outcomes in stroke patients undergoing thrombectomy. We then used random-effects bivariate meta-analysis models to summarize the studies. RESULTS: We retained a total of five studies that evaluated ML (4 support vector machine, 1 decision tree model) with a combined cohort of 802 patients. The prevalence of good functional outcome defined by 90-day mRS of 0-2 when available. Random effects model demonstrated that the AUC was 0.846 (95% confidence interval, CI 0.686-0.902). A pooled diagnostic odds ratio of 12.6 was computed. The pooled sensitivity and specificity were 0.795 (95% CI 0.651-0.889) and 0.780 (95% CI 0.634-0.879), respectively. CONCLUSION: ML may be useful as an adjunct to clinical assessment to predict functional outcomes in AIS patients undergoing thrombectomy, and hence identify suitable patients for treatment. Further studies validating ML models in large multicenter cohorts are necessary to explore this further.

The Role of Topographic Collaterals in Predicting Functional Outcome after Thrombolysis in Anterior Circulation Ischemic Stroke.

BACKGROUND: The Alberta Stroke Program Early CT (ASPECTS) leptomeningeal collaterals score on CT-angiography helps in prognosticating functional outcome in acute ischemic stroke (AIS) patients treated with intravenous thrombolysis. We evaluated whether a simplified topological ASPECTS collaterals scoring could serve as a rapid biomarker for early prediction in thrombolyzed AIS patients. METHODS: Consecutive patients from 2010 to 2014 with anterior circulation AIS treated with intravenous thrombolysis were included. The primary outcome was good functional outcome (modified Rankin scale score 0-1 at 3-months). Collaterals were scored according to the extent of contrast opacification in arteries distal to the acute occlusion. Prognostic value of individual ASPECTS leptomeningeal collateral regions was determined by multivariate logistic regression. RESULTS: A total of 283 patients were included (mean National Institutes of Health Stroke Scale [NIHSS] score 19.0 ± 6.3 points). Using multivariate logistic regression, good M5 region (parietal)-collaterals (OR 2.62, 95%CI 1.215-5.682, P = .014), younger age (OR .97 per year, 95%CI .943-.990, P = .006), nondiabetics (OR .44, 95%CI .224-.889, P = .021), and lower NIHSS (OR .89 per point, 95%CI .842-.935, P < .001) were independently associated with good functional outcome. The receiver operating characteristic curve showed NIHSS as a good predictor of functional outcome (area under the curve .718, 95%CI .656-.780, P < .001). However, a better predictive value was achieved when M5 collateral score was added to the NIHSS (area under the curve .752, 95%CI .694-.809, P < .001). CONCLUSIONS: Good collaterals in the M5 region are associated with good functional outcome. Addition of this simple neuroimaging tool to the pretreatment NIHSS may serve as a reliable biomarker for prognosis.

Incidence of needlestick injuries among medical students after implementation of preventive training.

INTRODUCTION: Structured training for the prevention of needlestick injuries (NSIs) among medical students was implemented in Singapore in 1998. In this study, we determined the incidence of NSIs and the knowledge and practice of managing and reporting NSIs among first-year clinical students in a medical school in Singapore, as well as the adequacy of the training provided for these students, 14 years after preventive training was instituted. METHODS: All third-year medical students (n = 257) from the Yong Loo Lin School of Medicine, National University of Singapore, Singapore, who had completed their first clinical year posting were enrolled in this cross-sectional study. A self-administered questionnaire was answered by the students one month after completion of their last clinical posting. Students who repeated their first clinical year were excluded from the study. RESULTS: 237 students completed the questionnaire. However, 9 of these students were excluded because they repeated their first clinical year. The response rate was 91.9%. Although 8 (3.5%) students reported one NSI each, only 2 (25.0%) of these 8 students reported the incident to the relevant authority. Among the students surveyed, 65.8% reported using gloves at all times during venepuncture procedures, 48.7% felt that improvements could be made to the current reporting system and procedures, and 53.2% felt that the training provided before commencement of clinical posting could be enhanced. CONCLUSION: There was a decrease in the incidence of NSIs among medical undergraduates in their first clinical year when compared to the incidences reported in earlier studies conducted in the same centre (35.1% in 1993 and 5.3% in 2004). The current reporting system could use a more user-friendly platform, and training on NSIs could be improved to focus more on real-life procedures and incident reporting.