Variant of Rett syndrome and CDKL5 gene: clinical and autonomic description of 10 cases.

UNLABELLED: Rett syndrome (RTT) is a severe neurodevelopmental disorder affecting almost exclusively females. The Hanefeld variant, or early-onset seizure variant, has been associated with mutations in CDKL5 gene. AIMS: In recent years more than 60 patients with mutations in the CDKL5 gene have been described in the literature, but the cardiorespiratory phenotype has not been reported. Our aim is to describe clinical and autonomic features of these girls. METHODS: 10 girls with CDKL5 mutations and a diagnosis of Hanefeld variant have been evaluated on axiological and clinical aspects. In all subjects an evaluation of the autonomic system was performed using the Neuroscope. RESULTS: Common features were gaze avoidance, repetitive head movements and hand stereotypies. The autonomic evaluation disclosed eight cases with the Forceful breather cardiorespiratory phenotype and two cases with the Apneustic breather phenotype. CONCLUSIONS: The clinical picture remains within the RTT spectrum but some symptoms are more pronounced in addition to the very early onset of seizures. The cardiorespiratory phenotype was dominated by Forceful breathers, while Feeble breathers were not found, differently from the general Rett population, suggesting a specific behavioral and cardiorespiratory phenotype of the RTT the Hanefeld variant.

The Correlation between Electroencephalography Amplitude and Interictal Abnormalities: Audit study.

OBJECTIVES: The aim of this study was to establish the relationship between background amplitude and interictal abnormalities in routine electroencephalography (EEG). METHODS: This retrospective audit was conducted between July 2006 and December 2009 at the Department of Clinical Physiology at Sultan Qaboos University Hospital (SQUH) in Muscat, Oman. A total of 1,718 electroencephalograms (EEGs) were reviewed. All EEGs were from patients who had been referred due to epilepsy, syncope or headaches. EEGs were divided into four groups based on their amplitude: group one ≤20 µV; group two 21-35 µV; group three 36-50 µV, and group four >50 µV. Interictal abnormalities were defined as epileptiform discharges with or without associated slow waves. Abnormalities were identified during periods of resting, hyperventilation and photic stimulation in each group. RESULTS: The mean age ± standard deviation of the patients was 27 ± 12.5 years. Of the 1,718 EEGs, 542 (31.5%) were abnormal. Interictal abnormalities increased with amplitude in all four categories and demonstrated a significant association (P <0.05). A total of 56 EEGs (3.3%) had amplitudes that were ≤20 µV and none of these showed interictal epileptiform abnormalities. CONCLUSION: EEG amplitude is an important factor in determining the presence of interictal epileptiform abnormalities in routine EEGs. This should be taken into account when investigating patients for epilepsy. A strong argument is made for considering long-term EEG monitoring in order to identify unexplained seizures which may be secondary to epilepsy. It is recommended that all tertiary institutions provide EEG telemetry services.

Pre-ictal autonomic changes.

Autonomic measures frequently alter with seizure activity and with brain state and so theoretically, there could be pre-ictal changes in autonomic function. However, there are considerable confounders. First, the measurement of autonomic function is not straightforward; heart rate and measures derived form heart rate have been those that have used the most in assessing changes in autonomic function. Second, autonomic function can vary considerably over the 24h cycle and can change suddenly depending on internal and external stimuli (e.g. fear, pain) and so any measures of changes in autonomic function will lose specificity. Third, changes in autonomic function in response to seizures, depends upon the individual, seizure type and spread of the seizure and even then can vary from seizure to seizure in the same individual. The idea that there will be well-defined, unique autonomic changes that occur in the pre-ictal period is very unlikely. These factors make it unlikely that autonomic function monitoring can be used successfully as a means of seizure prediction. However, in sleep, changes in autonomic function relate to changes in arousal state and since such states and the transition between such states may predict seizure occurrence in certain individuals, autonomic function could be a helpful determinant of seizure risk at certain stages of sleep. This hypothesis has, however, yet to be tested.