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OBJECTIVE: The aim of this article is to answer three relevant issues: i/What epileptic condition is referred to as subacute encephalopathy with seizures in alcoholics (SESA) syndrome; ii/ Why it can be important to distinguish SESA syndrome in clinical practice and iii/ What do we know about its pathophysiology. METHODS: We reviewed all cases published in the English language from the initial description of the syndrome to the present. All met the previously established criteria for SESA syndrome were included in our analysis. RESULTS: We found 34 patients diagnosed with SESA syndrome Fourteen (41.1%) out of 34 patients were over 60 years of age. In 12 (35.2 %), abstinence, and in 4 (11.7 %) excessive consumption of alcohol, were considered precipitating factors, respectively. Triggering causes were unknown in 18 cases (53.0 %). All cases (100 %) presented with altered mental status. Fourteen (41.1 %) subjects had a history of epileptic seizures in the context of alcohol withdrawal syndrome (AWS). Twenty (58.8 %) patients had focal motor seizures (FMSs), 24 (70.5 %) bilateral tonic-clonic seizures (BTCSs), and 15 (44.1 %) focal impaired awareness seizures (FIASs). In 8 (23.5 %), criteria for focal nonconvulsive status epilepticus (NCSE) were met. Twenty-eight (82.3 %) subjects had transient neurological deficits. In 29 (85.2 %) subjects, lateralized periodic discharges (LPDs) were observed on the EEG. Areas of signal hyperintensities and restricted diffusion in neuroimaging were mentioned in 22 subjects (64.7 %). Transfer to the intensive care unit was necessary in 8 (23.5 %) subjects. Thirteen (38.2 %) had recurrent episodes. Enduring brain damage was mentioned in 9 (26.4 %) cases. The most used anti-seizure medication (ASM) was levetiracetam, followed by phenytoin and lacosamide. CONCLUSIONS: SESA syndrome represents a well-defined subtype of focal NCSE in patients with chronic alcoholism. Its prompt recognition can facilitate the initiation of early ASM therapy and help design appropriate video-EEG evaluation and a treatment strategy.
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PURPOSE: To describe four patients with subacute encephalopathy with seizures in alcoholics (SESA) syndrome and to review its clinical, electroencephalogram (EEG), neuroimaging and diagnostic criteria. METHODS: We conducted a retrospective analysis of a series of prospectively collected patients who met the previously established criteria for SESA syndrome. Subsequently, we reviewed all cases published in the English language from the initial description to the present. RESULTS: We found 34 patients diagnosed with SESA syndrome to date, including the four cases of SESA in this report. Fourteen out of 34 (41.1 %) patients were over 60 years of age. Twelve (35.2 %) were abstinent from alcohol and in 4 (11.7 %) there was excessive alcohol consumption. Triggering causes were unknown in 18 cases (53.0 %). All cases (100 %) presented with an altered mental status. Fourteen (41.1 %) subjects had a history of epileptic seizures in the context of acute withdrawal syndrome (AWS). Twenty (58.8 %) patients had focal motor seizures (FMSs), 24 (70.5 %) bilateral tonic-clonic seizures (BTCSs), and 15 (44.1 %) focal impaired awareness seizures (FIASs). In 8 (23.5 %), criteria for focal nonconvulsive status epilepticus (NCSE) were met. Twenty-eight (82.3 %) subjects had transient neurological deficits. In 29 (85.2 %) subjects, lateralized periodic discharges (LPDs) were observed in the EEG. Areas of increased T2/FLAIR signal and restricted diffusion were mentioned in 22 subjects (64.7 %). Transfer to the intensive care unit (ICU) was necessary in 8 (23.5 %) subjects. Thirteen (38.2 %) had recurrent episodes. Enduring cerebral sequelae had been mentioned in 9 (26.4 %) cases. The most used anti-seizure medication (ASM) was levetiracetam, followed by phenytoin and lacosamide. CONCLUSION: SESA syndrome represents a well-defined subtype of focal NCSE in patients with chronic alcoholism. Its prompt recognition can facilitate the initiation of early ASM therapy and help implement a video-EEG evaluation and neuroimaging strategy.
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Eletroencefalografia , Humanos , Masculino , Pessoa de Meia-Idade , Feminino , Estudos Retrospectivos , Convulsões/etiologia , Adulto , Idoso , Alcoolismo/complicações , Convulsões por Abstinência de Álcool/complicações , Síndrome , Anticonvulsivantes/uso terapêuticoRESUMO
BACKGROUND: In intensive care units (ICUs), critically ill patients are monitored with electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is constrained by clinician availability, and EEG interpretation can be subjective and prone to interobserver variability. Automated deep-learning systems for EEG could reduce human bias and accelerate the diagnostic process. However, existing uninterpretable (black-box) deep-learning models are untrustworthy, difficult to troubleshoot, and lack accountability in real-world applications, leading to a lack of both trust and adoption by clinicians. METHODS: We developed an interpretable deep-learning system that accurately classifies six patterns of potentially harmful EEG activity - seizure, lateralized periodic discharges (LPDs), generalized periodic discharges (GPDs), lateralized rhythmic delta activity (LRDA), generalized rhythmic delta activity (GRDA), and other patterns - while providing faithful case-based explanations of its predictions. The model was trained on 50,697 total 50-second continuous EEG samples collected from 2711 patients in the ICU between July 2006 and March 2020 at Massachusetts General Hospital. EEG samples were labeled as one of the six EEG patterns by 124 domain experts and trained annotators. To evaluate the model, we asked eight medical professionals with relevant backgrounds to classify 100 EEG samples into the six pattern categories - once with and once without artificial intelligence (AI) assistance - and we assessed the assistive power of this interpretable system by comparing the diagnostic accuracy of the two methods. The model's discriminatory performance was evaluated with area under the receiver-operating characteristic curve (AUROC) and area under the precision-recall curve. The model's interpretability was measured with task-specific neighborhood agreement statistics that interrogated the similarities of samples and features. In a separate analysis, the latent space of the neural network was visualized by using dimension reduction techniques to examine whether the ictal-interictal injury continuum hypothesis, which asserts that seizures and seizure-like patterns of brain activity lie along a spectrum, is supported by data. RESULTS: The performance of all users significantly improved when provided with AI assistance. Mean user diagnostic accuracy improved from 47 to 71% (P<0.04). The model achieved AUROCs of 0.87, 0.93, 0.96, 0.92, 0.93, and 0.80 for the classes seizure, LPD, GPD, LRDA, GRDA, and other patterns, respectively. This performance was significantly higher than that of a corresponding uninterpretable black-box model (with P<0.0001). Videos traversing the ictal-interictal injury manifold from dimension reduction (a two-dimensional representation of the original high-dimensional feature space) give insight into the layout of EEG patterns within the network's latent space and illuminate relationships between EEG patterns that were previously hypothesized but had not yet been shown explicitly. These results indicate that the ictal-interictal injury continuum hypothesis is supported by data. CONCLUSIONS: Users showed significant pattern classification accuracy improvement with the assistance of this interpretable deep-learning model. The interpretable design facilitates effective human-AI collaboration; this system may improve diagnosis and patient care in clinical settings. The model may also provide a better understanding of how EEG patterns relate to each other along the ictal-interictal injury continuum. (Funded by the National Science Foundation, National Institutes of Health, and others.).
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It is well known that the brain is quite vulnerable to oxidative stress, initiating neuronal loss after ischemia-reperfusion (IR) injury. A potent protective mechanism is ischemic preconditioning (IPC), where proteins are among the primary targets. This study explores redox-active proteins' role in preserving energy supply. Adult rats were divided into the control, IR, and IPC groups. Protein profiling was conducted to identify modified proteins and then verified through activity assays, immunoblot, and immunohistochemical analyses. IPC protected cortex mitochondria, as evidenced by a 2.26-fold increase in superoxide dismutase (SOD) activity. Additionally, stable core subunits of respiratory chain complexes ensured sufficient energy production, supported by a 16.6% increase in ATP synthase activity. In hippocampal cells, IPC led to the downregulation of energy-related dehydrogenases, while a significantly higher level of peroxiredoxin 6 (PRX6) was observed. Notably, IPC significantly enhanced glutathione reductase activity to provide sufficient glutathione to maintain PRX6 function. Astrocytes may mobilize PRX6 to protect neurons during initial ischemic events, by decreased PRX6 positivity in astrocytes, accompanied by an increase in neurons following both IR injury and IPC. Maintained redox signaling via astrocyte-neuron communication triggers IPC's protective state. The partnership among PRX6, SOD, and glutathione reductase appears essential in safeguarding and stabilizing the hippocampus.
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Cefepime is a fourth-generation cephalosporin that is widely used to treat sepsis but is associated with a potentially dangerous neurotoxicity syndrome, cefepime-induced neurotoxicity (CIN). As a result, patients treated with cefepime may be at higher risk for morbidity, including seizures, and mortality. Though the recent ACORN trial concluded that cefepime does not increase the risk of mortality, most of these patients were not critically ill or elderly, two of the most at risk populations for CIN. Further, diagnosis may be difficult in the critical care setting as patients may have multiple reasons for encephalopathy. Therefore, this population in particular should be studied and monitored closely for CIN. Importantly, there are not well defined diagnostic criteria for CIN to guide evaluation and management. Defining the risk factors for CIN and using laboratory and EEG to help support the clinical diagnosis could be helpful in early recognition of CIN to help institute treatment and to rule out seizures. In this mini review, we highlight risk factors for CIN, discuss the possible value of EEG, and propose a diagnostic and management approach in the evaluation and management of CIN.
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In the case of suspicion of nonconvulsive status epilepticus (NCSE), reactivity on electroencephalograms (EEGs) can provide valuable diagnostic information. Reactivity refers to responses to auditory or somatosensory stimulation, with changes in amplitude and frequency of background activity. Because of self-perpetuating processes and the failure of self-terminating mechanisms, status epilepticus is unlikely to cease when patients spontaneously move, and it cannot typically be stopped by external stimulation (i.e., auditory and tactile stimuli). The defining EEG characteristic of absence status epilepticus is the presence of bilateral, synchronous, symmetric, rhythmic paroxysmal activity that shows little or no reactivity to sensory stimulation. On the other hand, in metabolic/toxic or multifactorial encephalopathies, triphasic waves (TWs) are influenced by the level of vigilance. TWs may be transiently abolished when patients increase their level of alertness from a drowsy/lethargic state to a state of wakefulness. This reactivity is only observed when patients can be aroused by a somatosensory or auditory stimulus. This reactivity tends to disappear with increasing severity of the disease and in comatose patients. In patients without preexisting developmental and epileptic encephalopathy, this pattern of stimulus-induced wakefulness with transient improvement of the EEG is a major criterion in determining that the EEG patterns are not ictal. This criterion of reactivity on EEGs, beyond the classical clinical/EEG criteria of NCSE (Salzburg criteria), should now be systematically added.
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Nível de Alerta , Eletroencefalografia , Estado Epiléptico , Humanos , Eletroencefalografia/métodos , Nível de Alerta/fisiologia , Estado Epiléptico/fisiopatologia , Estado Epiléptico/diagnóstico , Estimulação Acústica/métodos , Diagnóstico DiferencialRESUMO
Background: Non-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States. Despite guidelines on ultraviolet (UV) avoidance, it remains difficult for people to assess their exposure, as UV is invisible and the onset of UV-induced symptoms is delayed. Methods: In a prospective randomized trial, 97 elderly patients with a history of actinic keratoses (AK) were followed over 6 months. Fifty patients received UV counseling from a dermatologist and a wearable UV dosimeter that provided real-time and cumulative UV exposure. Forty-seven patients received only UV counseling from a dermatologist. Results: Over 75% of participants recorded UV exposure at least once a week during the summer. After 6 months of intervention, when comparing the device group to the control group, we observed a non-significant 20% lower ratio of incidence rates of AKs (95% CI = [-41, 55%], p-value = 0.44) and a significant 95% lower ratio of incidence rates of NMSCs (95% CI = [33, 99.6%], p-value = 0.024). Surveys demonstrated that the control group's score in self-perceived ability to participate in social activities significantly increased by 1.2 (p-value = 0.04), while in the device group, this score non-significantly decreased by 0.9 (p-value = 0.1). We did not observe changes, or between-group differences, in anxiety and depression surveys. Conclusion: This pilot clinical trial has a short duration and a small sample size. However, device adherence and quality of life questionnaires suggest a smartphone-connected wearable UV dosimeter is well accepted by an elderly population. This trial also indicates that a wearable UV dosimeter may be an effective behavioral change tool to reduce NMSC incidence in an elderly population with a prior history of AKs.Clinical trial registration: clinicaltrials.gov, identifier NCT03315286.
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Metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease due to the absence of effective therapies. A more comprehensive understanding of molecular events, encompassing the dysregulation of microRNAs (miRs) and metabolic reprogramming, holds the potential to unveil precise mechanisms underlying mCRPC. This study aims to assess the expression of selected serum exosomal miRs (miR-15a, miR-16, miR-19a-3p, miR-21, and miR-141a-3p) alongside serum metabolomic profiling and their correlation in patients with mCRPC and benign prostate hyperplasia (BPH). Blood serum samples from mCRPC patients (n = 51) and BPH patients (n = 48) underwent metabolome analysis through 1H-NMR spectroscopy. The expression levels of serum exosomal miRs in mCRPC and BPH patients were evaluated using a quantitative real-time polymerase chain reaction (qRT-PCR). The 1H-NMR metabolomics analysis revealed significant alterations in lactate, acetate, citrate, 3-hydroxybutyrate, and branched-chain amino acids (BCAAs, including valine, leucine, and isoleucine) in mCRPC patients compared to BPH patients. MiR-15a, miR-16, miR-19a-3p, and miR-21 exhibited a downregulation of more than twofold in the mCRPC group. Significant correlations were predominantly observed between lactate, citrate, acetate, and miR-15a, miR-16, miR-19a-3p, and miR-21. The importance of integrating metabolome analysis of serum with selected serum exosomal miRs in mCRPC patients has been confirmed, suggesting their potential utility for distinguishing of mCRPC from BPH.
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MicroRNAs , Hiperplasia Prostática , Neoplasias de Próstata Resistentes à Castração , Masculino , Humanos , MicroRNAs/genética , Neoplasias de Próstata Resistentes à Castração/patologia , Soro/metabolismo , Citratos , Lactatos , AcetatosRESUMO
Electroencephalography (EEG) is a useful adjunct to clinical neurological examination, particularly as it may detect subtle or subclinical disturbance of cerebral function and it allows monitoring of cerebral activity over time. Continuous EEG combined with quantitative analysis and machine learning may help identify changes in real time, before the emergence of clinical signs and response to interventions. EEG is rarely pathognomonic in encephalopathy/encephalitis but when interpreted correctly and within the clinical context, certain phenotypes may indicate a specific pathophysiology (eg, lateralised periodic discharges in HSV-1, generalised periodic discharges in sporadic Creutzfeldt-Jakob disease, and extreme delta brushes in anti-n-methyl-D-aspartate receptor autoimmune encephalitis). EEG is included in some specialist guidelines for disease assessment, monitoring and prognostication (ie, hepatic, cancer immunotherapy, viral, prion, autoimmune encephalitis and hypoxic ischaemic encephalopathy). EEG is invaluable for confirming or excluding non-convulsive seizures or status epilepticus, particularly in critically ill patients, and in understanding new concepts such as epileptic encephalopathy and the ictal-interictal continuum.
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Encefalite Antirreceptor de N-Metil-D-Aspartato , Encefalopatias , Estado Epiléptico , Humanos , Eletroencefalografia , Convulsões/tratamento farmacológico , Estado Epiléptico/diagnóstico , Encefalite Antirreceptor de N-Metil-D-Aspartato/diagnósticoRESUMO
The study of an organism's response to cerebral ischemia at different levels is essential to understanding the mechanism of the injury and protection. A great interest is devoted to finding the links between quantitative metabolic changes and post-ischemic damage. This work aims to summarize the outcomes of the most studied metabolites in brain tissue-lactate, glutamine, GABA (4-aminobutyric acid), glutamate, and NAA (N-acetyl aspartate)-regarding their biological function in physiological conditions and their role after cerebral ischemia/reperfusion. We focused on ischemic damage and post-ischemic recovery in both experimental-including our results-as well as clinical studies. We discuss the role of blood glucose in view of the diverse impact of hyperglycemia, whether experimentally induced, caused by insulin resistance, or developed as a stress response to the cerebral ischemic event. Additionally, based on our and other studies, we analyze and critically discuss post-ischemic alterations in energy metabolites and the elevation of blood ketone bodies observed in the studies on rodents. To complete the schema, we discuss alterations in blood plasma circulating amino acids after cerebral ischemia. So far, no fundamental brain or blood metabolite(s) has been recognized as a relevant biological marker with the feasibility to determine the post-ischemic outcome or extent of ischemic damage. However, studies from our group on rats subjected to protective ischemic preconditioning showed that these animals did not develop post-ischemic hyperglycemia and manifested a decreased metabolic infringement and faster metabolomic recovery. The metabolomic approach is an additional tool for understanding damaging and/or restorative processes within the affected brain region reflected in the blood to uncover the response of the whole organism via interorgan metabolic communications to the stressful cerebral ischemic challenge.
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Isquemia Encefálica , Hiperglicemia , Ratos , Animais , Isquemia Encefálica/metabolismo , Infarto Cerebral , Encéfalo/metabolismo , Ácido Láctico/metabolismo , Ácido gama-Aminobutírico/metabolismo , Hiperglicemia/metabolismoRESUMO
Historically, periodic EEG patterns were described as any pattern with stereotyped paroxysmal complexes occurring at regular intervals, i.e., the period (T). T is the sum of the duration of the waveform (t1) and, eventually, the duration of the interval between two consecutive waves (t2). The American Clinical Neurophysiology Society introduced the concept of a clearly discernible inter-discharge interval between consecutive waveforms (i.e., t2). As this definition was not applied to what have previously been termed triphasic waves and in some cases of lateralized periodic discharges, we propose reconsideration of terminology that includes historical use of definitions. This will allow the development and usage of the concept for periodic EEG patterns as any runs of stereotyped paroxysmal waveforms separated by nearly identical intervals and prolonged repetitive complexes on the EEG. Prolonged expression means EEG is recorded for a sufficient period of time to prove that the pattern is repetitive, thus resulting in a monomorphic/monotonous pattern. More important than the inter-discharge interval (t2), periodic EEG patterns occur at time regular intervals (T). As a result, periodic EEG activity should be considered along a continuum and not the opposite of rhythmic EEG activity where no interval activity exists between consecutive waveforms.
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Eletroencefalografia , Estado Epiléptico , Humanos , Eletroencefalografia/métodos , Causalidade , Periodicidade , Unidades de Terapia IntensivaRESUMO
OBJECTIVE: The Salzburg criteria for nonconvulsive status epilepticus (NCSE) and the American Clinical Neurophysiology Society (ACNS) Standardized Critical Care EEG Terminology 2021 include a diagnostic trial with intravenous (IV) antiseizure medications (ASMs) to assess electroencephalographic (EEG) and clinical response as a diagnostic criterion for definite NCSE and possible NCSE. However, how to perform this diagnostic test and assessing the EEG and clinical responses have not been operationally defined. METHODS: We performed a Delphi process involving six experts to standardize the diagnostic administration of IV ASM and propose operational criteria for EEG and clinical response. RESULTS: Either benzodiazepines (BZDs) or non-BZD ASMs can be used as first choice for a diagnostic IV ASM trial. However, non-BZDs should be considered in patients who already have impaired alertness or are at risk of respiratory depression. Levetiracetam, valproate, lacosamide, brivaracetam, or (if the only feasible drug) fosphenytoin or phenobarbital were deemed appropriate for a diagnostic IV trial. The starting dose should be approximately two thirds to three quarters of the full loading dose recommended for treatment of status epilepticus, with an additional smaller dose if needed. ASMs should be administered during EEG recording under supervision. A monitoring time of at least 15 min is recommended. If there is no response, a second trial with another non-BDZ or BDZs may be considered. A positive EEG response is defined as the resolution of the ictal-interictal continuum pattern for at least three times the longest previously observed spontaneous interval of resolution (if any), but minimum of one continuous minute. For a clinical response, physicians should use a standardized examination before and after IV ASM administration. We suggest a definite time-locked improvement in a focal deficit or at least one-step improvement on a new dedicated one-domain 10-level NCSE response scale. SIGNIFICANCE: The proposed standardized approach of a diagnostic IV ASM trial further refines the ACNS and Salzburg diagnostic criteria for NCSE.
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Estado Epiléptico , Humanos , Administração Intravenosa , Benzodiazepinas/uso terapêutico , Eletroencefalografia , Fenobarbital/uso terapêutico , Estado Epiléptico/diagnóstico , Estado Epiléptico/tratamento farmacológico , Ensaios Clínicos como AssuntoRESUMO
During aging, heart structure and function gradually deteriorate, which subsequently increases susceptibility to ischemia-reperfusion (IR). Maintenance of Ca2+ homeostasis is critical for cardiac contractility. We used Langendorff's model to monitor the susceptibility of aging (6-, 15-, and 24-month-old) hearts to IR, with a specific focus on Ca2+-handling proteins. IR, but not aging itself, triggered left ventricular changes when the maximum rate of pressure development decreased in 24-month-olds, and the maximum rate of relaxation was most affected in 6-month-old hearts. Aging caused a deprivation of Ca2+-ATPase (SERCA2a), Na+/Ca2+ exchanger, mitochondrial Ca2+ uniporter, and ryanodine receptor contents. IR-induced damage to ryanodine receptor stimulates Ca2+ leakage in 6-month-old hearts and elevated phospholamban (PLN)-to-SERCA2a ratio can slow down Ca2+ reuptake seen at 2-5 µM Ca2+. Total and monomeric PLN mirrored the response of overexpressed SERCA2a after IR in 24-month-old hearts, resulting in stable Ca2+-ATPase activity. Upregulated PLN accelerated inhibition of Ca2+-ATPase activity at low free Ca2+ in 15-month-old after IR, and reduced SERCA2a content subsequently impairs the Ca2+-sequestering capacity. In conclusion, our study suggests that aging is associated with a significant decrease in the abundance and function of Ca2+-handling proteins. However, the IR-induced damage was not increased during aging.
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Background and Objective: Medication management in pregnant women with epilepsy (PWWE) poses challenges, and understanding the effects of metabolic changes on antiseizure medications (ASMs) is important in planning care for PWWE. The possible teratogenic effects and risks of poorly controlled seizures have to be weighed. There are data in the literature on clinical management of ASMs including the effects of drug levels on seizures and factors that predict seizure frequency, but timing and frequency of monitoring and dose adjustment paradigms have not been well studied. Methods: This retrospective study was approved by the Institutional Review Board at Johns Hopkins University. We retrospectively identified adult PWWE evaluated during pregnancy at the Johns Hopkins Bayview Medical Center epilepsy clinic, between January 1, 2007, and January 1, 2021. We reviewed charts for information regarding demographics, medical and epilepsy history, medications, serum drug levels, and dosing paradigms. We assessed risk factors for breakthrough seizures with a focus on frequency and timing of laboratory testing. We calculated the dose-normalized concentration (DNC) for analysis with levetiracetam and lamotrigine, assessing changes in DNC over time by half trimesters, and analyzed DNC and effects on seizures in pregnancy. We also compared preemptive vs clinically based lamotrigine dose adjustments in managing epilepsy in pregnancy. Results: A total of 45 pregnancies in 39 patients were included in this study, 8 generalized, 28 focal epilepsy, and 3 unclassified. 31 PWWE (36 pregnancies) were on lamotrigine and/or levetiracetam, and 14 of these pregnancies experienced breakthrough seizures, 77% in the first trimester. Seizures led to the diagnosis of pregnancy in 5 patients. The DNC for levetiracetam decreased significantly compared with prepregnancy levels by the second half of the first trimester and demonstrated variable but frequently significant or near significant reduction throughout pregnancy. DNC for lamotrigine decreased significantly in the first half of the first trimester and remained significant throughout pregnancy. Age of mother at conception, week of first ASM serum level and number of levels obtained during pregnancy, and epilepsy type were not associated with breakthrough/increase in seizures. The history of drug resistance (p = 0.038) was associated with a higher odds of seizures. In those on lamotrigine, preemptive dose adjustments demonstrated similar results regarding seizure control when compared with clinical-based or laboratory-based dose management (p = 0.531). Discussion: This study demonstrates that frequency and timing of ASM level monitoring may not affect overall seizure outcomes during pregnancy in those on lamotrigine or levetiracetam. Furthermore, one can consider preemptive dose adjustments or a laboratory-based/clinical-based approach in managing lamotrigine as both seem safe and feasible. However, in those with drug-resistant epilepsy before pregnancy, earlier and closer monitoring is warranted given the risk of seizures early during pregnancy. Larger prospective studies are needed to confirm these results.
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BACKGROUND AND OBJECTIVES: To compare specific life stressors and domestic abuse that pregnant women and others with epilepsy (WWE) experience compared with pregnant women and others without epilepsy (WWoE). METHODS: The Pregnancy Risk Assessment Monitoring System (PRAMS) is an annual weighted survey of randomly sampled postpartum women administered by the Centers for Disease Control and Prevention. We used data from the PRAMS from 2012 to 2020 in 13 states to assess the life stressors reported by WWE compared with WWoE. We adjusted the data for maternal age, race, ethnicity, marital status, education, and socioeconomic status (SES; using income, Women, Infants, and Children program [WIC], and Medicaid use). We also examined reported abuse in WWE compared with WWoE. RESULTS: This study included data from 64,951 postpartum women, representing 4,072,189 women through weighted sampling. Of these, 1,140 reported having a diagnosis of epilepsy in the 3 months before their pregnancies (representing 81,021 WWE). WWE experienced a higher number of stressors compared with WWoE. WWE were more likely to have experienced 9 of the 14 stressors asked in the PRAMS questionnaire: severe illness of a close family member, separation or divorce, homelessness, loss of a partner's job, cut in work hours or pay, arguing more than usual with their partner, serving jail time, substance abuse problem in a close contact, and death of a close contact. After adjusting for demographics (age, race, and SES), epilepsy was still associated with a higher number of stressors in pregnant women. Other factors associated with stressors were younger age, Indigenous or mixed race, non-Hispanic ethnicity, lower income, and WIC or Medicaid use. Those who were married were less likely to report stressors. WWE were also more likely to report abuse before or during their pregnancies. DISCUSSION: Although managing stress is important in both epilepsy and pregnancy, WWE experience more stressors than do WWoE. After adjusting for maternal age, race, and SES, this increase in stressors persisted. Women who were younger, with lower income, on WIC or Medicaid, or not married were also more likely to experience life stressors. Alarmingly, reported abuse was also higher in WWE compared with WWoE. Attention from clinicians and support services for WWE are needed to optimize good pregnancy outcomes.
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Epilepsia , Resultado da Gravidez , Lactente , Estados Unidos , Gravidez , Feminino , Humanos , Criança , Epilepsia/tratamento farmacológico , Medição de Risco , Inquéritos e Questionários , Idade Materna , Anticonvulsivantes/uso terapêuticoRESUMO
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.
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Epilepsia , Convulsões , Humanos , Reprodutibilidade dos Testes , Mortalidade Hospitalar , Eletroencefalografia/métodos , Epilepsia/diagnósticoRESUMO
The role of the cytochrome P450 1A2 (CYP1A2) rs2472299, rs2470890 and rs11072508 polymorphisms in prostate cancer risk, disease progression and tumour development remains unclear. The potential associations of these three CYP1A2 polymorphisms and haplotypes with prostate cancer susceptibility and its clinicopathological characteristics were therefore investigated. The present case-control study consisted of 522 patients with prostate cancer and 554 healthy controls. High-resolution melting analysis was used to determine the CYP1A2 polymorphisms. No significant association in prostate cancer risk was seen for CYP1A2 rs2472299 and rs11072508. However, a significantly decreased risk of prostate cancer was found for CYP1A2 rs2470890 [odds ratio (OR), 0.67; P=0.02] in the recessive model. After analysis of the associations of clinical status and these three CYP1A2 polymorphisms, the CYP1A2 rs2470890 and rs11072508 polymorphisms showed a positive association with a higher Gleason score (rs2470890 OR, 1.36, P=0.04 in the allelic model; rs11072508 OR, 1.37, P=0.04 in the allelic model and OR, 1.60, P=0.03 in the dominant model). All three polymorphisms showed a significant positive association with pathological T stage in the additive, allelic and dominant genetic models (P<0.05). Haplotype analysis revealed that the most common haplotypes 'GTT' and 'ACC' were significantly associated with pathological T stages 3 and 4 (OR, 0.62; P=0.02 and OR, 1.54; P=0.03, respectively). A significant association was found between the 'GTT' haplotype and the Gleason score (OR, 0.71; P=0.03). In conclusion, these CYP1A2 polymorphisms and haplotypes have the potential to predict prostate cancer disease progression.
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PURPOSE: Electroencephalogram is used for prognostication and diagnosis in critically ill patients and is vital in developing clinical management algorithms. Unique waveforms on EEG may distinguish neurological disorders and define a potential for seizures. To better characterize zeta waves, we sought to define their electroclinical spectrum. METHODS: We performed a systematic review using MEDLINE, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Review [through Ovid], Scopus, Science Citation Index Expanded and Emerging Sources Citation Index [through the Web of Science], and Epistemonikos. Grey literature resources were searched. RESULTS: Five hundred thirty-seven articles were identified. After excluding duplicates and reviewing titles, abstracts, and bodies and bibliographies of articles, four studies reported 64 cases describing data from patients with zeta waves, with a prevalence of 3 to 4%. Various and often incomplete clinical, neuroimaging, and EEG data were available. 57 patients (89.1%) had a focal cerebral lesion concordant with the location of zeta waves on EEG. 26 patients (40.6%) had clinical seizures, all but one being focal onset. Thirteen patients (20%) had epileptiform activity on EEG. Typically, zeta waves were located in the frontal head regions, often with generalized, frontal, predominant, rhythmic delta activity and associated with focal EEG suppression. CONCLUSIONS: Zeta waves frequently represent an underlying focal structural lesion. Their presence suggests a heightened risk for seizures. The small number of retrospective cases series in the literature reporting zeta waves might be an underrepresentation. We suggest a need for prospective studies of cEEG in critically ill patients to determine their clinical significance.
Assuntos
Estado Terminal , Convulsões , Humanos , Estudos Retrospectivos , Estudos Prospectivos , Convulsões/diagnóstico , EletroencefalografiaRESUMO
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.
Assuntos
Eletroencefalografia , Convulsões , Humanos , Feminino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Eletroencefalografia/métodos , Encéfalo , Estado TerminalRESUMO
SUMMARY: Prognostication following cardiorespiratory arrest relies on the neurological examination, which is supported by neuroimaging and neurophysiological testing. Acute posthypoxic myoclonus (PHM) is a clinical entity that has prognostic significance and historically has been considered an indicator of poor outcome, but this is not invariably the case. "Malignant" and more "benign" forms of acute PHM have been described and differentiating them is key in understanding their meaning in prognosis. Neurophysiological tests, electroencephalogram in particular, and clinical phenotyping are crucial in defining subtypes of acute PHM. This review describes the neurophysiological and phenotypic markers of malignant and benign forms of acute PHM, a clinical approach to evaluating acute PHM following cardiorespiratory arrest in determining prognosis, and gaps in our understanding of acute PHM that require further study.