Prognostic Implications of Early Prediction in Posttraumatic Epilepsy

Posttraumatic epilepsy (PTE) is a complication of traumatic brain injury that can increase morbidity, but predicting which patients may develop PTE remains a challenge. Much work has been done to identify a variety of risk factors and biomarkers, or a combination thereof, for patients at highest risk of PTE. However, several issues have hampered progress toward fully adapted PTE models. Such issues include the need for models that are well-validated, cost-effective, and account for competing outcomes like death. Additionally, while an accurate PTE prediction model can provide quantitative prognostic information, how such information is communicated to inform shared decision-making and treatment strategies requires consideration of an individual patient's clinical trajectory and unique values, especially given the current absence of direct anti-epileptogenic treatments. Future work exploring approaches integrating individualized communication of prediction model results are needed.

Impact of Therapeutic Interventions on Cerebral Autoregulatory Function Following Severe Traumatic Brain Injury: A Secondary Analysis of the BOOST-II Study

BACKGROUND

The Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II randomized controlled trial used a tier-based management protocol based on brain tissue oxygen (PbtO2) and intracranial pressure (ICP) monitoring to reduce brain tissue hypoxia after severe traumatic brain injury. We performed a secondary analysis to explore the relationship between brain tissue hypoxia, blood pressure (BP), and interventions to improve cerebral perfusion pressure (CPP). We hypothesized that BP management below the lower limit of autoregulation would lead to cerebral hypoperfusion and brain tissue hypoxia that could be improved with hemodynamic augmentation.

METHODS

Of the 119 patients enrolled in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II trial, 55 patients had simultaneous recordings of arterial BP, ICP, and PbtO2. Autoregulatory function was measured by interrogating changes in ICP and PbtO2 in response to fluctuations in CPP using time-correlation analysis. The resulting autoregulatory indices (pressure reactivity index and oxygen reactivity index) were used to identify the "optimal" CPP and limits of autoregulation for each patient. Autoregulatory function and percent time with CPP outside personalized limits of autoregulation were calculated before, during, and after all interventions directed to optimize CPP.

RESULTS

Individualized limits of autoregulation were computed in 55 patients (mean age 38 years, mean monitoring time 92 h). We identified 35 episodes of brain tissue hypoxia (PbtO2 < 20 mm Hg) treated with CPP augmentation. Following each intervention, mean CPP increased from 73 ± 14 mm Hg to 79 ± 17 mm Hg (p = 0.15), and mean PbtO2 improved from 18.4 ± 5.6 mm Hg to 21.9 ± 5.6 mm Hg (p = 0.01), whereas autoregulatory function trended toward improvement (oxygen reactivity index 0.42 vs. 0.37, p = 0.14; pressure reactivity index 0.25 vs. 0.21, p = 0.2). Although optimal CPP and limits remained relatively unchanged, there was a significant decrease in the percent time with CPP below the lower limit of autoregulation in the 60 min after compared with before an intervention (11% vs. 23%, p = 0.05).

CONCLUSIONS

Our analysis suggests that brain tissue hypoxia is associated with cerebral hypoperfusion characterized by increased time with CPP below the lower limit of autoregulation. Interventions to increase CPP appear to improve autoregulation. Further studies are needed to validate the importance of autoregulation as a modifiable variable with the potential to improve outcomes.

Polygenic Risk of Epilepsy and Post-Stroke Epilepsy

Background and Aims

Epilepsy is highly heritable, with numerous known genetic risk loci. However, the genetic predisposition's role in post-acute brain injury epilepsy remains understudied. This study assesses whether a higher genetic predisposition to epilepsy raises post-stroke or Transient Ischemic Attack (TIA) survivor's risk of Post-Stroke Epilepsy (PSE).

Methods

We conducted a three-stage genetic analysis. First, we identified independent epilepsy-associated ( p <5x10 -8 ) genetic variants from public data. Second, we estimated PSE-specific variant weights in stroke/TIA survivors from the UK Biobank. Third, we tested for an association between a polygenic risk score (PRS) and PSE risk in stroke/TIA survivors from the All of Us Research Program. Primary analysis included all ancestries, while a secondary analysis was restricted to European ancestry only. A sensitivity analysis excluded TIA survivors. Association testing was conducted via multivariable logistic regression, adjusting for age, sex, and genetic ancestry.

Results

Among 19,708 UK Biobank participants with stroke/TIA, 805 (4.1%) developed PSE. Likewise, among 12,251 All of Us participants with stroke/TIA, 394 (3.2%) developed PSE. After establishing PSE-specific weights for 39 epilepsy-linked genetic variants in the UK Biobank, the resultant PRS was associated with elevated odds of PSE development in All of Us (OR:1.16[1.02-1.32]). A similar result was obtained when restricting to participants of European ancestry (OR:1.23[1.02-1.49]) and when excluding participants with a TIA history (OR:1.18[1.02-1.38]).

Conclusions

Our findings suggest that akin to other forms of epilepsy, genetic predisposition plays an essential role in PSE. Because the PSE data were sparse, our results should be interpreted cautiously.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

BACKGROUND AND OBJECTIVES

The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC.

METHODS

This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability.

RESULTS

Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds.

DISCUSSION

Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation

BACKGROUND AND OBJECTIVES

Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns.

METHODS

We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes.

RESULTS

SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively.

DISCUSSION

SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

Emergent external ventricular drain placement in patients with factor Xa inhibitor-associated intracerebral hemorrhage after reversal with andexanet alfa

BACKGROUND

Andexanet alfa (AA), a factor Xa-inhibitor (FXi) reversal agent, is given as a bolus followed by a 2-hour infusion. This long administration time can delay EVD placement in intracerebral hemorrhage (ICH) patients. We sought to evaluate the safety of EVD placement immediately post-AA bolus compared to post-AA infusion.

METHODS

We conducted a retrospective study that included adult patients admitted with FXi-associated ICH who received AA and underwent EVD placement The primary outcome was the occurrence of a new hemorrhage (tract, extra-axial, or intraventricular hemorrhage). Secondary outcomes included mortality, intensive care unit and hospital length of stay, and discharge modified Rankin Score. The primary safety outcome was documented thrombotic events.

RESULTS

Twelve patients with FXi related ICH were included (EVD placement post-AA bolus, N = 8; EVD placement post-AA infusion, N = 4). Each arm included one patient with bilateral EVD placed. There was no difference in the incidence of new hemorrhages, with one post-AA bolus patient had small, focal, nonoperative extra-axial hemorrhage. Morbidity and mortality were higher in post-AA infusion patients (mRS, post-AA bolus, 4 [4-6] vs. post-AA infusion 6 [5,6], p = 0.24 and post-AA bolus, 3 (37.5 %) vs. post-AA infusion, 3 (75 %), p = 0.54, respectively). One patient in the post-AA bolus group had thrombotic event. There was no difference in hospital LOS (post-AA bolus, 19 days [12-26] vs. post-AA infusion, 14 days [9-22], p = 0.55) and ICU LOS (post-AA bolus, 10 days [6-13] vs. post-AA infusion, 11 days [5-21], p = 0.86).

CONCLUSION

We report no differences in the incidence of tract hemorrhage, extra-axial hemorrhage, or intraventricular hemorrhage post-AA bolus versus post-AA infusion. Larger prospective studies to validate these results are warranted.

Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy

BACKGROUND

Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1).

METHODS

We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE1 patients were matched with 63 non-PTE1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1 using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.

RESULTS

In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1 risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).

CONCLUSIONS

Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Automated EEG-based prediction of delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

Delayed cerebral ischemia (DCI) is a leading complication of aneurysmal subarachnoid hemorrhage (SAH) and electroencephalography (EEG) is increasingly used to evaluate DCI risk. Our goal is to develop an automated DCI prediction algorithm integrating multiple EEG features over time.

METHODS

We assess 113 moderate to severe grade SAH patients to develop a machine learning model that predicts DCI risk using multiple EEG features.

RESULTS

Multiple EEG features discriminate between DCI and non-DCI patients when aligned either to SAH time or to DCI onset. DCI and non-DCI patients have significant differences in alpha-delta ratio (0.08 vs 0.05, p < 0.05) and percent alpha variability (0.06 vs 0.04, p < 0.05), Shannon entropy (p < 0.05) and epileptiform discharge burden (205 vs 91 discharges per hour, p < 0.05) based on whole brain and vascular territory averaging. Our model improves predictions by emphasizing the most informative features at a given time with an area under the receiver-operator curve of 0.73, by day 5 after SAH and good calibration between 48-72 hours (calibration error 0.13).

CONCLUSIONS

Our proposed model obtains good performance in DCI prediction.

SIGNIFICANCE

We leverage machine learning to enable rapid, automated, multi-featured EEG assessment and has the potential to increase the utility of EEG for DCI prediction.

High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH).

METHODS

Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptiform discharges (ED), measured as number of ED per hour.

RESULTS

We find that many SAH patients have an increase in ED burden during the first 3-10 days following rupture, the major risk period for DCI. However, those who develop DCI have a significantly higher hourly burden from days 3.5-6 after SAH vs. those who do not. ED burden is higher in DCI patients when assessed in relation to the onset of DCI (area under the receiver operator curve 0.72). Finally, specific trends of ED burden over time, assessed by group-based trajectory analysis, also help stratify DCI risk.

CONCLUSIONS

These results suggest that ED burden is a useful parameter for identifying those at higher risk of developing DCI after SAH. The higher burden rate associated with DCI supports the theory of metabolic supply-demand mismatch which contributes to this complication.

SIGNIFICANCE

ED burden is a novel biomarker for predicting those at high risk of DCI.

The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume

BACKGROUND

Among prognostic imaging variables, the hematoma volume on admission computed tomography (CT) has long been considered the strongest predictor of outcome and mortality in intracerebral hemorrhage.

AIMS

To examine whether different features of hematoma shape are associated with functional outcome in deep intracerebral hemorrhage.

METHODS

We analyzed 790 patients from the ATACH-2 trial, and 14 shape features were quantified. We calculated Spearman's Rho to assess the correlation between shape features and three-month modified Rankin scale (mRS) score, and the area under the receiver operating characteristic curve (AUC) to quantify the association between shape features and poor outcome defined as mRS>2 as well as mRS > 3.

RESULTS

Among 14 shape features, the maximum intracerebral hemorrhage diameter in the coronal plane was the strongest predictor of functional outcome, with a maximum coronal diameter >∼3.5 cm indicating higher three-month mRS scores. The maximum coronal diameter versus hematoma volume yielded a Rho of 0.40 versus 0.35 (p = 0.006), an AUC_[mRS>2] of 0.71 versus 0.68 (p = 0.004), and an AUC_[mRS>3] of 0.71 versus 0.69 (p = 0.029). In multiple regression analysis adjusted for known outcome predictors, the maximum coronal diameter was independently associated with three-month mRS (p < 0.001).

CONCLUSIONS

A coronal-plane maximum diameter measurement offers greater prognostic value in deep intracerebral hemorrhage than hematoma volume. This simple shape metric may expedite assessment of admission head CTs, offer a potential biomarker for hematoma size eligibility criteria in clinical trials, and may substitute volume in prognostic intracerebral hemorrhage scoring systems.

Development and Validation of a Model to Identify Critical Brain Injuries Using Natural Language Processing of Text Computed Tomography Reports

IMPORTANCE

Clinical text reports from head computed tomography (CT) represent rich, incompletely utilized information regarding acute brain injuries and neurologic outcomes. CT reports are unstructured; thus, extracting information at scale requires automated natural language processing (NLP). However, designing new NLP algorithms for each individual injury category is an unwieldy proposition. An NLP tool that summarizes all injuries in head CT reports would facilitate exploration of large data sets for clinical significance of neuroradiological findings.

OBJECTIVE

To automatically extract acute brain pathological data and their features from head CT reports.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study developed a 2-part named entity recognition (NER) NLP model to extract and summarize data on acute brain injuries from head CT reports. The model, termed BrainNERD, extracts and summarizes detailed brain injury information for research applications. Model development included building and comparing 2 NER models using a custom dictionary of terms, including lesion type, location, size, and age, then designing a rule-based decoder using NER outputs to evaluate for the presence or absence of injury subtypes. BrainNERD was evaluated against independent test data sets of manually classified reports, including 2 external validation sets. The model was trained on head CT reports from 1152 patients generated by neuroradiologists at the Yale Acute Brain Injury Biorepository. External validation was conducted using reports from 2 outside institutions. Analyses were conducted from May 2020 to December 2021.

MAIN OUTCOMES AND MEASURES

Performance of the BrainNERD model was evaluated using precision, recall, and F1 scores based on manually labeled independent test data sets.

RESULTS

A total of 1152 patients (mean [SD] age, 67.6 [16.1] years; 586 [52%] men), were included in the training set. NER training using transformer architecture and bidirectional encoder representations from transformers was significantly faster than spaCy. For all metrics, the 10-fold cross-validation performance was 93% to 99%. The final test performance metrics for the NER test data set were 98.82% (95% CI, 98.37%-98.93%) for precision, 98.81% (95% CI, 98.46%-99.06%) for recall, and 98.81% (95% CI, 98.40%-98.94%) for the F score. The expert review comparison metrics were 99.06% (95% CI, 97.89%-99.13%) for precision, 98.10% (95% CI, 97.93%-98.77%) for recall, and 98.57% (95% CI, 97.78%-99.10%) for the F score. The decoder test set metrics were 96.06% (95% CI, 95.01%-97.16%) for precision, 96.42% (95% CI, 94.50%-97.87%) for recall, and 96.18% (95% CI, 95.151%-97.16%) for the F score. Performance in external institution report validation including 1053 head CR reports was greater than 96%.

CONCLUSIONS AND RELEVANCE

These findings suggest that the BrainNERD model accurately extracted acute brain injury terms and their properties from head CT text reports. This freely available new tool could advance clinical research by integrating information in easily gathered head CT reports to expand knowledge of acute brain injury radiographic phenotypes.

Bedside monitoring of hypoxic ischemic brain injury using low-field, portable brain magnetic resonance imaging after cardiac arrest

BACKGROUND

Assessment of brain injury severity is critically important after survival from cardiac arrest (CA). Recent advances in low-field MRI technology have permitted the acquisition of clinically useful bedside brain imaging. Our objective was to deploy a novel approach for evaluating brain injury after CA in critically ill patients at high risk for adverse neurological outcome.

METHODS

This retrospective, single center study involved review of all consecutive portable MRIs performed as part of clinical care for CA patients between September 2020 and January 2022. Portable MR images were retrospectively reviewed by a blinded board-certified neuroradiologist (S.P.). Fluid-inversion recovery (FLAIR) signal intensities were measured in select regions of interest.

RESULTS

We performed 22 low-field MRI examinations in 19 patients resuscitated from CA (68.4% male, mean [standard deviation] age, 51.8 [13.1] years). Twelve patients (63.2%) had findings consistent with HIBI on conventional neuroimaging radiology report. Low-field MRI detected findings consistent with HIBI in all of these patients. Low-field MRI was acquired at a median (interquartile range) of 78 (40-136) hours post-arrest. Quantitatively, we measured FLAIR signal intensity in three regions of interest, which were higher amongst patients with confirmed HIBI. Low-field MRI was completed in all patients without disruption of intensive care unit equipment monitoring and no safety events occurred.

CONCLUSION

In a critically ill CA population in whom MR imaging is often not feasible, low-field MRI can be deployed at the bedside to identify HIBI. Low-field MRI provides an opportunity to evaluate the time-dependent nature of MRI findings in CA survivors.

Deep Learning Applications for Acute Stroke Management

Brain imaging is essential to the clinical care of patients with stroke, a leading cause of disability and death worldwide. Whereas advanced neuroimaging techniques offer opportunities for aiding acute stroke management, several factors, including time delays, inter-clinician variability, and lack of systemic conglomeration of clinical information, hinder their maximal utility. Recent advances in deep machine learning (DL) offer new strategies for harnessing computational medical image analysis to inform decision making in acute stroke. We examine the current state of the field for DL models in stroke triage. First, we provide a brief, clinical practice-focused primer on DL. Next, we examine real-world examples of DL applications in pixel-wise labeling, volumetric lesion segmentation, stroke detection, and prediction of tissue fate postintervention. We evaluate recent deployments of deep neural networks and their ability to automatically select relevant clinical features for acute decision making, reduce inter-rater variability, and boost reliability in rapid neuroimaging assessments, and integrate neuroimaging with electronic medical record (EMR) data in order to support clinicians in routine and triage stroke management. Ultimately, we aim to provide a framework for critically evaluating existing automated approaches, thus equipping clinicians with the ability to understand and potentially apply DL approaches in order to address challenges in clinical practice. ANN NEUROL 2022.

Antiseizure Medication Treatment and Outcomes in Patients with Subarachnoid Hemorrhage Undergoing Continuous EEG Monitoring

BACKGROUND

Patients with aneurysmal subarachnoid hemorrhage (aSAH) with electroencephalographic epileptiform activity (seizures, periodic and rhythmic patterns, and sporadic discharges) are frequently treated with antiseizure medications (ASMs). However, the safety and effectiveness of ASM treatment for epileptiform activity has not been established. We used observational data to investigate the effectiveness of ASM treatment in patients with aSAH undergoing continuous electroencephalography (cEEG) to develop a causal hypothesis for testing in prospective trials.

METHODS

This was a retrospective single-center cohort study of patients with aSAH admitted between 2011 and 2016. Patients underwent ≥ 24 h of cEEG within 4 days of admission. All patients received primary ASM prophylaxis until aneurysm treatment (typically within 24 h of admission). Treatment exposure was defined as reinitiation of ASMs after aneurysm treatment and cEEG initiation. We excluded patients with non-cEEG indications for ASMs (e.g., epilepsy, acute symptomatic seizures). Outcomes measures were 90-day mortality and good functional outcome (modified Rankin Scale scores 0-3). Propensity scores were used to adjust for baseline covariates and disease severity.

RESULTS

Ninety-four patients were eligible (40 continued ASM treatment; 54 received prophylaxis only). ASM continuation was not significantly associated with higher 90-day mortality (propensity-adjusted hazard ratio [HR] = 2.01 [95% confidence interval (CI) 0.57-7.02]). ASM continuation was associated with lower likelihood for 90-day good functional outcome (propensity-adjusted HR = 0.39 [95% CI 0.18-0.81]). In a secondary analysis, low-intensity treatment (low-dose single ASM) was not significantly associated with mortality (propensity-adjusted HR = 0.60 [95% CI 0.10-3.59]), although it was associated with a lower likelihood of good outcome (propensity-adjusted HR = 0.37 [95% CI 0.15-0.91]), compared with prophylaxis. High-intensity treatment (high-dose single ASM, multiple ASMs, or anesthetics) was associated with higher mortality (propensity-adjusted HR = 6.80 [95% CI 1.67-27.65]) and lower likelihood for good outcomes (propensity-adjusted HR = 0.30 [95% CI 0.10-0.94]) compared with prophylaxis only.

CONCLUSIONS

Our findings suggest the testable hypothesis that continuing ASMs in patients with aSAH with cEEG abnormalities does not improve functional outcomes. This hypothesis should be tested in prospective randomized studies.

Measuring expertise in identifying interictal epileptiform discharges

OBJECTIVE

Interictal epileptiform discharges on EEG are integral to diagnosing epilepsy. However, EEGs are interpreted by readers with and without specialty training, and there is no accepted method to assess skill in interpretation. We aimed to develop a test to quantify IED recognition skills.

METHODS

A total of 13,262 candidate IEDs were selected from EEGs and scored by eight fellowship-trained reviewers to establish a gold standard. An online test was developed to assess how well readers with different training levels could distinguish candidate waveforms. Sensitivity, false positive rate and calibration were calculated for each reader. A simple mathematical model was developed to estimate each reader's skill and threshold in identifying an IED, and to develop receiver operating characteristics curves for each reader. We investigated the number of IEDs needed to measure skill level with acceptable precision.

RESULTS

Twenty-nine raters completed the test; nine experts, seven experienced non-experts and thirteen novices. Median calibration errors for experts, experienced non-experts and novices were -0.056, 0.012, 0.046; median sensitivities were 0.800, 0.811, 0.715; and median false positive rates were 0.177, 0.272, 0.396, respectively. The number of test questions needed to measure those scores was 549. Our analysis identified that novices had a higher noise level (uncertainty) compared to experienced non-experts and experts. Using calculated noise and threshold levels, receiver operating curves were created, showing increasing median area under the curve from novices (0.735), to experienced non-experts (0.852) and experts (0.891).

SIGNIFICANCE

Expert and non-expert readers can be distinguished based on ability to identify IEDs. This type of assessment could also be used to identify and correct differences in thresholds in identifying IEDs.

Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke

Brain imaging is essential to the clinical management of patients with ischemic stroke. Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways. Here, portable magnetic resonance imaging (pMRI) acquired at very low magnetic field strength (0.064 T) is used to obtain actionable bedside neuroimaging for 50 confirmed patients with ischemic stroke. Low-field pMRI detected infarcts in 45 (90%) patients across cortical, subcortical, and cerebellar structures. Lesions as small as 4 mm were captured. Infarcts appeared as hyperintense regions on T2-weighted, fluid-attenuated inversion recovery and diffusion-weighted imaging sequences. Stroke volume measurements were consistent across pMRI sequences and between low-field pMRI and conventional high-field MRI studies. Low-field pMRI stroke volumes significantly correlated with stroke severity and functional outcome at discharge. These results validate the use of low-field pMRI to obtain clinically useful imaging of stroke, setting the stage for use in resource-limited environments.

The Utility of Quantitative EEG in Detecting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

SUMMARY

In this review, we discuss the utility of quantitative EEG parameters for the detection of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage in the context of the complex pathophysiology of DCI and the limitations of current diagnostic methods. Because of the multifactorial pathophysiology of DCI, methodologies solely assessing blood vessel narrowing (vasospasm) are insufficient to detect all DCI. Quantitative EEG has facilitated the exploration of EEG as a diagnostic modality of DCI. Multiple quantitative EEG parameters such as alpha power, relative alpha variability, and alpha/delta ratio show reliable detection of DCI in multiple studies. Recent studies on epileptiform abnormalities suggest that their potential for the detection of DCI. Quantitative EEG is a promising, continuous, noninvasive, monitoring modality of DCI implementable in daily practice. Future work should validate these parameters in larger populations, facilitated by the development of automated detection algorithms and multimodal data integration.

Combining Transcranial Doppler and EEG Data to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage

BACKGROUND AND OBJECTIVES

Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and predicts increased DCI risk. Our objective was to determine whether combining EEG and TCD data improves prediction of DCI after SAH. We hypothesize that integrating these diagnostic modalities improves DCI prediction.

METHODS

We retrospectively assessed patients with moderate to severe SAH (2011-2015; Fisher 3-4 or Hunt-Hess 4-5) who had both prospective TCD and EEG acquisition during hospitalization. Middle cerebral artery (MCA) peak systolic velocities (PSVs) and the presence or absence of epileptiform abnormalities (EAs), defined as seizures, epileptiform discharges, and rhythmic/periodic activity, were recorded daily. Logistic regressions were used to identify significant covariates of EAs and TCD to predict DCI. Group-based trajectory modeling (GBTM) was used to account for changes over time by identifying distinct group trajectories of MCA PSV and EAs associated with DCI risk.

RESULTS

We assessed 107 patients; DCI developed in 56 (51.9%). Univariate predictors of DCI are presence of high-MCA velocity (PSV ≥200 cm/s, sensitivity 27%, specificity 89%) and EAs (sensitivity 66%, specificity 62%) on or before day 3. Two univariate GBTM trajectories of EAs predicted DCI (sensitivity 64%, specificity 62.75%). Logistic regression and GBTM models using both TCD and EEG monitoring performed better. The best logistic regression and GBTM models used both TCD and EEG data, Hunt-Hess score at admission, and aneurysm treatment as predictors of DCI (logistic regression: sensitivity 90%, specificity 70%; GBTM: sensitivity 89%, specificity 67%).

DISCUSSION

EEG and TCD biomarkers combined provide the best prediction of DCI. The conjunction of clinical variables with the timing of EAs and high MCA velocities improved model performance. These results suggest that TCD and cEEG are promising complementary monitoring modalities for DCI prediction. Our model has potential to serve as a decision support tool in SAH management.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that combined TCD and EEG monitoring can identify delayed cerebral ischemia after SAH.

Bedside detection of intracranial midline shift using portable magnetic resonance imaging

Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07–40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11–2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.

Hospital Revisits for Post-Ischemic Stroke Epilepsy after Acute Stroke Interventions

OBJECTIVES

Improvements in acute stroke care have led to an increase in ischemic stroke survivors, who are at risk for development of post-ischemic stroke epilepsy (PISE). The impact of therapies such as thrombectomy and thrombolysis on risk of hospital revisits for PISE is unclear. We utilized administrative data to investigate the association between stroke treatment and PISE-related visits.

MATERIALS AND METHODS

Using claims data from California, New York, and Florida, we performed a retrospective analysis of adult survivors of acute ischemic strokes. Patients with history of epilepsy, trauma, infections, or tumors were excluded. Included patients were followed for a primary outcome of revisits for seizures or epilepsy. Cox proportional hazards regression was used to identify covariates associated with PISE.

RESULTS

In 595,545 included patients (median age 74 [IQR 21], 52% female), the 6-year cumulative rate of PISE-related revisit was 2.20% (95% CI 2.16-2.24). In multivariable models adjusting for demographics, comorbidities, and indicators of stroke severity, IV-tPA (HR 1.42, 95% CI 1.31-1.54, p<0.001) but not MT (HR 1.62, 95% CI 0.90-1.50, p=0.2) was associated with PISE-related revisit. Patients who underwent decompressive craniectomy experienced a 2-fold increase in odds for returning with PISE (HR 2.35, 95% CI 1.69-3.26, p<0.001). In-hospital seizures (HR 4.06, 95% CI 3.76-4.39, p<0.001) also elevated risk for PISE.

SIGNIFICANCE

We demonstrate that ischemic stroke survivors who received IV-tPA, underwent decompressive craniectomy, or experienced acute seizures were at increased risk PISE-related revisit. Close attention should be paid to these patients with increased potential for long-term development of and re-hospitalization for PISE.

Association of Posttraumatic Epilepsy With 1-Year Outcomes After Traumatic Brain Injury

IMPORTANCE

Posttraumatic epilepsy (PTE) is a recognized sequela of traumatic brain injury (TBI), but the long-term outcomes associated with PTE independent of injury severity are not precisely known.

OBJECTIVE

To determine the incidence, risk factors, and association with functional outcomes and self-reported somatic, cognitive, and psychological concerns of self-reported PTE in a large, prospectively collected TBI cohort.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter, prospective cohort study was conducted as part of the Transforming Research and Clinical Knowledge in Traumatic Brain Injury study and identified patients presenting with TBI to 1 of 18 participating level 1 US trauma centers from February 2014 to July 2018. Patients with TBI, extracranial orthopedic injuries (orthopedic controls), and individuals without reported injuries (eg, friends and family of participants; hereafter friend controls) were prospectively followed for 12 months. Data were analyzed from January 2020 to April 2021.

EXPOSURE

Demographic, imaging, and clinical information was collected according to TBI Common Data Elements. Incidence of self-reported PTE was assessed using the National Institute of Neurological Disorders and Stroke Epilepsy Screening Questionnaire (NINDS-ESQ).

MAIN OUTCOMES AND MEASURES

Primary outcomes included Glasgow Outcome Scale Extended, Rivermead Cognitive Metric (RCM; derived from the Rivermead Post Concussion Symptoms Questionnaire), and the Brief Symptom Inventory-18 (BSI).

RESULTS

Of 3296 participants identified as part of the study, 3044 met inclusion criteria, and 1885 participants (mean [SD] age, 41.3 [17.1] years; 1241 [65.8%] men and 644 [34.2%] women) had follow-up information at 12 months, including 1493 patients with TBI; 182 orthopedic controls, 210 uninjured friend controls; 41 patients with TBI (2.8%) and no controls had positive screening results for PTE. Compared with a negative screening result for PTE, having a positive screening result for PTE was associated with presenting Glasgow Coma Scale score (8.1 [4.8] vs.13.5 [3.3]; P < .001) as well as with anomalous acute head imaging findings (risk ratio, 6.42 [95% CI, 2.71-15.22]). After controlling for age, initial Glasgow Coma Scale score, and imaging findings, compared with patients with TBI and without PTE, patients with TBI and with positive PTE screening results had significantly lower Glasgow Outcome Scale Extended scores (mean [SD], 6.1 [1.7] vs 4.7 [1.5]; P < .001), higher BSI scores (mean [SD], 50.2 [10.7] vs 58.6 [10.8]; P = .02), and higher RCM scores (mean [SD], 3.1 [2.6] vs 5.3 [1.9]; P = .002) at 12 months.

CONCLUSIONS AND RELEVANCE

In this cohort study, the incidence of self-reported PTE after TBI was found to be 2.8% and was independently associated with unfavorable outcomes. These findings highlight the need for effective antiepileptogenic therapies after TBI.

Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage population

BACKGROUND AND PURPOSE

Radiomics provides a framework for automated extraction of high-dimensional feature sets from medical images. We aimed to determine radiomics signature correlates of admission clinical severity and medium-term outcome from intracerebral hemorrhage (ICH) lesions on baseline head computed tomography (CT).

METHODS

We used the ATACH-2 (Antihypertensive Treatment of Acute Cerebral Hemorrhage II) trial dataset. Patients included in this analysis (n = 895) were randomly allocated to discovery (n = 448) and independent validation (n = 447) cohorts. We extracted 1130 radiomics features from hematoma lesions on baseline noncontrast head CT scans and generated radiomics signatures associated with admission Glasgow Coma Scale (GCS), admission National Institutes of Health Stroke Scale (NIHSS), and 3-month modified Rankin Scale (mRS) scores. Spearman's correlation between radiomics signatures and corresponding target variables was compared with hematoma volume.

RESULTS

In the discovery cohort, radiomics signatures, compared to ICH volume, had a significantly stronger association with admission GCS (0.47 vs. 0.44, p = 0.008), admission NIHSS (0.69 vs. 0.57, p < 0.001), and 3-month mRS scores (0.44 vs. 0.32, p < 0.001). Similarly, in independent validation, radiomics signatures, compared to ICH volume, had a significantly stronger association with admission GCS (0.43 vs. 0.41, p = 0.02), NIHSS (0.64 vs. 0.56, p < 0.001), and 3-month mRS scores (0.43 vs. 0.33, p < 0.001). In multiple regression analysis adjusted for known predictors of ICH outcome, the radiomics signature was an independent predictor of 3-month mRS in both cohorts.

CONCLUSIONS

Limited by the enrollment criteria of the ATACH-2 trial, we showed that radiomics features quantifying hematoma texture, density, and shape on baseline CT can provide imaging correlates for clinical presentation and 3-month outcome. These findings couldtrigger a paradigm shift where imaging biomarkers may improve current modelsfor prognostication, risk-stratification, and treatment triage of ICH patients.

A model of metabolic supply-demand mismatch leading to secondary brain injury

Secondary brain injury (SBI) is defined as new or worsening injury to the brain after an initial neurologic insult, such as hemorrhage, trauma, ischemic stroke, or infection. It is a common and potentially preventable complication following many types of primary brain injury (PBI). However, mechanistic details about how PBI leads to additional brain injury and evolves into SBI are poorly characterized. In this work, we propose a mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH) of SBI. Our model, based on the Hodgkin-Huxley model, supplemented with additional dynamics for extracellular potassium, oxygen concentration, and excitotoxity, provides a high-level unified explanation for why patients with acute brain injury frequently develop SBI. We investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, and seizures can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI. The proposed model also helps explain several important empirical observations, including the common association of acute brain injury with seizures, the association of seizures with tissue hypoxia and so on. In contrast to current practices which assume that ischemia plays the predominant role in SBI, our model suggests that metabolic crisis involved in SBI can also be nonischemic. Our findings offer a more comprehensive understanding of the complex interrelationship among potassium, oxygen, excitotoxicity, seizures, and SBI.NEW & NOTEWORTHY We present a novel mechanistic model for the metabolic supply demand mismatch hypothesis (MSDMH), which attempts to explain why patients with acute brain injury frequently develop seizure activity and secondary brain injury (SBI). Specifically, we investigate how decreased oxygen, increased extracellular potassium, excitotoxicity, seizures, all common sequalae of primary brain injury (PBI), can induce SBI and suggest three underlying paths for how events following PBI may lead to SBI.

Electroencephalographic Abnormalities are Common in COVID-19 and are Associated with Outcomes

OBJECTIVE

The aim was to determine the prevalence and risk factors for electrographic seizures and other electroencephalographic (EEG) patterns in patients with Coronavirus disease 2019 (COVID-19) undergoing clinically indicated continuous electroencephalogram (cEEG) monitoring and to assess whether EEG findings are associated with outcomes.

METHODS

We identified 197 patients with COVID-19 referred for cEEG at 9 participating centers. Medical records and EEG reports were reviewed retrospectively to determine the incidence of and clinical risk factors for seizures and other epileptiform patterns. Multivariate Cox proportional hazards analysis assessed the relationship between EEG patterns and clinical outcomes.

RESULTS

Electrographic seizures were detected in 19 (9.6%) patients, including nonconvulsive status epilepticus (NCSE) in 11 (5.6%). Epileptiform abnormalities (either ictal or interictal) were present in 96 (48.7%). Preceding clinical seizures during hospitalization were associated with both electrographic seizures (36.4% in those with vs 8.1% in those without prior clinical seizures, odds ratio [OR] 6.51, p = 0.01) and NCSE (27.3% vs 4.3%, OR 8.34, p = 0.01). A pre-existing intracranial lesion on neuroimaging was associated with NCSE (14.3% vs 3.7%; OR 4.33, p = 0.02). In multivariate analysis of outcomes, electrographic seizures were an independent predictor of in-hospital mortality (hazard ratio [HR] 4.07 [1.44-11.51], p < 0.01). In competing risks analysis, hospital length of stay increased in the presence of NCSE (30 day proportion discharged with vs without NCSE: HR 0.21 [0.03-0.33] vs 0.43 [0.36-0.49]).

INTERPRETATION

This multicenter retrospective cohort study demonstrates that seizures and other epileptiform abnormalities are common in patients with COVID-19 undergoing clinically indicated cEEG and are associated with adverse clinical outcomes. ANN NEUROL 2021;89:872-883.

Prenylflavonoids isolated from Macaranga tanarius stimulate odontoblast differentiation of human dental pulp stem cells and tooth root formation via the mitogen-activated protein kinase and protein kinase B pathways

AIM

To identify odontogenesis-promoting compounds and examine the molecular mechanism underlying enhanced odontoblast differentiation and tooth formation.

METHODOLOGY

Five different nymphaeols, nymphaeol B (NB), isonymphaeol B (INB), nymphaeol A (NA), 3'-geranyl-naringenin (GN) and nymphaeol C (NC) were isolated from the fruit of Macaranga tanarius. The cytotoxic effect of nymphaeols on human DPSCs was observed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The effect of nymphaeols on odontoblast differentiation was analysed with Alizarin Red S staining and odontoblast marker expression was assessed using real-time polymerase chain reaction and Western blot analysis. The molecular mechanism was investigated with Western blot analysis. In order to examine the effect of INB on dentine formation in the developing tooth germ, INB-soaked beads were placed under the tooth bud explants in the collagen gel; thereafter, the tooth bud explant-bead complexes were implanted into the sub-renal capsules for 3 weeks. Tooth root formation was analysed using micro-computed tomography and histological analysis. Data are presented as mean ± standard error (SEM) values of three independent experiments, and results are compared using a two-tailed Student's t-test. The data were considered to have statistical significance when the P-value was less than 0.05.

RESULTS

Three of the compounds, NB, INB, and GN, did not exert a cytotoxic effect on human DPSCs. However, INB was most effective in promoting the deposition of calcium minerals in vitro (P < 0.001) and induced the expression of odontogenic marker genes (P < 0.05). Moreover, this compound strongly induced the phosphorylation of mitogen-activated protein (MAP) kinases and protein kinase B (AKT) (P < 0.05). The inhibition of p38 MAP, c-Jun N-terminal kinase (JNK), and AKT substantially suppressed the INB-induced odontoblast differentiation (P < 0.001). In addition, isonymphaeol B significantly induced the formation of dentine and elongation of the tooth root in vivo (P < 0.05).

CONCLUSIONS

Prenylflavonoids, including INB, exerted stimulatory effects on odontoblast differentiation and tooth root and dentine formation via the MAP kinase and AKT signalling pathways. These results suggest that nymphaeols could stimulate the repair processes for dentine defects or injuries.

Abstract P41: Integrating Demographics, TCD and EEG Diagnostic Modalities Improves Delayed Cerebral Ischemia Prediction After Subarachnoid Hemorrhage

Introduction: Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and predicts increased DCI risk. Clinical variables have also been used in DCI prediction. We hypothesize integrating these diagnostic modalities improves DCI prediction.

Methods: We assessed 107 patients with moderate-severe SAH (2011-2015) who had both TCD and EEG monitoring during hospitalization. Clinical demographics, including Hunt-Hess and aneurysm treatment (clipping/coiling), were collected via retrospective chart review. Middle cerebral artery (MCA) peak systolic velocities (PSV) and the presence or absence of epileptiform abnormalities (EA), defined as seizures, epileptiform discharges, and rhythmic/periodic activity, were recorded daily. Logistic regressions were used to identify EEG, TCD, and clinical variables associated with DCI. Group-Based Trajectory Modeling (GBTM) was used to account for changes over time by identifying distinct group trajectories of MCA and EA associated with DCI risk.

Results: Independent predictors of DCI in logistic regressions are: presence of high MCA velocity (PSV≥200cm/s) and presence of EA on or before day 3. There are 2 univariate GBTM trajectories of EA (%DCI in group 1=32.1, group 2=70.4) significantly associated with DCI, but MCA velocity trajectories are not significant. Logistic regression and GBTM models using both TCD and EEG monitoring improve upon models using either modality alone. Hunt-Hess score at admission and aneurysm treatment as covariates further improved model performance. The best models used both TCD and EEG monitoring modalities and clinical variables as predictors (logistic regression: Se=90%, Sp=70%; GBTM: Se=89%, Sp=67%).

Conclusions: EEG and TCD biomarkers combined provide the best prediction of DCI, compared to either alone. Models that considered the timing of EA and high MCA velocities plus clinical variables improved model performance.

Deep active learning for Interictal Ictal Injury Continuum EEG patterns

OBJECTIVES

Seizures and seizure-like electroencephalography (EEG) patterns, collectively referred to as "ictal interictal injury continuum" (IIIC) patterns, are commonly encountered in critically ill patients. Automated detection is important for patient care and to enable research. However, training accurate detectors requires a large labeled dataset. Active Learning (AL) may help select informative examples to label, but the optimal AL approach remains unclear.

METHODS

We assembled >200,000 h of EEG from 1,454 hospitalized patients. From these, we collected 9,808 labeled and 120,000 unlabeled 10-second EEG segments. Labels included 6 IIIC patterns. In each AL iteration, a Dense-Net Convolutional Neural Network (CNN) learned vector representations for EEG segments using available labels, which were used to create a 2D embedding map. Nearest-neighbor label spreading within the embedding map was used to create additional pseudo-labeled data. A second Dense-Net was trained using real- and pseudo-labels. We evaluated several strategies for selecting candidate points for experts to label next. Finally, we compared two methods for class balancing within queries: standard balanced-based querying (SBBQ), and high confidence spread-based balanced querying (HCSBBQ).

RESULTS

Our results show: 1) Label spreading increased convergence speed for AL. 2) All query criteria produced similar results to random sampling. 3) HCSBBQ query balancing performed best. Using label spreading and HCSBBQ query balancing, we were able to train models approaching expert-level performance across all pattern categories after obtaining ∼7000 expert labels.

CONCLUSION

Our results provide guidance regarding the use of AL to efficiently label large EEG datasets in critically ill patients.

Vessel wall MRI in ruptured cranial dural arteriovenous fistulas

Intracranial high-resolution vessel wall MRI (VW-MRI) is an imaging paradigm that is useful in site-of-rupture identification in patients presenting with spontaneous subarachnoid hemorrhage and multiple intracranial aneurysms. Only a handful of case reports describe its potential utility in the evaluation of more complex brain vascular malformations. We report for the first time three patients with ruptured cranial dural arteriovenous fistulas (dAVFs) that were evaluated with high-resolution VW-MRI. The presumed site-of-rupture was identified based on contiguity of a venous ectasia with adjacent blood products and thick, concentric wall enhancement. This preliminary experience suggests a role for high-resolution VW-MRI in the evaluation of ruptured cranial dAVFs, in particular, site-of-rupture identification. It also supports an emerging hypothesis that all spontaneously ruptured, macrovascular lesions demonstrate avid vessel wall enhancement.

Development of Expert-Level Automated Detection of Epileptiform Discharges During Electroencephalogram Interpretation

Importance

Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are a biomarker of epilepsy, seizure risk, and clinical decline. However, there is a scarcity of experts qualified to interpret EEG results. Prior attempts to automate IED detection have been limited by small samples and have not demonstrated expert-level performance. There is a need for a validated automated method to detect IEDs with expert-level reliability.

Objective

To develop and validate a computer algorithm with the ability to identify IEDs as reliably as experts and classify an EEG recording as containing IEDs vs no IEDs.

Design, Setting, and Participants

A total of 9571 scalp EEG records with and without IEDs were used to train a deep neural network (SpikeNet) to perform IED detection. Independent training and testing data sets were generated from 13 262 IED candidates, independently annotated by 8 fellowship-trained clinical neurophysiologists, and 8520 EEG records containing no IEDs based on clinical EEG reports. Using the estimated spike probability, a classifier designating the whole EEG recording as positive or negative was also built.

Main Outcomes and Measures

SpikeNet accuracy, sensitivity, and specificity compared with fellowship-trained neurophysiology experts for identifying IEDs and classifying EEGs as positive or negative or negative for IEDs. Statistical performance was assessed via calibration error and area under the receiver operating characteristic curve (AUC). All performance statistics were estimated using 10-fold cross-validation.

Results

SpikeNet surpassed both expert interpretation and an industry standard commercial IED detector, based on calibration error (SpikeNet, 0.041; 95% CI, 0.033-0.049; vs industry standard, 0.066; 95% CI, 0.060-0.078; vs experts, mean, 0.183; range, 0.081-0.364) and binary classification performance based on AUC (SpikeNet, 0.980; 95% CI, 0.977-0.984; vs industry standard, 0.882; 95% CI, 0.872-0.893). Whole EEG classification had a mean calibration error of 0.126 (range, 0.109-0.1444) vs experts (mean, 0.197; range, 0.099-0.372) and AUC of 0.847 (95% CI, 0.830-0.865).

Conclusions and Relevance

In this study, SpikeNet automatically detected IEDs and classified whole EEGs as IED-positive or IED-negative. This may be the first time an algorithm has been shown to exceed expert performance for IED detection in a representative sample of EEGs and may thus be a valuable tool for expedited review of EEGs.

Association of race and ethnicity to incident epilepsy, or epileptogenesis, after subdural hematoma

OBJECTIVE

To determine whether race is associated with the development of epilepsy after subdural hematoma (SDH), we identified adult survivors of SDH in a statewide administrative dataset and followed them up for at least 1 year for revisits associated with epilepsy.

METHODS

We performed a retrospective cohort study using claims data on all discharges from emergency departments (EDs) and hospitals in California. We identified adults (age ≥18 years) admitted from 2005 to 2011 with first-time traumatic and nontraumatic SDH. We used validated diagnosis codes to identify a primary outcome of ED or inpatient revisit for epilepsy. We used multivariable Cox regression for survival analysis to identify demographic and medical risk factors for epilepsy.

RESULTS

We identified 29,342 survivors of SDH (mean age 71.2 [SD 16.4] years, female sex 11,954 [41.1%]). Three thousand two hundred thirty (11.0%) patients had revisits to EDs or hospitals with a diagnosis of epilepsy during the study period. Black patients (n = 1,684 [5.7%]) had significantly increased risk compared to White patients (n = 16,945 [57.7%]; hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.28-1.64, p < 0.001). Status epilepticus during the index SDH admission, although infrequent (n = 94 [0.3%]), was associated with a nearly 4-fold risk of epilepsy (HR 3.75, 95% CI 2.80-5.03, p < 0.001). Alcohol use, drug use, smoking, renal disease, and markers of injury severity (i.e., intubation, surgical intervention, length of stay, disposition other than home) were also associated with epilepsy (all p < 0.05).

CONCLUSIONS

We found an association between Black race and ED and hospital revisits for epilepsy after SDH, establishing the presence of a racial subgroup that is particularly vulnerable to post-SDH epileptogenesis.

Assessment of Brain Injury Using Portable, Low-Field Magnetic Resonance Imaging at the Bedside of Critically Ill Patients

IMPORTANCE

Neuroimaging is a key step in the clinical evaluation of brain injury. Conventional magnetic resonance imaging (MRI) systems operate at high-strength magnetic fields (1.5-3 T) that require strict, access-controlled environments. Limited access to timely neuroimaging remains a key structural barrier to effectively monitor the occurrence and progression of neurological injury in intensive care settings. Recent advances in low-field MRI technology have allowed for the acquisition of clinically meaningful imaging outside of radiology suites and in the presence of ferromagnetic materials at the bedside.

OBJECTIVE

To perform an assessment of brain injury in critically ill patients in intensive care unit settings, using a portable, low-field MRI device at the bedside.

DESIGN, SETTING, AND PARTICIPANTS

This was a prospective, single-center cohort study of 50 patients admitted to the neuroscience or coronavirus disease 2019 (COVID-19) intensive care units at Yale New Haven Hospital in New Haven, Connecticut, from October 30, 2019, to May 20, 2020. Patients were eligible if they presented with neurological injury or alteration, no contraindications for conventional MRI, and a body habitus not exceeding the scanner's 30-cm vertical opening. Diagnosis of COVID-19 was determined by positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction nasopharyngeal swab result.

EXPOSURES

Portable MRI in an intensive care unit room.

MAIN OUTCOMES AND MEASURES

Demographic, clinical, radiological, and treatment data were collected and analyzed. Brain imaging findings are described.

RESULTS

Point-of-care MRI examinations were performed on 50 patients (16 women [32%]; mean [SD] age, 59 [12] years [range, 20-89 years]). Patients presented with ischemic stroke (n = 9), hemorrhagic stroke (n = 12), subarachnoid hemorrhage (n = 2), traumatic brain injury (n = 3), brain tumor (n = 4), and COVID-19 with altered mental status (n = 20). Examinations were acquired at a median of 5 (range, 0-37) days after intensive care unit admission. Diagnostic-grade T1-weighted, T2-weighted, T2 fluid-attenuated inversion recovery, and diffusion-weighted imaging sequences were obtained for 37, 48, 45, and 32 patients, respectively. Neuroimaging findings were detected in 29 of 30 patients who did not have COVID-19 (97%), and 8 of 20 patients with COVID-19 (40%) demonstrated abnormalities. There were no adverse events or complications during deployment of the portable MRI or scanning in an intensive care unit room.

CONCLUSIONS AND RELEVANCE

This single-center series of patients with critical illness in an intensive care setting demonstrated the feasibility of low-field, portable MRI. These findings demonstrate the potential role of portable MRI to obtain neuroimaging in complex clinical care settings.

Detecting Seizures and Epileptiform Abnormalities in Acute Brain Injury

PURPOSE OF REVIEW

Acute brain injury (ABI) is a broad category of pathologies, including traumatic brain injury, and is commonly complicated by seizures. Electroencephalogram (EEG) studies are used to detect seizures or other epileptiform patterns. This review seeks to clarify EEG findings relevant to ABI, explore practical barriers limiting EEG implementation, discuss strategies to leverage EEG monitoring in various clinical settings, and suggest an approach to utilize EEG for triage.

RECENT FINDINGS

Current literature suggests there is an increased morbidity and mortality risk associated with seizures or patterns on the ictal-interictal continuum (IIC) due to ABI. Further, increased use of EEG is associated with better clinical outcomes. However, there are many logistical barriers to successful EEG implementation that prohibit its ubiquitous use. Solutions to these limitations include the use of rapid EEG systems, non-expert EEG analysis, machine learning algorithms, and the incorporation of EEG data into prognostic models.

Clinical Characteristics of Developmentally Delayed Children based on Interdisciplinary Evaluation

The aim of this study is to examine the clinical characteristics of children suspected to have neurodevelopmental disorders and to present features that could be helpful diagnostic clues at the clinical assessment stage. All children who visited the interdisciplinary clinic for developmental problems from May 2001 to December 2014 were eligible for this study. Medical records of the children were reviewed. A total of 1,877 children were enrolled in this study. Most children were classified into four major diagnostic groups: global developmental delay (GDD), autism spectrum disorder (ASD), developmental language disorder (DLD) and motor delay (MD). GDD was the most common (43.9%), and boys were significantly more predominant than girls in all groups. When evaluating the predictive power of numerous risk factors, the probability of GDD was lower than the probability of ASD among boys, while the probability of GDD increased as independent walking age increased. Compared with GDD and DLD, the probability of GDD was increased when there was neonatal history or when the independent walking age was late. Comparison of ASD and DLD showed that the probability of ASD decreased when a maternal history was present, whereas the probability of ASD increased with male gender. To conclude, the present study revealed the clinical features of children with various neurodevelopmental disorders. These results are expected to be helpful for more effectively flagging children with potential neurodevelopmental disorders in the clinical setting.

Soluble ST2 Is Associated With New Epileptiform Abnormalities Following Nontraumatic Subarachnoid Hemorrhage

Background and Purpose- We evaluated the association between 2 types of predictors of delayed cerebral ischemia after nontraumatic subarachnoid hemorrhage, including biomarkers of the innate immune response and neurophysiologic changes on continuous electroencephalography. Methods- We studied subarachnoid hemorrhage patients that had at least 72 hours of continuous electroencephalography and blood samples collected within the first 5 days of symptom onset. We measured inflammatory biomarkers previously associated with delayed cerebral ischemia and functional outcome, including soluble ST2 (sST2), IL-6 (interleukin-6), and CRP (C-reactive protein). Serial plasma samples and cerebrospinal fluid sST2 levels were available in a subgroup of patients. Neurophysiologic changes were categorized into new or worsening epileptiform abnormalities (EAs) or new background deterioration. The association of biomarkers with neurophysiologic changes were evaluated using the Wilcoxon rank-sum test. Plasma and cerebrospinal fluid sST2 were further examined longitudinally using repeated measures mixed-effects models. Results- Forty-six patients met inclusion criteria. Seventeen (37%) patients developed new or worsening EAs, 21 (46%) developed new background deterioration, and 8 (17%) developed neither. Early (day, 0-5) plasma sST2 levels were higher among patients with new or worsening EAs (median 115 ng/mL [interquartile range, 73.8-197]) versus those without (74.7 ng/mL [interquartile range, 44.8-102]; P=0.024). Plasma sST2 levels were similar between patients with or without new background deterioration. Repeated measures mixed-effects modeling that adjusted for admission risk factors showed that the association with new or worsening EAs remained independent for both plasma sST2 (β=0.41 [95% CI, 0.09-0.73]; P=0.01) and cerebrospinal fluid sST2 (β=0.97 [95% CI, 0.14-1.8]; P=0.021). IL-6 and CRP were not associated with new background deterioration or with new or worsening EAs. Conclusions- In patients admitted with subarachnoid hemorrhage, sST2 level was associated with new or worsening EAs but not new background deterioration. This association may identify a link between a specific innate immune response pathway and continuous electroencephalography abnormalities in the pathogenesis of secondary brain injury after subarachnoid hemorrhage.

Abstract TMP22: Dynamic Worsening of Epileptiform Abnormalities Following Subarachnoid Hemorrhage is Associated With Poor 3-Month Outcomes

Objective: Worsening epileptiform abnormalities (EAs) and deteriorating background activity are common continuous electroencephalography (cEEG) patterns that predict subsequent clinical deterioration following subarachnoid hemorrhage (SAH). While worsening EAs and background deterioration both imply cortical dysfunction, we sought to clarify if these patterns have a different association with clinical outcomes.

Methods: We enrolled patients with SAH undergoing > 3 days of cEEG monitoring enrolled in a prospective outcome study with a modified Rankin Scale (mRS) assessment at 3 months. Worsening EAs included new or increasing burden of sporadic epileptiform discharges, lateralized rhythmic delta activity (LRDA), lateralized periodic discharges (LPD), or generalized periodic discharges (GPD). Background deterioration was defined as decreasing Alpha Delta Ratio (ADR), Relative Alpha Variability (RAV) or worsening focal slowing. We evaluated the association between these cEEG patterns and 3-month mRS >3 and examined whether the influence on outcome was independent of delayed cerebral ischemia (DCI).

Results: Of 59 patients meeting inclusion criteria (3-month mRS median 3 [IQR 1-5]), worsening EAs developed in 23 (39%) and new background deterioration in 24 (41%), whereas 24 patients (41%) developed neither finding and 12 (20%) developed both. Patients with worsening EAs were more likely to have a poor 3-month mRS compared to those without worsening EAs (OR 6.44; 95%CI 1.99-20.9; p=0.001). Developing new background deterioration was not significantly associated with poor 3-month outcome (OR 1.56, 95%CI 0.53-4.59; p=0.42). There was no additive effect on poor outcome of developing both findings. In a multivariate logistic regression, the effect of worsening EAs on 3-month mRS was independent of DCI.

Interpretation: While both worsening EAs and new background deterioration have previously been associated with DCI, only worsening EAs influences poor long-term outcome. Further investigation may clarify if distinct mechanisms underlie these differences.

Endophytic and endolichenic fungal diversity in maritime Antarctica based on cultured material and their evolutionary position among Dikarya

Fungal endophytes comprise one of the most ubiquitous groups of plant symbionts. They live asymptomatically within vascular plants, bryophytes and also in close association with algal photobionts inside lichen thalli. While endophytic diversity in land plants has been well studied, their diversity in lichens and bryophytes are poorly understood. Here, we compare the endolichenic and endophytic fungal communities isolated from lichens and bryophytes in the Barton Peninsula, King George Island, Antarctica. A total of 93 fungal isolates were collected from lichens and bryophytes. In order to determine their identities and evolutionary relationships, DNA sequences of the nuclear internal transcribed spacer (ITS), nuclear ribosomal small subunit (nuSSU), nuclear large subunit (nuLSU), and mitochondrial SSU (mtSSU) rDNA were obtained and protein coding markers of the two largest subunit of RNA polymerase II (RPB1 and RPB2) were generated. Multilocus phylogenetic analyses revealed that most of the fungal isolates were distributed in the following six classes in the phylum Ascomycota: Dothideomycetes, Eurotiomycetes, Lecanoromycetes, Leotiomycetes, Pezizomycetes and Sordariomycetes. For the first time we report the presence of subphylum Mortierellomycotina that may belong to an undescribed order in endophytic fungi. Taken together, our results imply that lichens and bryophytes provide similar niches and harbour a selection of these fungi, indicating generalists within the framework of evolutionary adaptation.

Reverse Locked-In Syndrome

BACKGROUND

Basilar artery occlusion can cause locked-in syndrome, which is characterized by quadriplegia, anarthria, and limited communication via eye movements. Here, we describe an uncommon stroke syndrome associated with endovascular recanalization of the top of the basilar artery: "reverse locked-in syndrome."

METHODS

We report the case of a patient with atypical neurological deficits caused by acute ischemic stroke of the midbrain tegmentum. We perform neuroanatomic localization of the patient's infarcts by mapping the magnetic resonance imaging (MRI) data onto a brainstem atlas.

RESULTS

A 61-year-old man presented with acute coma and quadriplegia due to top of the basilar artery occlusion. He underwent emergent endovascular thrombectomy, with successful recanalization of the basilar artery at 4 h and 43 min post-ictus. The patient regained consciousness and purposeful movement in all four extremities, but the post-procedure neurological examination demonstrated bilateral ptosis with complete pupillary and oculomotor paralysis. MRI revealed infarction of the bilateral oculomotor nuclei in the midbrain tegmentum. At 9-month follow-up, he had anisocoria and dysconjugate gaze, but was living at home and required minimal assistance in performing all activities of daily living.

CONCLUSIONS

Since the patient's deficits were the exact opposite of those described in locked-in syndrome, we propose the term "reverse locked-in syndrome" to describe this neurological entity characterized by bilateral ptosis, non-reactive pupils, and ophthalmoplegia with preservation of consciousness and extremity motor function.

Epileptiform activity in traumatic brain injury predicts post-traumatic epilepsy

We hypothesize that epileptiform abnormalities (EAs) in the electroencephalogram (EEG) during the acute period following traumatic brain injury (TBI) independently predict first-year post-traumatic epilepsy (PTE₁ ). We analyze PTE₁ risk factors in two cohorts matched for TBI severity and age (n = 50). EAs independently predict risk for PTE₁ (odds ratio [OR], 3.16 [0.99, 11.68]); subdural hematoma is another independent risk factor (OR, 4.13 [1.18, 39.33]). Differences in EA rates are apparent within 5 days following TBI. Our results suggest that increased EA prevalence identifies patients at increased risk for PTE₁ , and that EAs acutely post-TBI can identify patients most likely to benefit from antiepileptogenesis drug trials. Ann Neurol 2018;83:858-862.

Single-stage cell-based cartilage repair in a rabbit model: cell tracking and in vivo chondrogenesis of human umbilical cord blood-derived mesenchymal stem cells and hyaluronic acid hydrogel composite

OBJECTIVE

Human umbilical cord blood-derived mesenchymal stem cells (hUCB-MSCs) have gained popularity as a promising cell source for regenerative medicine, but limited in vivo studies have reported cartilage repair. In addition, the roles of MSCs in cartilage repair are not well-understood. The purpose of this study was to investigate the feasibility of transplanting hUCB-MSCs and hyaluronic acid (HA) hydrogel composite to repair articular cartilage defects in a rabbit model and determine whether the transplanted cells persisted or disappeared from the defect site.

DESIGN

Osteochondral defects were created in the trochlear grooves of the knees. The hUCB-MSCs and HA composite was transplanted into the defect of experimental knees. Control knees were transplanted by HA or left untreated. Animals were sacrificed at 8 and 16 weeks post-transplantation and additionally at 2 and 4 weeks to evaluate the fate of transplanted cells. The repair tissues were evaluated by gross, histological and immunohistochemical analysis.

RESULTS

Transplanting hUCB-MSCs and HA composite resulted in overall superior cartilage repair tissue with better quality than HA alone or no treatment. Cellular architecture and collagen arrangement at 16 weeks were similar to those of surrounding normal articular cartilage tissue. Histological scores also revealed that cartilage repair in experimental knees was better than that in control knees. Immunohistochemical analysis with anti-human nuclear antibody confirmed that the transplanted MSCs disappeared gradually over time.

CONCLUSION

Transplanting hUCB-MSCs and HA composite promote cartilage repair and interactions between hUCB-MSCs and host cells initiated by paracrine action may play an important role in cartilage repair.

Epileptiform abnormalities predict delayed cerebral ischemia in subarachnoid hemorrhage

OBJECTIVE

To identify whether abnormal neural activity, in the form of epileptiform discharges and rhythmic or periodic activity, which we term here ictal-interictal continuum abnormalities (IICAs), are associated with delayed cerebral ischemia (DCI).

METHODS

Retrospective analysis of continuous electroencephalography (cEEG) reports and medical records from 124 patients with moderate to severe grade subarachnoid hemorrhage (SAH). We identified daily occurrence of seizures and IICAs. Using survival analysis methods, we estimated the cumulative probability of IICA onset time for patients with and without delayed cerebral ischemia (DCI).

RESULTS

Our data suggest the presence of IICAs indeed increases the risk of developing DCI, especially when they begin several days after the onset of SAH. We found that all IICA types except generalized rhythmic delta activity occur more commonly in patients who develop DCI. In particular, IICAs that begin later in hospitalization correlate with increased risk of DCI.

CONCLUSIONS

IICAs represent a new marker for identifying early patients at increased risk for DCI. Moreover, IICAs might contribute mechanistically to DCI and therefore represent a new potential target for intervention to prevent secondary cerebral injury following SAH.

SIGNIFICANCE

These findings imply that IICAs may be a novel marker for predicting those at higher risk for DCI development.

Potentially modifiable risk factors for atrial fibrillation following lung resection surgery: a retrospective cohort study

Atrial fibrillation is the most frequent arrhythmia after thoracic surgery and is associated with increased hospital costs, morbidity and mortality. In this study, we aimed to identify potentially modifiable risk factors for postoperative atrial fibrillation following lung resection surgery and to suggest possible measures to reduce risk. We retrospectively reviewed the medical records of 4731 patients who underwent lobectomy or more major lung resection over a 6-year period. Patients who developed atrial fibrillation postoperatively and required treatment were included in the postoperative atrial fibrillation group, while the remaining patients were assigned to the non-postoperative atrial fibrillation group. Risk factors for postoperative atrial fibrillation were analysed by multivariate analysis and propensity score matching. Overall, 12% of patients developed postoperative atrial fibrillation. Potentially modifiable risk factors for postoperative atrial fibrillation were excessive alcohol consumption (odds ratio (OR) = 1.48, 95% CI 1.08-2.02, p = 0.0140), red cell transfusion (2.70(2.13-3.43), p < 0.0001), use of inotropes (1.81(1.42-2.31), p < 0.0001) and open (vs. thoracoscopic) surgery (1.59(1.23-2.05), p < 0.0001). Compared with inotrope use, vasopressor administration was not related to postoperative atrial fibrillation. Use of steroids or thoracic epidural anaesthesia did not reduce the incidence of postoperative atrial fibrillation. We conclude that high alcohol consumption, red cell transfusion, use of inotropes and open surgery are potentially modifiable risk factors for postoperative atrial fibrillation. Pre-operative alcohol consumption needs to be addressed. Avoiding red cell transfusion and performing lung resection via video-assisted thoracoscopic surgery may reduce the incidence of postoperative atrial fibrillation and the administration of vasopressors rather than inotropes is preferred.

Malva verticillata seed extracts upregulate the Wnt pathway in human dermal papilla cells

OBJECTIVE

Mesenchymal-epithelial interactions are important in controlling hair growth and the hair cycle. The β-catenin pathway of dermal papilla cells (DPCs) plays a pivotal role in morphogenesis and normal regeneration of hair follicles. Deletion of β-catenin in the dermal papilla reduces proliferation of the hair follicle progenitor cells that generate the hair shaft and induces an early onset of the catagen phase. In this study, a modulator of the Wnt/β-catenin activity was studied in oriental herb extracts on cultured human DPCs.

METHODS

The effect of Malva verticillata (M. verticillata) seeds on human DPCs was investigated by a Wnt/β-catenin reporter activity assay system (β-catenin-TCF/LEF reporter gene) and cell proliferation analysis. The synthesis of the factors related to hair growth and cycling was measured at both the mRNA and the protein level by semi-quantitative PCR and Western blot analysis, respectively.

RESULTS

An extract from M. verticillata seeds increased Wnt reporter activity in a concentration-dependent manner and also led to increased β-catenin levels in cultured human DPCs. Myristoleic acid, identified as an effective compound of M. verticillata seeds, stimulated the proliferation of DPCs in a dose-dependent manner and increased transcription levels of the downstream targets: IGF-1, KGF, VEGF and HGF. Myristoleic acid also enhanced the phosphorylation of MAPKs (Akt and p38).

CONCLUSION

Overall, the data suggest that this extract of M. verticillata seeds could be a good candidate for treating hair loss by modulating the Wnt/β-catenin pathway in DPCs.

Neural stem cell transplantation at critical period improves learning and memory through restoring synaptic impairment in Alzheimer's disease mouse model

Alzheimer's disease (AD) is characterized by neuronal loss in several regions of the brain. Recent studies have suggested that stem cell transplantation could serve as a potential therapeutic strategy to halt or ameliorate the inexorable disease progression. However, the optimal stage of the disease for stem cell transplantation to have a therapeutic effect has yet to be determined. Here, we demonstrated that transplantation of neural stem cells into 12-month-old Tg2576 brains markedly improved both cognitive impairments and neuropathological features by reducing β-amyloid processing and upregulating clearance of β-amyloid, secretion of anti-inflammatory cytokines, endogenous neurogenesis, as well as synapse formation. In contrast, the stem cell transplantation did not recover cognitive dysfunction and β-amyloid neuropathology in Tg2576 mice aged 15 months when the memory loss is manifest. Overall, this study underscores that stem cell therapy at optimal time frame is crucial to obtain maximal therapeutic effects that can restore functional deficits or stop the progression of AD.

Ecklonia cava promotes hair growth

BACKGROUND

Previous studies have reported the protective effects on skin elasticity of the edible marine seaweed Ecklonia cava, which acts through regulation of both antioxidative and anti-inflammatory responses.

AIM

We evaluated the effect of E. cava and one of its components, dioxinodehydroeckol, on hair-shaft growth in cultured human hair follicles and on hair growth in mice.

METHODS

The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was used to check cell viability of human dermal papilla cells (DPCs) and outer root sheath (ORS) cells after treatment with E. cava and its metabolite, dioxinodehydroeckol. Hair-shaft growth was measured using the in vitro hair-follicle organ-culture system, in the presence or absence of E. cava and dioxinodehydroeckol. Anagen induction activity was examined by topical application of E. cava to the dorsal skin of C57BL/6 mice. Insulin-like growth factor (IGF)-1 expression was measured by reverse transcriptase PCR and ELISA.

RESULTS

The proliferation activity was found to be highest for the ethyl acetate-soluble fraction of E. cava (EAFE) in DPCs and in ORS cells. Treatment with EAFE resulted in elongation of the hair shaft in cultured human hair follicles, and promoted transition of the hair cycle from the telogen to the anagen phase in the dorsal skin of C57BL/6 mice. In addition, EAFE induced an increase in IGF-1 expression in DPCs. Dioxinodehydroeckol, a component of E. cava, induced elongation of the hair shaft, an increase in proliferation of DPCs and ORS cells, and an increase in expression of IGF-1 in DPCs.

CONCLUSIONS

These results suggest that E. cava containing dioxinodehydroeckol promotes hair growth through stimulation of DPCs and ORS cells.

A comparison of the BURP and conventional and modified jaw thrust manoeuvres for orotracheal intubation using the Clarus Video System

We evaluated the effects of three airway manipulation manoeuvres: (a) conventional (single-handed chin lift); (b) backward, upward and right-sided pressure (BURP) manoeuvre; and (c) modified jaw thrust manoeuvre (two-handed aided by an assistant) on laryngeal view and intubation time using the Clarus Video System in 215 patients undergoing general anaesthesia with orotracheal intubation. In the first part of this study, the laryngeal view was recorded as a modified Cormack-Lehane grade with each manoeuvre. In the second part, intubation was performed using the assigned airway manipulation. The primary outcome was the time to intubation, and the secondary outcomes were the modified Cormack-Lehane grade, the number of attempts and the overall success rate. There were significant differences in modified Cormack-Lehane grade between the three airway manipulations (p < 0.0001). Post-hoc analysis indicated that the modified jaw thrust improved the laryngeal view compared with the conventional (p < 0.0001) and the BURP manoeuvres (p < 0.0001). The BURP worsened the laryngeal view compared with the conventional manoeuvre (p = 0.0132). The time to intubation in the modified jaw thrust group was shorter than with the conventional manoeuvre (p = 0.0004) and the BURP group (p < 0.0001). We conclude that the modified jaw thrust is the most effective manoeuvre at improving the laryngeal view and shortening intubation time with the Clarus Video System.

The effects of prolonged inspiratory time during one-lung ventilation: a randomised controlled trial

We evaluated the effects of a prolonged inspiratory time on gas exchange in subjects undergoing one-lung ventilation for thoracic surgery. One hundred patients were randomly assigned to Group I:E = 1:2 or Group I:E = 1:1. Arterial blood gas analysis and respiratory mechanics measurements were performed 10 min after anaesthesia induction, 30 and 60 min after initiation of one-lung ventilation, and 15 min after restoration of conventional two-lung ventilation. The mean (SD) ratio of the partial pressure of arterial oxygen to fraction of inspired oxygen after 60 min of one-lung ventilation was significantly lower in Group I:E = 1:2 compared with Group I:E = 1:1 (27.7 (13.2) kPa vs 35.2 (22.1) kPa, respectively, p = 0.043). Mean (SD) physiological dead space-to-tidal volume ratio after 60 min of one-lung ventilation was significantly higher in Group I:E = 1:2 compared with Group I:E = 1:1 (0.46 (0.04) vs 0.43 (0.04), respectively, p = 0.008). Median (IQR [range]) peak inspiratory pressure was higher in Group I:E = 1:2 compared with Group I:E = 1:1 after 60 min of one-lung ventilation (23 (22-25 [18-29]) cmH2O vs 20 (18-21 [16-27]) cmH2O, respectively, p < 0.001) and median (IQR [range]) mean airway pressure was lower in Group I:E = 1:2 compared with Group I:E = 1:1 (10 (8-11 [5-15]) cmH2O vs 11 (10-13 [5-16]) cmH2O, respectively, p < 0.001). We conclude that, compared with an I:E ratio of 1:2, an I:E ratio of 1:1 resulted in a modest improvement in oxygenation and decreased shunt fraction during one-lung ventilation.

Efficacy and safety of the dipeptidyl peptidase-4 inhibitor gemigliptin compared with sitagliptin added to ongoing metformin therapy in patients with type 2 diabetes inadequately controlled with metformin alone

AIMS

This study was designed to assess the efficacy and safety of a dipeptidyl peptidase-4 inhibitor, gemigliptin versus sitagliptin added to metformin in patients with type 2 diabetes.

METHODS

We conducted a double-blind, randomized, active-controlled trial in 425 Asian patients with inadequately controlled type 2 diabetes being treated with metformin alone. Eligible patients were randomized into three groups: 50 mg gemigliptin qd, 25 mg gemigliptin bid or sitagliptin 100 mg qd added to ongoing metformin treatment for 24 weeks. Haemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) were measured periodically, and oral glucose tolerance tests were performed at baseline and 24 weeks after starting the treatment regimen.

RESULTS

Twenty-four weeks later, adding gemigliptin (50 mg/day) to ongoing metformin therapy significantly improved glycaemic control. Reduction in HbA1c caused by 50 mg gemigliptin qd (-0.77% ± 0.8) was non-inferior to that caused by 100 mg sitagliptin qd (-0.8% ± 0.85). Proportion of patients achieving HbA1c <7% while taking 25 mg gemigliptin bid (50%) or 50 mg gemigliptin qd (54.07%) was comparable to the results with 100 mg sitagliptin qd (48.87%). There were significant decreases in FPG, postprandial glucose and AUC0-2 h glucose, as well as increases in GLP-1 and β cell sensitivity to glucose (supported by homeostasis model assessment of β-cell function, postprandial 2-h c-peptide and insulinogenic index) in patients receiving gemigliptin treatment with their metformin therapy. There was no increased risk of adverse effects with this dose of gemigliptin compared with sitagliptin 100 mg qd.

CONCLUSIONS

Addition of gemigliptin 50 mg daily to metformin was shown to be efficacious, well tolerated and non-inferior to sitagliptin in patients with type 2 diabetes mellitus.