Comparative analysis of patients with new onset refractory status epilepticus preceded by fever (febrile infection-related epilepsy syndrome) versus without prior fever: An interim analysis.

Febrile infection-related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non-FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non-FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non-FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non-infection-related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein-1 alpha (MIP-1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non-FIRES NORSE are very similar conditions.

Estimate of Patients With Missed Seizures Because of Delay in Conventional EEG.

PURPOSE: There is frequent delay between ordering and placement of conventional EEG. Here we estimate how many patients had seizures during this delay. METHODS: Two hundred fifty consecutive adult patients who underwent conventional EEG monitoring at the University of Wisconsin Hospital were retrospectively chart reviewed for demographics, time of EEG order, clinical and other EEG-related information. Patients were stratified by use of anti-seizure medications before EEG and into low-risk, medium-risk, and high-risk groups based on 2HELPS2B score (0, 1, or >1). Monte Carlo simulations (500 trials) were performed to estimate seizures during delay. RESULTS: The median delay from EEG order to performing EEG was 2.00 hours (range of 0.5-8.00 hours) in the total cohort. For EEGs ordered after-hours, it was 2.00 hours (range 0.5-8.00 hours), and during business hours, it was 2.00 hours (range 0.5-6.00 hours). The place of EEG, intensive care unit, emergency department, and general floor, did not show significant difference (P = 0.84). Anti-seizure medication did not affect time to first seizure in the low-risk (P = 0.37), medium-risk (P = 0.44), or high-risk (P = 0.12) groups. The estimated % of patients who had a seizure in the delay period for low-risk group (2HELPS2B = 0) was 0.8%, for the medium-risk group (2HELPS2B = 1) was 10.3%, and for the high-risk group (2HELPS2B > 1) was 17.6%, and overall risk was 7.2%. CONCLUSIONS: The University of Wisconsin Hospital with 24-hour in-house EEG technologists has a median delay of 2 hours from order to start of EEG, shorter than published reports from other centers. Nonetheless, seizures were likely missed in about 7.2% of patients.

Prevalence and localization of nocturnal epileptiform discharges in mild cognitive impairment.

Recent evidence shows that identifying and treating epileptiform abnormalities in patients with Alzheimer's disease could represent a potential avenue to improve clinical outcome. Specifically, animal and human studies have revealed that in the early phase of Alzheimer's disease, there is an increased risk of seizures. It has also been demonstrated that the administration of anti-seizure medications can slow the functional progression of the disease only in patients with EEG signs of cortical hyperexcitability. In addition, although it is not known at what disease stage hyperexcitability emerges, there remains no consensus regarding the imaging and diagnostic methods best able to detect interictal events to further distinguish different phenotypes of Alzheimer's disease. In this exploratory work, we studied 13 subjects with amnestic mild cognitive impairment and 20 healthy controls using overnight high-density EEG with 256 channels. All participants also underwent MRI and neuropsychological assessment. Electronic source reconstruction was also used to better select and localize spikes. We found spikes in six of 13 (46%) amnestic mild cognitive impairment compared with two of 20 (10%) healthy control participants (P = 0.035), representing a spike prevalence similar to that detected in previous studies of patients with early-stage Alzheimer's disease. The interictal events were low-amplitude temporal spikes more prevalent during non-rapid eye movement sleep. No statistically significant differences were found in cognitive performance between amnestic mild cognitive impairment patients with and without spikes, but a trend in immediate and delayed memory was observed. Moreover, no imaging findings of cortical and subcortical atrophy were found between amnestic mild cognitive impairment participants with and without epileptiform spikes. In summary, our exploratory study shows that patients with amnestic mild cognitive impairment reveal EEG signs of hyperexcitability early in the disease course, while no other significant differences in neuropsychological or imaging features were observed among the subgroups. If confirmed with longitudinal data, these exploratory findings could represent one of the first signatures of a preclinical epileptiform phenotype of amnestic mild cognitive impairment and its progression.

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 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.

Neurological Prognostication After Hypoglycemic Coma: Role of Clinical and EEG Findings.

BACKGROUND: Hypoglycemic coma (HC) is an uncommon but severe clinical condition associated with poor neurological outcome. There is a dearth of robust neurological prognostic factors after HC. On the other hand, there is an increasing body of literature on reliable prognostic markers in the postanoxic coma, a similar-albeit not identical-situation. The objective of this study was thus to investigate the use and predictive value of these markers in HC. METHODS: We conducted a retrospective, multicenter, cohort study within five centers of the Critical Care EEG Monitoring Research Consortium. We queried our electroencephalography (EEG) databases to identify all patients undergoing continuous EEG monitoring after admission to an intensive care unit with HC (defined as Glasgow Coma Scale < 8 on admission and a first blood glucose level < 50 mg/dL or not documented but in an obvious clinical context) between 01/01/2010 and 12/31/2020. We studied the association of findings at neurological examination (Glasgow Coma Scale motor subscale, pupillary light and corneal reflexes) and at continuous EEG monitoring(highly malignant patterns, reactivity, periodic discharges, seizures) with best neurological outcome within 3 months after hospital discharge, defined by the Cerebral Performance Category as favorable (1-3: recovery of consciousness) versus unfavorable (4-5: lack of recovery of consciousness). RESULTS: We identified 60 patients (30 [50%] women; age 62 [51-72] years). Thirty-one and 29 patients had a favorable and unfavorable outcome, respectively. The presence of pupillary reflexes (24 [100%] vs. 17 [81%]; p value 0.04) and a motor subscore > 2 (22 [92%] vs. 12 [63%]; p value 0.03) at 48-72 h were associated with a favorable outcome. A highly malignant EEG pattern was observed in 7 of 29 (24%) patients with unfavorable outcome versus 0 of 31 (0%) with favorable outcome, whereas the presence of EEG reactivity was observed in 28 of 31 (90%) patients with favorable outcome versus 13 of 29 (45%) with unfavorable outcome (p < 0.001 for comparison of all background categories). CONCLUSIONS: This preliminary study suggests that highly malignant EEG patterns might be reliable prognostic markers of unfavorable outcome after HC. Other EEG findings, including lack of EEG reactivity and seizures and clinical findings appear less accurate. These findings should be replicated in a larger multicenter prospective study.

Association Between Lateralized Periodic Discharge Amplitude and Seizure on Continuous EEG Monitoring in Patients With Structural Brain Abnormality in Critical Illness.

Objective: To investigate the association between lateralized periodic discharge (LPD) amplitude and seizure risk on an individual level in patients with structural brain abnormality. Methods: Retrospective case-control study of patients with structural brain abnormality undergoing continuous EEG monitoring was performed. We included 10 patients with LPDs and seizures as cases and 10 controls, patients with LPDs without seizure. Analysis was performed with a mixed-effects model with primary outcome measure of number of seizures per 8-h EEG epoch with fixed effects being variables of interest and random effect being subject ID. Results: Epochs with seizures showed a higher absolute amplitude (corrected p = 0.04) and a higher relative amplitude (corrected p = 0.04) of LPDs. Additionally, the number of seizures was higher in epochs that had LPDs with plus features (uncorrected p = 0.002) and LPDs with higher relative amplitude (uncorrected p = 0.005). Conclusion: Higher LPD amplitude is associated with increased risk of seizures on an individual patient level. A decreasing amplitude is suggestive of decreasing seizure risk, and may in fact be suggestive of decreasing ictal character of LPDs.

Health Assessment Questionnaire at One Year Predicts All-Cause Mortality in Patients With Early Rheumatoid Arthritis.

OBJECTIVE: Higher self-reported disability (high Health Assessment Questionnaire [HAQ] score) has been associated with hospitalizations and mortality in established rheumatoid arthritis (RA), but associations in early RA are unknown. METHODS: Patients with early RA (symptom duration <1 year) enrolled in the Canadian Early Arthritis Cohort who initiated disease-modifying antirheumatic drugs and had completed HAQ data at baseline and 1 year were included in the study. Discrete-time proportional hazards models were used to estimate crude and multi-adjusted associations of baseline HAQ and HAQ at 1 year with all-cause mortality in each year of follow-up. RESULTS: A total of 1,724 patients with early RA were included. The mean age was 55 years, and 72% were women. Over 10 years, 62 deaths (3.6%) were recorded. Deceased patients had higher HAQ scores at baseline (mean ± SD 1.2 ± 0.7) and at 1 year (0.9 ± 0.7) than living patients (1.0 ± 0.7 and 0.5 ± 0.6, respectively; P < 0.001). Disease Activity Score in 28 joints (DAS28) was higher in deceased versus living patients at baseline (mean ± SD 5.4 ± 1.3 versus 4.9 ± 1.4) and at 1 year (mean ± SD 3.6 ± 1.4 versus 2.8 ± 1.4) (P < 0.001). Older age, male sex, lower education level, smoking, more comorbidities, higher baseline DAS28, and glucocorticoid use were associated with mortality. Contrary to HAQ score at baseline, the association between all-cause mortality and HAQ score at 1 year remained significant even after adjustment for confounders. For baseline HAQ score, the unadjusted hazard ratio (HR) was 1.46 (95% confidence interval [95% CI] 1.02-2.09), and the adjusted HR was 1.25 (95% CI 0.81-1.94). For HAQ score at 1 year, the unadjusted HR was 2.58 (95% CI 1.78-3.72), and the adjusted HR was 1.75 (95% CI 1.10-2.77). CONCLUSION: Our findings indicate that higher HAQ score and DAS28 at 1 year are significantly associated with all-cause mortality in a large early RA cohort.

Development and validation of a decision aid for choosing among antithrombotic agents for atrial fibrillation.

BACKGROUND: Multiple antithrombotic agents are available for stroke prevention in atrial fibrillation (AF). A decision aid can assist patients in making informed decisions that best serves their needs. OBJECTIVE: To validate a decision aid to assist patients in choosing between antithrombotic agents (antiplatelets, warfarin, direct-acting oral anticoagulants (DOACs)) for AF. METHODS: Patients (60years or older) were recruited for this prospective study. The decision aid presented descriptions related to AF, then charts portraying important outcomes for comparisons between 1) no treatment, aspirin and anticoagulants, 2) warfarin versus DOACs, and 3) DOAC versus DOAC. The primary outcome was confidence in making treatment decisions. The secondary outcomes included change in knowledge scores, ratings of clarity, helpfulness and comprehensiveness. RESULTS: Eighty-one patients (mean age 75.2 [SD 7.5], 77% taking an anticoagulant) participated. After using the decision aid, mean decisional conflict score was low at 7.2 [SD 10.8] on a scale from 1 to 100. Mean knowledge score (total possible 10) improved from 7.4 [SD 1.7] to 9.3 [SD 1.0] (p<0.001). The mean helpfulness score in making a treatment choice was high at 6.2 [SD 0.9] on a scale from 1 to 7. No participant found the decision aid difficult to understand. Information in the decision aid was rated as good or excellent in terms of clarity and comprehensiveness. CONCLUSIONS: Our decision aid addresses a key medication safety gap - assisting patients to participate in shared decisions about anticoagulation. Future research is required to evaluate how decision aids influence actual choices and clinical outcomes.

Stretch-induced Activation of Transforming Growth Factor-ß1 in Pulmonary Fibrosis.

RATIONALE: Recent findings suggesting transforming growth factor (TGF)-ß1 activation by mechanical stimuli in vitro raised the question of whether this phenomenon was relevant in vivo in the context of pulmonary fibrosis. OBJECTIVES: To explore the effect of mechanical stress on TGF-ß1 activation and its signaling pathway in rat and human fibrotic lung tissue using a novel ex vivo model. METHODS: Rat lung fibrosis was induced using transient gene expression of active TGF-ß1. Lungs were harvested at Day 14 or 21 and submitted to various stimuli in a tissue bath equipped with a force transducer and servo-controlled arm. MEASUREMENTS AND MAIN RESULTS: Fibrotic lung strips responded to tensile force by releasing active TGF-ß1 from latent stores with subsequent increase in tissue phospho-Smad2/3. In contrast, measurable active TGF-ß1 and phospho-Smad2/3 were not induced by mechanical stress in nonfibrotic lungs. Protease inhibition did not affect the release of active TGF-ß1. A TGF-ß1 receptor inhibitor, Rho-associated protein kinase inhibitor, and αv integrin inhibitor all attenuated mechanical stretch-induced phospho-Smad2/3 in fibrotic lung strips. Furthermore, the induction of phospho-Smad2/3 was enhanced in whole fibrotic rat lungs undergoing ventilation pressure challenge compared with control lungs. Last, tissue slices from human lung with usual interstitial pneumonia submitted to mechanical force showed an increase in TGF-ß1 activation and induction of phospho-Smad2/3 in contrast with human nonfibrotic lungs. CONCLUSIONS: Mechanical tissue stretch contributes to the development of pulmonary fibrosis via mechanotransduced activation of TGF-ß1 in rodent and human pulmonary fibrosis.