婴幼儿皮肤血管瘤的治疗现状及研究进展

婴幼儿血管瘤(infantile hemangioma,IH)是婴幼儿最常见的良性血管性肿瘤,具有独特的生命周期,在出生后快速生长,部分皮损缓慢消退。目前尽管对血管瘤发病机制仍不十分清楚,但治疗方法多种多样,采取单一治疗方法难以取得理想效果,应适时考虑采取综合治疗方法。     

Should patients with complex febrile seizure be admitted for further management?

Background and aims

Children with first complex febrile seizure (CFS) are often admitted for observation. The goals of this study were 1) to assess the risk of seizure recurrence during admission, 2) to determine whether early EEG affects acute management.

Parechovirus Genotype 3 Outbreak among Infants,New South Wales,Australia, 2013–2014

From October 2013 through February 2014, human parechovirus genotype 3 infection was identified in 183 infants in New South Wales, Australia. Of those infants, 57% were male and 95% required hospitalization. Common signs and symptoms were fever >38°C (86%), irritability (80%), tachycardia (68%), and rash (62%). Compared with affected infants in the Northern Hemisphere, infants in New South Wales were slightly older, both sexes were affected more equally, and rash occurred with considerably higher frequency. The New South Wales syndromic surveillance system, which uses near real-time emergency department and ambulance data, was useful for monitoring the outbreak. An alert distributed to clinicians reduced unnecessary hospitalization for patients with suspected sepsis.     

Potential role of brivaracetam in pediatric epilepsy

Brivaracetam (BRV) is a new antiseizure medication (ASM) that is currently approved for adjunctive treatment in patients with focal onset seizures. Similarly to levetiracetam (LEV), BRV works by binding SV2A vesicles with a high affinity and a linear pharmacokinetic profile. Retrospective studies and randomized clinical trials have already proven the efficacy of BRV, even in patients who failed treatment with LEV. Most studies about the efficacy and tolerability conducted so far were performed in adult cohorts, whereas few studies have been performed in children; however, BRV was proven to be a useful ASM for pediatric focal epilepsies, with fewer studies and conflicting results among patients with generalized epilepsies and epileptic syndromes. Retention rates were high in the cohorts analyzed, and no serious treatment‐emergent adverse events were reported in the majority of patients, with somnolence, drowsiness, irritability, aggression, and decreased appetite being the most frequently reported side effects. Although there are few original papers published on the subject so far, the analysis of the literature data demonstrated the efficacy and safety of BRV in pediatric patients, with more evidence for children aged 4‐16 years with an onset of focal seizures. However, a positive response was also achieved in patients affected by encephalopathic epilepsies (eg, Jeavons' epilepsy, Dravet syndrome, Lennox‐Gastaut syndrome, and juvenile myoclonic epilepsy), and ongoing studies are now testing BRV in order to widen its application to other forms of epilepsy and to test its effectiveness when used in monotherapy. This review aims to provide a comprehensive analysis of the literature surrounding the efficacy and tolerability of BRV for pediatric patients.     

Detecting rare events using extreme value statistics applied to epileptic convulsions in children

ObjectiveNocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure detection with the standard method of video electroencephalography monitoring. The goal of this paper is to propose a method for hypermotor seizure detection based on accelerometers that are attached to the extremities.MethodsSupervised methods that are commonly used in literature need annotation of data and hence require expert (neurologist) interaction resulting in a substantial cost. In this paper an unsupervised method is proposed that uses extreme value statistics and seizure detection based on a model of normal behavior that is estimated using all recorded and unlabeled data. In this way the expensive interaction can be avoided.ResultsWhen applying this method to a labeled dataset, acquired from 7 patients, all hypermotor seizures are detected in 5 of the 7 patients with an average positive predictive value (PPV) of 53%. For evaluating the performance on an unlabeled dataset, seizure events are presented to the system as normal movement events. Since hypermotor seizures are rare compared to normal movements, the very few abnormal events have a negligible effect on the quality of the model. In this way, it was possible to evaluate the system for 3 of the 7 patients when 3% of the training set was composed of seizure events. This resulted in sensitivity scores of 80%, 22% and 90% and a PPV of 89%, 21% and 44% respectively. These scores are comparable with a state-of-the-art supervised machine learning based approach which requires a labeled dataset.ConclusionsA person-dependent epileptic seizure detection method has been designed that requires little human interaction. In contrast to traditional machine learning approaches, the imbalance of the dataset does not cause substantial difficulties.