Incidence and predictors of posttraumatic epilepsy and cognitive impairment in patients with traumatic brain injury: A retrospective cohort study in Malaysia.

OBJECTIVE: Posttraumatic epilepsy (PTE) significantly impacts morbidity and mortality, yet local PTE data remain scarce. In addition, there is a lack of evidence on cognitive comorbidity in individuals with PTE in the literature. We sought to identify potential PTE predictors and evaluate cognitive comorbidity in patients with PTE. METHODS: A 2-year retrospective cohort study was employed, in which adults with a history of admission for traumatic brain injury (TBI) in 2019 and 2020 were contacted. Three hundred one individuals agreed to participate, with a median follow-up time of 30.75 months. The development of epilepsy was ascertained using a validated tool and confirmed by our neurologists during visits. Clinical psychologists assessed the patients' cognitive performance. RESULTS: The 2-year cumulative incidence of PTE was 9.3% (95% confidence interval [CI] 5.9-12.7). The significant predictors of PTE were identified as a previous history of brain injury [hazard ratio [HR] 4.025, p = .021], and intraparenchymal hemorrhage (HR: 2.291, p = .036), after adjusting for other confounders. TBI patients with PTE performed significantly worse on the total ACE-III cognitive test (73.5 vs 87.0, p = .018), CTMT (27.5 vs 33.0, p = .044), and PSI (74.0 vs 86.0, p = .006) than TBI patients without PTE. A significantly higher percentage of individuals in the PTE group had cognitive impairment, compared to the non-PTE group based on ACE-III (53.6% vs 46.4%, p = .001) and PSI (70% vs 31.7%, p = .005) scores at 2 years post-TBI follow-up. SIGNIFICANCE: This study emphasizes the link between TBI and PTE and the chance of developing cognitive impairment in the future. Clinicians can target interventions to prevent PTE by identifying specific predictors, which helps them make care decisions and develop therapies to improve patients' quality of life.

Electroconvulsive Therapy in Refractory and Super-Refractory Status Epilepticus in Adults: A Scoping Review.

BACKGROUND: Electroconvulsive therapy (ECT) has been suggested as a treatment option for refractory status epilepticus (RSE) and super-refractory status epilepticus (SRSE). OBJECTIVE: The objective of this scoping review was to conduct an extensive literature review on the role of ECT as a treatment option for RSE and SRSE. METHODS: We searched Ovid MEDLINE and Scopus for journal articles from database inception until February 2024. Articles were then selected based on predetermined inclusion and exclusion criteria. RESULTS: We identified five retrospective case series with 28 adult patients receiving ECT for RSE or SRSE. ECT was administered within 3-70 days (mean 20 days) after the development of SE, and the mean number of ECT courses ranged from 1 to 12 sessions for each patient. ECT was administered in fixed or titrated doses. A total of 20 out of 28 patients (71%) showed clinical improvement, with two (7%) having complete cessation of seizures. It is essential to note that given the lack of control, there could be overreporting of clinical improvement in these studies. 11 patients (39%) were reported as deceased due to causes that were not directly related to ECT treatment. Four patients (14%) reported adverse effects of ECT, including memory, concentration, and/or cognitive impairment. CONCLUSIONS: There are level-4 Oxford Centre for Evidence-Based Medicine evidence and low-level Grading of Recommendations Assessment Development and Education evidence that suggest ECT as a treatment option for RSE and SRSE. In light of the limitations of the existing evidence, clinicians should carefully consider individual patients' clinical contexts when deciding on the appropriateness of ECT as a treatment option. Further research, including prospective studies with controlled designs, is needed to elucidate the efficacy, safety, and optimal regime of ECT in the management of RSE and SRSE.

Prevalence and predictors of vitamin D deficiency among adults with epilepsy: A cross-sectional study.

BACKGROUND: Vitamin D deficiency among adult people with epilepsy (PWE) is scarcely studied, despite its essential role in bone health and maintaining homeostasis. Several studies have studied the relationship between factors related to epilepsy and vitamin D metabolism. We aim to investigate this in our multi-ethnic society. METHODS: This was a single-center cross-sectional study. We recruited 159 participants diagnosed with epilepsy on antiseizure medications (ASMs). We included those aged 18 years and above, excluding patients with long-term medical conditions that would affect vitamin D metabolism. Sociodemographic data and details of epilepsy were collated. Venous sampling was performed to analyze the levels of albumin-corrected calcium, phosphate, alkaline phosphatase, and 25-hydroxyvitamin D3 [25(OH)D]. Serum 25(OH)D level is defined as deficient (<20 ng/ml), insufficient (20-29 ng/ml), and sufficient (≥30 ng/ml). RESULTS: The study reported that 73 (45.9%) participants had vitamin D deficiency, 38 (23.9%) had vitamin D insufficiency, and 48 (30.2%) patients had sufficient vitamin D levels. The predictors identified were PWE aged 18 to 44 years old (p = 0.001), female gender (OR 3.396, p = 0.002), and ethnicity (p < 0.001), specifically Malay and Chinese. However, no significant association was identified between types of ASMs, serum calcium, or the prevalence of vitamin D deficiency. CONCLUSION: Vitamin D deficiency among PWE is prevalent in our local population, suggesting that regular screening should be considered for those at risk. Early identification would allow intervention to reduce the risk of future complications.

Characteristics of Perfusion Computed Tomography Imaging in Patients with Seizures Mimicking Acute Stroke.

INTRODUCTION: Seizures as acute stroke mimics are a diagnostic challenge. OBJECTIVE: The aim of the study was to characterize the perfusion patterns on perfusion computed tomography (PCT) in patients with seizures masquerading as acute stroke. METHODS: We conducted a study on patients with acute seizures as stroke mimics. The inclusion criteria for this study were patients (1) initially presenting with stroke-like symptoms but finally diagnosed to have seizures and (2) with PCT performed within 72 h of seizures. The PCT of seizure patients (n = 27) was compared with that of revascularized stroke patients (n = 20) as the control group. RESULTS: Among the 27 patients with seizures as stroke mimics, 70.4% (n = 19) showed characteristic PCT findings compared with the revascularized stroke patients, which were as follows: (1) multi-territorial cortical hyperperfusion {(73.7% [14/19] vs. 0% [0/20], p = 0.002), sensitivity of 73.7%, negative predictive value (NPV) of 80%}, (2) involvement of the ipsilateral thalamus {(57.9% [11/19] vs. 0% [0/20], p = 0.007), sensitivity of 57.9%, NPV of 71.4%}, and (3) reduced perfusion time {(84.2% [16/19] vs. 0% [0/20], p = 0.001), sensitivity of 84.2%, NPV of 87%}. These 3 findings had 100% specificity and positive predictive value in predicting patients with acute seizures in comparison with reperfused stroke patients. Older age was strongly associated with abnormal perfusion changes (p = 0.038), with a mean age of 66.8 ± 14.5 years versus 49.2 ± 27.4 years (in seizure patients with normal perfusion scan). CONCLUSIONS: PCT is a reliable tool to differentiate acute seizures from acute stroke in the emergency setting.

A rare but treatable cause of recurrent chest pain - Ictal chest pain.

BACKGROUND: Chest pain as the primary manifestation of epilepsy is extremely rare and has only been reported once to date. CASE PRESENTATION: We herein describe a 47-year-old woman with recurrent chest pain for 3 years. The cause of her chest pain remained elusive despite extensive investigations including comprehensive cardiac work-up. She was referred to the neurology clinic for one episode of confusion. Video-electroencephalographic monitoring detected unequivocal ictal changes during her habitual chest pain events. She has remained chest pain (seizure) free with a single antiseizure drug. CONCLUSIONS: This case underlines the importance of epilepsy as a rare yet treatable cause of recurrent chest pain. Further studies are required to determine the pathophysiology of ictal chest pain.

Feasibility of cardiac-based seizure detection and prediction: A systematic review of non-invasive wearable sensor-based studies.

A reliable seizure detection or prediction device can potentially reduce the morbidity and mortality associated with epileptic seizures. Previous findings indicating alterations in cardiac activity during seizures suggest the usefulness of cardiac parameters for seizure detection or prediction. This study aims to examine available studies on seizure detection and prediction based on cardiac parameters using non-invasive wearable devices. The Embase, PubMed, and Scopus databases were used to systematically search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Human studies that evaluated seizure detection or prediction based on cardiac parameters collected using wearable devices were included. The QUADAS-2 tool and proposed standards for validation for seizure detection devices were used for quality assessment. Twenty-four articles were identified and included in the analysis. Twenty studies evaluated seizure detection algorithms, and four studies focused on seizure prediction. Most studies used either a wrist-worn or chest-worn device for data acquisition. Among the seizure detection studies, cardiac parameters utilized for the algorithms mainly included heart rate (HR) (n = 11) or a combination of HR and heart rate variability (HRV) (n = 6). HR-based seizure detection studies collectively reported a sensitivity range of 56%-100% and a false alarm rate (FAR) of 0.02-8/h, with most studies performing retrospective validation of the algorithms. Three of the seizure prediction studies retrospectively validated multimodal algorithms, combining cardiac features with other physiological signals. Only one study prospectively validated their seizure prediction algorithm using HRV extracted from ECG data collected from a custom wearable device. These studies have demonstrated the feasibility of using cardiac parameters for seizure detection and prediction with wearable devices, with varying algorithmic performance. Many studies are in the proof-of-principle stage, and evidence for real-time detection or prediction is currently limited. Future studies should prioritize further refinement of the algorithm performance with prospective validation using large-scale longitudinal data. PLAIN LANGUAGE SUMMARY: This systematic review highlights the potential use of wearable devices, like wristbands, for detecting and predicting seizures via the measurement of heart activity. By reviewing 24 articles, it was found that most studies focused on using heart rate and changes in heart rate for seizure detection. There was a lack of studies looking at seizure prediction. The results were promising but most studies were not conducted in real-time. Therefore, more real-time studies are needed to verify the usage of heart activity-related wearable devices to detect seizures and even predict them, which will be beneficial to people with epilepsy.

Electroencephalography as a tool for assessing delirium in hospitalized patients: A single-center tertiary hospital experience.

Background: Delirium is a prevalent yet underdiagnosed disorder characterized by acute cognitive impairment. Various screening tools are available, including the Confusion Assessment Method (CAM) and 4 A's test (4AT). However, the results of these assessments may vary among raters. Therefore, we investigated the objective use of electroencephalography (EEG) in delirium and its clinical associations and predictive value. Method: This cross-sectional observational study was conducted at Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan, Malaysia, from April 2021 to April 2023. This study included patients aged ≥18 years with a preliminary diagnosis of delirium. Demographic and clinical data were collected along with EEG recordings evaluated by certified neurologists to classify abnormalities and compare the associated factors between patients with delirium with or without EEG abnormalities. Results: One hundred and twenty patients were recruited, with 80.0% displaying EEG abnormalities, mostly generalized slowing (moderate to severe) and primarily generalized slowing (mild to severe), and were characterized by theta activity. Age was significantly associated with EEG abnormalities, with patients aged 75 and older demonstrating the highest incidence (88.2%). The CAM scores were strongly correlated with EEG abnormalities (r = 0.639, P < 0.001) and was a predictor of EEG abnormalities (P < 0.012), indicating that EEG can complement clinical assessments for delirium. The Richmond Agitation and Sedation Scale (RASS) scores (r = -0.452, P < 0.001) and Barthel index (BI) (r = -0.582, P < 0.001) were negatively correlated with EEG abnormalities. Additionally, a longer hospitalization duration was associated with EEG abnormalities (r = 0.250, P = 0.006) and emerged as a predictor of such changes (P = 0.030). Conclusion: EEG abnormalities are prevalent in patients with delirium, particularly in elderly patients. CAM scores and the duration of hospitalization are valuable predictors of EEG abnormalities. EEG can be an objective tool for enhancing delirium diagnosis and prognosis, thereby facilitating timely interventions.

Why was the study done? Confusion is frequently observed among patients presenting with various medical issues. There are several tests available to assist in assessment of these patients to see if the symptoms present constitute delirium. However, there may be occasions where identifying delirium is difficult despite the tools available. Electroencephalography (EEG) may be another option to assist medical personnel in diagnosing delirium. In this study, we examine the use of EEG in identification of delirium and its clinical associations. What did the researchers do? Our team studied the use of EEG in patients admitted for various medical issues with symptoms suggestive of delirium over a 2-year period. We collected relevant clinical data and performed EEG for each participant. What did the researchers find? A total of 120 participants were involved in the study. We observe abnormal EEG findings in 80% of patients with the majority showing generalized slowing. The factors associated with EEG abnormalities are advancing age, positive Confusion Assessment Method (CAM), and duration of hospitalization. What do the findings mean? As the service is not widely available, it would not be practical to substitute existing clinical assessment tools with EEG. However, we cannot discount the importance of identifying delirium due to its association with poor clinical outcomes. Therefore, for centers that may perform EEG, it may be used as an adjunct in diagnosing delirium should any doubts arise.

Brain waves spectral analysis of human responses to odorous and non-odorous substances: a preliminary study.

OBJECTIVE: The aim of this study was to identify the potential electrophysiological biomarkers of human responses by comparing the electroencephalogram brain wave changes towards lavender versus normal saline in a healthy human population. METHOD: This study included a total of 44 participants without subjective olfactory disturbances. Lavender and normal saline were used as the olfactory stimulant and control. Electroencephalogram was recorded and power spectra were analysed by the spectral analysis for each alpha, beta, delta, theta and gamma bandwidth frequency upon exposure to lavender and normal saline independently. RESULTS: The oscillatory brain activities in response to the olfactory stimulant indicated that the lavender smell decreased the beta activity in the left frontal (F7 electrode) and central region (C3 electrode) with a reduction in the gamma activity in the right parietal region (P4 electrode) (p < 0.05). CONCLUSION: Olfactory stimulants result in changes of electrical brain activities in different brain regions, as evidenced by the topographical brain map and spectra analysis of each brain wave.

Risk Factors for Post-Stroke Seizures in a Tertiary Care Center: A Case-Control Study.

Purpose: Stroke is the second leading cause of global deaths. Post-stroke seizures (PSS) can lead to lasting complications, such as prolonged hospitalizations, increased disability rates, and higher mortality. Our study investigates the associated factors that contribute to post-stroke seizures in patients at a local tertiary hospital. Patients and Methods: We designed a case-control study where patients admitted with PSS were recruited with consent. Controls admitted for stroke without seizure were then included. Suitability based on exclusion criteria was ensured before recording their sociodemographic and clinical data. An EEG was performed and read by two certified neurologists before the data was analyzed. Results: We recruited 180 participants, 90 cases and 90 matched controls. Gender (p=0.013), race (p=0.015), dyslipidemia (p<0.001), prior stroke (p<0.031), large artery atherosclerosis (p<0.001), small vessel occlusions (p<0.001), blood pressure on presentation (p<0.028) and thrombolysis administration (p<0.029) were significantly associated with the occurrence of PSS. An increase in odds of PSS was observed in the male gender (1.974), dyslipidemia (3.480), small vessel occlusions (4.578), and in participants with epileptiform changes on EEG (3.630). Conversely, lower odds of PSS were seen in participants with high blood pressure on presentation (0.505), large artery atherosclerosis (0.266), and those who underwent thrombolysis (0.319). Conclusion: This study emphasized that identifying post-stroke seizures may be aided by EEGs and recognizing at-risk groups, which include males of Chinese descent in Asia, dyslipidemia, small vessel occlusions, those with low to normal blood pressure on presentation, and epileptiform changes in EEGs.

The research aims to establish the risk factors associated with post-stroke seizures in an Asian population and their similarity to the Western literature. Our findings highlight the critical risk factors to identify in at-risk patients, which may prompt changes in guidelines in future to enhance patient outcomes and improve the quality of care.

Spectrum of Ictal-Interictal Continuum: The Significance of 2HELPS2B Score and Background Suppression.

PURPOSE: The aims of this study were to identify (1) the spectrum of ictal-interictal continuum (IIC) using the two dimensions of 2HELPS2B score and background suppression and (2) the response to subsequent anti-seizure drugs depends on the spectrum of IIC. METHODS: The study prospectively enrolled 62 patients with IIC on EEG. The diagnosis of nonconvulsive status epilepticus was attempted with Salzburg criteria as well as clinical and neuroimaging data. IICs were dichotomized into patients with nonconvulsive status epilepticus and coma-IIC. The 2HELPS2B score was evaluated as the original proposal. The suppression ratio was analyzed with Persyst software. RESULTS: Forty-seven cases (75.8%) were nonconvulsive status epilepticus-IIC and 15 cases (24.2%) were coma-IIC. Multivariate analysis revealed that the 2HELPS2B score was the only significant variable dichotomizing the spectrum of IIC (odds ratio, 3.0; 95% confidence interval, 1.06-8.6; P = 0.03 for nonconvulsive status epilepticus-IIC). In addition, the suppression ratio was significantly negatively correlated with 2HELPS2B scores (Spearman coefficient = -0.37, P = 0.004 for left hemisphere and Spearman coefficient = -0.3, P = 0.02 for right hemisphere). Furthermore, patients with higher 2HELPS2B score (74% [14/19] in ≥2 points vs. 44% [14/32] in <2 points, P = 0.03 by χ 2 test) and lower suppression ratio (62% [23/37] in ≤2.18 vs. 35% [6/17] in >2.18, P = 0.06 by χ 2 test) seemed to be more responsive to subsequent anti-seizure drug. CONCLUSIONS: The 2HELPS2B score and background suppression can be used to distinguish the spectrum of IIC and thereby predict the response to subsequent anti-seizure drug.

Safety and adverse events following COVID-19 vaccination among people with epilepsy: A cross-sectional study.

OBJECTIVE: Epilepsy is a non-communicable disease costing a massive burden globally. It is known that there is increased prevalence of morbidity and mortality following COVID-19 infection among people with epilepsy (PWE). However, there is limited information about the adverse events following COVID-19 immunization among PWE. Hence, this study aimed to assess the safety and adverse events following immunization (AEFI) of various COVID-19 vaccines among PWE from our centre, focusing on neurological AEFI. METHODS: This cross-sectional study recruited 120 adult PWE from the Neurology Clinic of the Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Consent-taking was conducted via synchronous or asynchronous approaches, followed by a phone call interview session. The interview collected socio-demographic information, epilepsy-related variables, and vaccination-related variables. Univariate analysis and multiple logistic regression analysis were done to confirm factors associated with the AEFI of COVID-19 vaccination. RESULTS: Among all types of COVID-19 vaccines, most of the PWE received the Cominarty® COVID-19 vaccination (52.5%). Overall, local AEFI was the quickest to develop, with an average onset within a day. PWE with normal body mass index (BMI) had a higher risk of developing both local and systemic AEFI compared to those underweight and obese PWE (OR: 15.09, 95% CI 1.70-134.28, P = 0.02). SIGNIFICANCE: COVID-19 vaccines are safe for PWE. AEFI among PWE are similar to those of the general population following COVID-19 vaccination. Therefore, clinicians should encourage PWE to take COVID-19 vaccines.

The prevalence and predictors of poor sleep quality and excessive daytime sleepiness in epilepsy: A single tertiary centre experience in Malaysia.

BACKGROUND AND OBJECTIVE: People with epilepsy frequently encounter sleep disruptions that can stem from a variety of complex factors. Epilepsy-related sleep disturbance can lead to reduced quality of life and excessive daytime hypersomnolence. Identification of sleep disturbances may help in the overall management of epilepsy patients. This study was conducted to determine the prevalence and predictors of poor sleep quality and daytime sleepiness in epilepsy. METHODS: A cross-sectional study on 284 epilepsy patients was performed in a local tertiary centre. The demographic and clinical epilepsy data were collected. The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires were utilised to determine the quality of life and daytime hypersomnolence of epilepsy patients, respectively. RESULTS: Poor sleep quality was reported in 78 (27.5%) patients while daytime hypersomnolence was present in 17 (6%) patients. The predictors of poor sleep quality include structural causes (OR = 2.749; 95% CI: 1.436, 5.264, p = 0.002), generalised seizures (OR = 1.959, 95% CI: 1.04, 3.689, p = 0.037), and antiseizure medications such as Carbamazepine (OR = 2.34; 95% CI: 1.095, 5.001, p = 0.028) and Topiramate (OR 2.487; 95% CI: 1.028, 6.014, p = 0.043). Females are 3.797 times more likely score higher in ESS assessment (OR 3.797; 95% CI: 1.064, 13.555 p = 0.04). DISCUSSION: Sleep disturbances frequently coexist with epilepsy. Patients should be actively evaluated using the PSQI and ESS questionnaires. It is imperative to identify the key factors that lead to reduced sleep quality and heightened daytime sleepiness in patients with epilepsy, as this is essential to properly manage their condition.

Qualitative electroencephalogram and its predictors in the diagnosis of stroke.

Introduction: Stroke is a typical medical emergency that carries significant disability and morbidity. The diagnosis of stroke relies predominantly on the use of neuroimaging. Accurate diagnosis is pertinent for management decisions of thrombolysis and/or thrombectomy. Early identification of stroke using electroencephalogram (EEG) in the clinical assessment of stroke has been underutilized. This study was conducted to determine the relevance of EEG and its predictors with the clinical and stroke features. Methods: A cross-sectional study was carried out where routine EEG assessment was performed in 206 consecutive acute stroke patients without seizures. The demographic data and clinical stroke assessment were collated using the National Institutes of Health Stroke Scale (NIHSS) score with neuroimaging. Associations between EEG abnormalities and clinical features, stroke characteristics, and NIHSS scores were evaluated. Results: The mean age of the study population was 64.32 ± 12 years old, with 57.28% consisting of men. The median NIHSS score on admission was 6 (IQR 3-13). EEG was abnormal in more than half of the patients (106, 51.5%), which consisted of focal slowing (58, 28.2%) followed by generalized slowing (39, 18.9%) and epileptiform changes (9, 4.4%). NIHSS score was significantly associated with focal slowing (13 vs. 5, p < 0.05). Type of stroke and imaging characteristics were significantly associated with EEG abnormalities (p < 0.05). For every increment in NIHSS score, there are 1.08 times likely for focal slowing (OR 1.089; 95% CI 1.033, 1.147, p = 0.002). Anterior circulation stroke has 3.6 times more likely to have abnormal EEG (OR 3.628; 95% CI 1.615, 8.150, p = 0.002) and 4.55 times higher to exhibit focal slowing (OR 4.554; 95% CI 1.922, 10.789, p = 0.01). Conclusion: The type of stroke and imaging characteristics are associated with EEG abnormalities. Predictors of focal EEG slowing are NIHSS score and anterior circulation stroke. The study emphasized that EEG is a simple yet feasible investigational tool, and further plans for advancing stroke evaluation should consider the inclusion of this functional modality.

Anxiety among hospitalized COVID-19 patients: a case-control study from a tertiary teaching hospital in Malaysia.

Introduction: Anxiety has been increasingly recognized as part of the psychosocial health issues in COVID-19 patients. However, the impact of this topic may be underestimated in low- and middle-income countries. This study aimed to estimate the prevalence of and risk factors of anxiety in COVID-19 patients compared to controls in a local tertiary teaching hospital in Malaysia. Methods: In this case-control study, we analyzed data on adult patients aged 18 years and above hospitalized for COVID-19 infection with matched hospitalized controls. The demographic, clinical data and anxiety measures using the Generalized Anxiety Disorder-7 questionnaire were analyzed using univariate and multivariate analysis. Results: 86.6% in the COVID-19 group had anxiety, significantly higher than 13.4% in the control group (p = 0.001). The COVID-19 group was significantly associated with the GAD-7 severity (p = 0.001). The number of COVID-19 patients in the mild, moderate, and severe anxiety groups was 48 (84.2%), 37 (86%), and 18 (94.7%), respectively. Multiple logistic regression showed significant predictors for anxiety, including COVID-19 diagnosis and neurological symptoms. Anxiety was found 36.92 times higher in the patients with COVID-19 compared to those without COVID-19 (OR 36.92;95% CI 17.09, 79.78, p = 0.001). Patients with neurological symptoms were at risk of having anxiety (OR 2.94; 95% CI 1.03, 8.41, p = 0.044). Discussion: COVID-19 patients experience a significant disruption in psychosocial functioning due to hospitalization. The burden of anxiety is notably high, compounded by a diagnosis of COVID-19 itself and neurological symptomatology. Early psychiatric referrals are warranted for patients at risk of developing anxiety symptoms.

Management of status epilepticus in Malaysia: A national survey of current practice and treatment gap.

INTRODUCTION: Early and effective treatment is fundamental in status epilepticus (SE) management. At the initiative of the Epilepsy Council of Malaysia, this study aimed to determine the treatment gap in SE across different healthcare settings in Malaysia. METHODS: A web-based survey was sent to clinicians involved in the management of SE, across all states and at all levels of healthcare services. RESULTS: A total of 158 responses were received from 104 health facilities, including 23 tertiary government hospitals (95.8% of all government tertiary hospitals in Malaysia), 4 (80.0%) universities, 14 (6.7%) private, 15 (11.5%) district hospitals and 21 clinics. Intravenous (IV) diazepam was available in 14 (93.3%) district and 33 (80.5%) tertiary hospitals for prehospital management. Non-IV benzodiazepine (rectal diazepam and intramuscular midazolam) was not widely available in prehospital services (75.8% and 51.5%). Intramuscular midazolam was underutilised (60.0% in district and 65.9% in tertiary hospitals). IV sodium valproate and levetiracetam were only available in 66.7% and 53.3% of the district hospitals, respectively. Electroencephalogram (EEG) services were available in only 26.7% of the district hospitals. Non-pharmacological therapies such as ketogenic diet, electroconvulsive therapy, and therapeutic hypothermia were not available in most district and tertiary hospitals for refractory and super-refractory SE. CONCLUSIONS: We identified several gaps in the current practice of SE management, including limited availability and underutilization of non-IV midazolam in prehospital services, underutilization of non-IV midazolam and other second-line ASMs, and lack of EEG monitoring in district hospitals and limited treatment options for refractory and super-refractory SE in tertiary hospitals.

Neurological manifestations in SARS-CoV-2 infection: A single-center cross-sectional study in Malaysia.

Background: Neurological involvement associated with SARS-CoV-2 infection has been reported from different regions of the world. However, data from South East Asia are scarce. We described the neurological manifestations and their associated factors among the hospitalized COVID-19 patients from an academic tertiary hospital in Malaysia. Methods: A cross-sectional observational study of hospitalized COVID-19 patients was conducted. The neurological manifestations were divided into the self-reported central nervous system (CNS) symptoms, stroke associated symptoms, symptoms of encephalitis or encephalopathy and specific neurological complications. Multiple logistic regression was performed using demographic and clinical variables to determine the factors associated with outcome. Results: Of 156 hospitalized COVID-19 patients with mean age of 55.88 ± 6.11 (SD) years, 23.7% developed neurological complications, which included stroke, encephalitis and encephalopathy. Patients with neurological complications were more likely to have diabetes mellitus (p = 0.033), symptoms of stroke [limb weakness (p < 0.001), slurred speech (p < 0.001)]; and encephalitis or encephalopathy [confusion (p < 0.001), forgetfulness (p = 0.006) and seizure (p = 0.019)]. Unvaccinated patients had a 4.25-fold increased risk of having neurological complications (adjusted OR = 4.25; 95% CI: 1.02, 17.71, p = 0.047). Anosmia and dysgeusia were less associated with neurological complications (adjusted OR = 0.22; 95% CI: 0.05, 0.96, p = 0.044). The odds of neurological complications were increased by 18% in patients with leukocytosis (adjusted OR = 1.18, 95% CI: 1.003, p = 0.0460). Conclusions: Stroke, encephalitis and encephalopathy were the common neurological complications from our study. Diabetes mellitus, presence of symptoms of stroke, symptoms of encephalitis or encephalopathy, leukocytosis, and being unvaccinated against COVID-19 were the associated risk factors of developing neurological complications.