The prevalence, characteristics and outcome of seizure in tuberculous meningitis

The Spectrum of Intracranial Arteriopathies and Ischemic Strokes in Pediatric Tubercular Meningitis: A Tricentric Study From Eastern India

INTRODUCTION

Addressing the need to uniformly classify arteriopathies among patients with arterial ischemic stroke (AIS) due to tubercular meningitis (TBM), we used the Childhood AIS Standardised Classification and Diagnostic Evaluation (CASCADE) criteria.

METHODS

This tri-centric prospective study included children aged 0.5-12 years with TBM and AIS. Magnetic resonance angiographies (MRAs) were done during admission and repeated 3 and 12 months after discharge. Arteriopathies were classified according to the primary CASCADE criteria. We used the modified Pediatric Alberta Stroke Programme Early Computed Tomography Score as an ordinal measure of infarct volume. The severity of arteriopathies was graded using the focal cerebral arteriopathy severity score (FCASS). The final outcomes were measured at the 12-month follow-up visit using the Pediatric Stroke Outcome Measure (PSOM).

RESULTS

Out of 55 patients, 64% had MRA-evidenced arteriopathies and 84% had multiple infarcts. The middle cerebral (46%) and internal carotid arteries (22%) were most commonly affected. The basal ganglia (70%) and the cerebral cortex (61%) were most commonly infarcted. CASCADE categories included 3b (40%), 1d (38%), 2b (16%), 2c (5%), progressive (32%), and stable (44%) arteriopathies. Younger age, hypertrophic pachymeningitis, cortical infarcts, recurrent strokes, progressive arteriopathies, EEG abnormalities, and mortality were significantly higher among patients with MRA-proven arteriopathies. Patients with progressive arteriopathies had a significantly higher prevalence of hypertrophic pachymeningitis, cortical infarcts, and recurrent strokes. FCASS correlated positively with outcomes measured by the Pediatric Stroke Outcome Measure and modified Pediatric Alberta Stroke Programme Early Computed Tomography Score.

CONCLUSION

The CASCADE classification clarified the arteriopathy patterns, enabling us to correlate them with the characteristics of the infarcts. FCASS is useful to grade the arteriopathy severity and progression in TBM.

An overview of machine learning methods in enabling IoMT-based epileptic seizure detection

The healthcare industry is rapidly automating, in large part because of the Internet of Things (IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of Medical Things (IoMT). Data collecting and processing are the fundamental components of all IoMT applications. Machine learning (ML) algorithms must be included into IoMT immediately due to the vast quantity of data involved in healthcare and the value that precise forecasts have. In today's world, together, IoMT, cloud services, and ML techniques have become effective tools for solving many problems in the healthcare sector, such as epileptic seizure monitoring and detection. One of the biggest hazards to people's lives is epilepsy, a lethal neurological condition that has become a global issue. To prevent the deaths of thousands of epileptic patients each year, there is a critical necessity for an effective method for detecting epileptic seizures at their earliest stage. Numerous medical procedures, including epileptic monitoring, diagnosis, and other procedures, may be carried out remotely with the use of IoMT, which will reduce healthcare expenses and improve services. This article seeks to act as both a collection and a review of the different cutting-edge ML applications for epilepsy detection that are presently being combined with IoMT.

Seizures and epilepsy associated with central nervous system tuberculosis

Central nervous system (CNS) tuberculosis is a life-threatening condition that usually presents with seizures, particularly in children and HIV-infected patients. Tuberculous meningitis (TBM) and tuberculomas are the two forms of CNS tuberculosis that can present with seizures. Seizures usually resolve after successful treatment of the underlying infection. However, the success of the treatment is usually based on an early diagnosis. Delay in the treatment of CNS tuberculosis increases the risk of its associated complications, such as stroke. This would lead to the development of epilepsy. Early seizures may be related to meningeal irritation and cerebral edema, whereas late seizures are often associated with structural brain lesions that generally require more advanced and prolonged treatment. Risk factors associated with the development of epilepsy include young age, refractory seizures, tuberculoma, cortical involvement, epileptiform discharges, and residual lesions. Treatment of CNS tuberculosis is based on early initiation of appropriate anti-tuberculous drugs, antiseizure medications, and correction of associated predisposing factors. Finally, further research into the mechanisms of seizures and the development of epilepsy in CNS tuberculosis could help improve management of these conditions.

Nonconvulsive status epilepticus as an unusual presentation of tuberculous meningoencephalitis: A case report

We describe a 50-year-old woman who was recently diagnosed with tuberculosis, with acute alteration in mental status. EEG showed nonconvulsive status epilepticus features. Brain MRI revealed multiple ring-enhancing lesions. She responded well to treatment for both status epilepticus and tuberculosis. Her level of consciousness improved and she became fully aware.

Comparison of Seizure Characteristics and Recurrence Rates in Children with Viable Parenchymal Neurocysticercosis and Tuberculoma in India

Inflammatory granulomas (neurocysticercosis [NCC] and tuberculomas) are important causes of seizures in children and adults in the developing world. Although several studies have explored seizure characteristics individually in patients with either NCC or tuberculoma, none has compared the seizure recurrence rate between them. This study included patients aged 5 to 18 years with viable parenchymal NCC or tuberculomas who had completed regular follow-up of at least 12 months at a tertiary institute in India. Their baseline seizure and electroencephalographic characteristics, antiseizure medications (ASMs), and breakthrough seizure rates at 12, 24, and 52 weeks were noted. A total of 103 and 54 patients with active NCC and tuberculomas respectively were included. The number of patients who had at least one breakthrough seizure at 12, 24, and 52 weeks in both groups was comparable (P = 0.32, 0.27, and 0.13), and the vast majority were controlled on monotherapy (98% cases in each group). The proportion of patients who required an increase in the dose or change of ASMs or polytherapy, the proportion of children who had status epilepticus at or before 12 months, abnormal electroencephalogram at 12 months, and calcified and active granuloma in neuroimaging at 12 months were also comparable between the two groups (P > 0.05 for all). The number of patients who had ASM-related adverse events and discontinued ASM due to serious adverse events was comparable between both groups, except for hepatotoxicity in the tuberculoma group. The predictors for breakthrough seizures that were found to be statistically significant in the NCC group were the presence of perilesional edema in the baseline magnetic resonance imaging (P = 0.02) and more than five active granulomas (P = 0.01); predictors in the tuberculoma group were the presence of severe perilesional edema causing midline shift in the baseline magnetic resonance imaging (P = 0.01) and more than five active granulomas (P = 0.04). The recurrence rates of breakthrough seizures over the next 12 months in newly detected cases of active NCC and tuberculomas were comparable.

COVID-19-infected woman along with tuberculosis and psychogenic non-epileptic seizures: A case report

During the COVID-19 pandemic, we should not forget about chronic, underlying and important diseases, especially diseases that cause immune system deficiency, of which TB is one and may be missed. Also, we should pay attention to the past medical history of the patients and their drug-drug interactions during the treatment period of COVID-19. Our main clinical message is that diseases such as TB, which weaken the immune system, may predispose a person to COVID-19 infection and COVID-19 may exacerbate TB and it's mortality. On the other hand, diseases that target the lung tissue such as TB and COVID-19, may have synergistic effects and increase mortality (for a patient whose lung capacity is reduced due to TB, superimposed COVID-19 can worsen the situation). In addition, it may be necessary to take more serious considerations for COVID-19 in low socio-economy countries, such as Afghanistan, where TB is more prevalent.

PGE2 displays immunosuppressive effects during human active tuberculosis

Prostaglandin E2 (PGE2), an active lipid compound derived from arachidonic acid, regulates different stages of the immune response of the host during several pathologies such as chronic infections or cancer. In fact, manipulation of PGE2 levels was proposed as an approach for countering the Type I IFN signature of tuberculosis (TB). However, very limited information regarding the PGE2 pathway in patients with active TB is currently available. In the present work, we demonstrated that PGE2 exerts a potent immunosuppressive action during the immune response of the human host against Mycobacterium tuberculosis (Mtb) infection. Actually, we showed that PGE2 significantly reduced the surface expression of several immunological receptors, the lymphoproliferation and the production of proinflammatory cytokines. In addition, PGE2 promoted autophagy in monocytes and neutrophils cultured with Mtb antigens. These results suggest that PGE2 might be attenuating the excessive inflammatory immune response caused by Mtb, emerging as an attractive therapeutic target. Taken together, our findings contribute to the knowledge of the role of PGE2 in the human host resistance to Mtb and highlight the potential of this lipid mediator as a tool to improve anti-TB treatment.

A spiking neural network (SNN) for detecting high frequency oscillations (HFOs) in the intraoperative ECoG

To achieve seizure freedom, epilepsy surgery requires the complete resection of the epileptogenic brain tissue. In intraoperative electrocorticography (ECoG) recordings, high frequency oscillations (HFOs) generated by epileptogenic tissue can be used to tailor the resection margin. However, automatic detection of HFOs in real-time remains an open challenge. Here we present a spiking neural network (SNN) for automatic HFO detection that is optimally suited for neuromorphic hardware implementation. We trained the SNN to detect HFO signals measured from intraoperative ECoG on-line, using an independently labeled dataset (58 min, 16 recordings). We targeted the detection of HFOs in the fast ripple frequency range (250-500 Hz) and compared the network results with the labeled HFO data. We endowed the SNN with a novel artifact rejection mechanism to suppress sharp transients and demonstrate its effectiveness on the ECoG dataset. The HFO rates (median 6.6 HFO/min in pre-resection recordings) detected by this SNN are comparable to those published in the dataset (Spearman's [Formula: see text] = 0.81). The postsurgical seizure outcome was "predicted" with 100% (CI [63 100%]) accuracy for all 8 patients. These results provide a further step towards the construction of a real-time portable battery-operated HFO detection system that can be used during epilepsy surgery to guide the resection of the epileptogenic zone.