Active clinical trials for "Seizures"

People over 65 years of ag break down (metabolize) drugs differently than younger adults. It is not known why this happens or how elderly people absorb or break down these drug differently. These difference may show that elderly individuals need lower doses of medications to avoid possible toxicity. We are interested in studying how yor body absorbs and breaks down your lamotrigine medication. This research may indicate that doses of lamotrigine should be lowered as people get older.

This study will evaluate the effectiveness and safety of seletracetam when it is used in addition to other anti-epileptic medications by patients with partial onset seizures. It will also help to determine the best dose to use.

To compare the effect of "point-of-care" (POC) analysis of blood work with traditional laboratory methods on length of stay in a pediatric emergency department (PED).

The unpredictable nature of epileptic seizures places people with epilepsy under permanent psychological stress, which contributes significantly to a restriction in their quality of life. The possibility of predicting the arrival of epileptic seizures would allow, in addition to taking a preventive treatment if the risk of seizure is close, to prevent traumas and accidents linked to possible falls during seizures, to authorize driving for certain people with epilepsy and to reduce the costs of medical care. To date and to our knowledge, no seizure detection device has been commercialized. There are commercialized devices based on biometric sensors other than EEG, but these are strictly dedicated to the detection of seizures and do not allow the anticipation of seizures. Regarding prediction, current research seems to have difficulties in developing convincing algorithms. The only system used successfully in real time would require a device implantable in the brain, but this would raise problems of acceptability. In addition, 20% of people with drug-resistant epilepsy have psychogenic non-epileptic seizures (PNES). These are sometimes difficult to differentiate from epileptic seizures by people with epilepsy and their caregivers, and their management differs from that of epileptic seizures. The distinction between these 2 types of events should also be taken into account by these prediction/detection tools. From the field of biomedical detection dogs, there is currently a converging body of evidence supporting that people with epilepsy emit specific odors associated with seizure events. Trained dogs have been shown to be able to discriminate body odors sampled during or just after an epileptic seizure from those sampled from the same subjects in various contexts outside of a seizure. It was also shown that a seizure can also be predicted by the volatile organic compounds (VOCs) released by the patient (human volatilome); the olfactory signature being already detectable up to 3h before a seizure. Another study used trained dogs to confirm that they are able to detect a seizure by smell and that this olfactory difference is already detectable before a seizure. The human volatilome VOCs lead is particularly promising, notably for its non-invasiveness and for the pre-ictal precocity that prediction allows. But at the moment, the studies are too studies are too preliminary, with sample sizes too small to conclude on the inter-individual generalization of the odor, taking into account the type of seizure involved and the influence of other variables (e.g., gender, age, medications). Moreover, in order to develop a reliable and transportable electronic detection tool, the identification of the VOCs involved is necessary, since the choice of sensors (e.g., to constitute an electronic nose) depends on it. The objective of this study is to overcome these shortcomings, by aiming at the identification of the informative odor(s) associated with epileptic events during the pre-ictal, ictal and post-ictal periods, taking into account the type of seizures (focal seizures, secondary generalized focal seizures, primary generalized seizures - motor and non-motor) and the inter-individual differences.

Convulsion is a common pediatric disorder and there is strong relation between convulsion and cardiovascular system which revealed by ECG monitoring and there are many ECG abnormalities attributed to different causes of convulsions, A 12-lead ECG is a low-cost test and can detect clinically significant abnormalities such as long QTc interval or heart block. Doing an ECG in all patients presenting with seizures clinic, inevitably, pick up non-specific abnormalities which require further investigation. Moreover, a normal 12-lead ECG does not exclude a cardiovascular cause for collapse and for those in whom a cardiac cause is still suspected despite a normal ECG, referral to a cardiologist is advisable

By following up the prognosis of surgical patients, the application value of Cortex ID quantitative analysis in the localization of epilepsy foci was studied. By studying the correlation between autonomic nerve function and epilepsy neural network in epilepsy patients, and analyzing the differences between different epilepsy patients, it can provide more information for judging the prognosis of epilepsy patients.

A cross sectional study on neonatal seizures in Assuit University Children's hospital NICU.

Epilepsy is a chronic disease triggered by increased impulsiveness of nerve cells in the brain and may require a lifelong treatment. Epilepsy is confirmed by two or more unprovoked seizures in more than 24 hours. Febrile Convulsion is another type of seizure occurring due to fever over 38 °C without a history of convulsion, CNS infection, electrolyte imbalance, metabolic disorder, intoxication, and trauma. Unlike epileptic seizures, there are non-epileptic seizures such as Breath Holding Spells that affect children's behaviors and often look like epileptic seizures. QT parameters elongation show the danger of dysrhythmia and unexpected sicknesses such as cardiomyopathy, mitral valve prolapse, ischemic coronary illness, and kidney disorders. Many investigators have reported changes in QT parameters in various diseases such as diabetes mellitus, celiac disease, thalassemia , epilepsy ,Breath holding spells and febrile seizure.

This study is being done to find out if a smartphone app can identify absence seizures. Children who have a history of absence seizures, as well as children without any seizure history, will be testing out the app. If participating the child will be guided through hyperventilation, an activity that asks the child to take quick, deep breaths. The app will record video of the child's face and sounds they make during hyperventilation. Hyperventilation is a safe and established technique frequently used during EEG (electroencephalogram) to encourage seizure occurrence. The App will be used during a regularly scheduled EEG.

CAPAMETRIM 2 aims to characterize epileptic motor patterns by a quantitative three-dimensional analysis of movements. This is done to obtain a 3-D motor signature of seizures, for a given patient, and allows their detection with an ambulatory monitoring system. The benefit for patients is to improve the diagnosis of their diseases by better characterizing their seizures.