Background The spectrum of neurological and psychiatric complications associated with paediatric SARS-CoV-2 infection is poorly understood. We aimed to analyse the range and prevalence of these complications in hospitalised children and adolescents. MethodsWe did a prospective national cohort study in the UK using an online network of secure rapid-response notification portals established by the CoroNerve study group. Paediatric neurologists were invited to notify any children and adolescents (age <18 years) admitted to hospital with neurological or psychiatric disorders in whom they considered SARS-CoV-2 infection to be relevant to the presentation. Patients were excluded if they did not have a neurological consultation or neurological investigations or both, or did not meet the definition for confirmed SARS-CoV-2 infection (a positive PCR of respiratory or spinal fluid samples, serology for anti-SARS-CoV-2 IgG, or both), or the Royal College of Paediatrics and Child Health criteria for paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS). Individuals were classified as having either a primary neurological disorder associated with COVID-19 (COVID-19 neurology group) or PIMS-TS with neurological features (PIMS-TS neurology group). The denominator of all hospitalised children and adolescents with COVID-19 was collated from National Health Service England data. Findings Between April 2, 2020, and Feb 1, 2021, 52 cases were identified; in England, there were 51 cases among 1334 children and adolescents hospitalised with COVID-19, giving an estimated prevalence of 3•8 (95% CI 2•9-5•0) cases per 100 paediatric patients. 22 (42%) patients were female and 30 (58%) were male; the median age was 9 years (range 1-17). 36 (69%) patients were Black or Asian, 16 (31%) were White. 27 (52%) of 52 patients were classified into the COVID-19 neurology group and 25 (48%) were classified into the PIMS-TS neurology group. In the COVID-19 neurology group, diagnoses included status epilepticus (n=7), encephalitis (n=5), Guillain-Barré syndrome (n=5), acute demyelinating syndrome (n=3), chorea (n=2), psychosis (n=2), isolated encephalopathy (n=2), and transient ischaemic attack (n=1). The PIMS-TS neurology group more often had multiple features, which included encephalopathy (n=22 [88%]), peripheral nervous system involvement (n=10 [40%]), behavioural change (n=9 [36%]), and hallucinations at presentation (n=6 [24%]). Recognised neuroimmune disorders were more common in the COVID-19 neurology group than in the PIMS-TS neurology group (13 [48%] of 27 patients vs 1 [<1%] of 25 patients, p=0•0003). Compared with the COVID-19 neurology group, more patients in the PIMS-TS neurology group were admitted to intensive care (20 [80%] of 25 patients vs six [22%] of 27 patients, p=0•0001) and received immunomodulatory treatment (22 [88%] patients vs 12 [44%] patients, p=0•045). 17 (33%) patients (10 [37%] in the COVID-19 neurology group and 7 [28%] in the PIMS-TS neurology group) were discharged with disabili...
Low grade gliomas (LGGs) constitute the largest, yet clinically and (molecular-) histologically heterogeneous group of pediatric brain tumors of WHO grades I and II occurring throughout all pediatric age groups and at all central nervous system (CNS) sites. The tumors are characterized by a slow growth rate and may show periods of growth arrest. Around 40% of all LGG patients can be cured by complete neurosurgical resection and are followed by close observation. In case of relapse, second resection often is possible. Following incomplete resection observation is recommended, as long as there is no radiologic tumor growth and the patient does not suffer from significant, tumor-related symptoms. This also applies to patients with a diagnosis of LGG on the basis of radiological criteria. By contrast, clinical worsening and / or radiologic progression are an indication to treatment with either chemo- or radiotherapy. Overall survival is around 90%, and many patients survive with residual tumor, i. e. they suffer from chronic disease. All patients need comprehensive neuro-oncological care, the principles and details of which are summarized in the current guidelines. These represent standard of care for diagnostic work-up (including neuroimaging and neuropathology), and for therapeutic decisions (including the indications to non-surgical treatment) as well as concepts for neurosurgical intervention, chemotherapy and radiotherapy as well as surveillance and rehabilitation. The current treatment algorithm was compiled by members of the LGG working group of the SIOP-E brain tumor group (SIOP-E-BTG) and is based upon the results of previous European LGG studies and international reports.
This is the largest published series of ioMRI-aided pediatric neurosurgery to date. We have demonstrated that it can be used safely and routinely in pediatric neurosurgical procedures at any age, assisting the surgeon in achieving the best extent of resection and aiding in intra-operative decision-making for tumor- and non-tumor-related intracranial pathology.
To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10−3 mm2 s−1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.
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