The incidence of childhood and adolescent seizures in the UK from 1999 to 2011: A retrospective cohort study using the Clinical Practice Research Datalink

Sammon, Cormac; Charlton, Rachel; Snowball, Julia; Weil, J.

doi:10.1016/j.vaccine.2015.07.093

Cited by 11 publications

(7 citation statements)

References 22 publications

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“…The prevalence rates of febrile seizure vary geographically. 2 6–11 15 22–26 The highest rate is in Guam, at 11.4% in children aged up to 5 years. 24 The rate in South Korea is also high, at 11.2% in children aged up to 5 years.…”

Section: Discussionmentioning

confidence: 97%

“… 15 23 Most previous large cohort studies were based on a database or datalink obtained from hospitals, according to the International Classification of Diseases (ICD) code. 2 8 11 22 26 Studies based on a datalink of ICD codes do not include children who experienced seizures or febrile seizures but did not visit the hospital. In contrast, our data were obtained directly from parents.…”

Section: Discussionmentioning

confidence: 99%

“…The peak age of seizure and febrile seizure onset was between 12 and 24 months, which is concurrent with the findings of earlier studies. 2–4 Most febrile seizures occurred between 6 months and 3 years of age, with a peak incidence at 18 months, although approximately 6%–15% of cases occurred after the age of 4 years. 4 Therefore, based on our results, the lifetime prevalence of febrile seizure is approximately 9.6%–10.7% in Japan.…”

Section: Discussionmentioning

confidence: 99%

“…1 Seizures, including febrile seizures, often occur in children, peaking at 1 year of age. [2][3][4][5] The prevalence of afebrile seizures is thought to be around 1% among children. 2 6 7 In contrast, the prevalence of febrile seizures varies geographically and is reportedly 2%-5% in the USA and Europe 6 8-10 and 8%-11% in East Asia.…”

Section: Introductionmentioning

confidence: 99%

“… 2–5 The prevalence of afebrile seizures is thought to be around 1% among children. 2 6 7 In contrast, the prevalence of febrile seizures varies geographically and is reportedly 2%–5% in the USA and Europe 6 8–10 and 8%–11% in East Asia. 7 11 These geographical differences can be attributed mainly to genetic factors, although several studies have focused on the environmental risk factors.…”

Section: Introductionmentioning

confidence: 99%

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Seizure prevalence in children aged up to 3 years: a longitudinal population-based cohort study in Japan

et al. 2020

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ObjectiveTo investigate the prevalence of seizures/febrile seizures in children up to 3 years of age and examine the effects of gestational age at birth on the risk for febrile seizures.DesignRetrospective longitudinal population-based cohort study.SettingKobe City public health center, Kobe, Japan, from 2010 to 2018.ParticipantsChildren who underwent a medical check-up at 3 years of age.MethodsInformation regarding seizures was collected from the parents of 96 014 children. We identified the occurrence of seizure/febrile seizure in 74 017 children, whose gestational ages at birth were noted. We conducted a multivariate analysis with the parameter, gestational age at birth, to analyse the risk of seizure. We also stratified the samples by sex and birth weight (<2500 g or not) and compared the prevalence of seizure between those with the term and late preterm births.ResultsThe prevalence of seizure was 12.1% (11.8%–12.3%), 13.2% (12.2%–14.4%), 14.6% (12.4%–17.7%) and 15.7% (10.5%–22.8%) in children born at 37–41, 34–36, 28–33 and 22–27 gestational weeks, respectively. The prevalence of febrile seizures was 9.0% (8.8%–9.2%), 10.5% (9.5%–11.5%), 11.8% (9.7%–14.5%) and 11.2% (6.9%–17.7%) in children born at 37–41, 34–36, 28–33 and 22–27 gestational weeks, respectively. Male was an independent risk factor for seizures (OR: 1.15, 95% CI 1.09 to 1.20; absolute risk increase 0.014, 95% CI 0.010 to 0.019) and febrile seizures (OR: 1.21, 95% CI 1.15 to 1.28; absolute risk increase 0.016, 95% CI 0.012 to 0.020), respectively. Late preterm birth was not associated with an increased risk of seizure/febrile seizure.ConclusionsAlthough very preterm birth may increase the risk of seizure/febrile seizure, the risk associated with late preterm birth is considerably small and less than that associated with male.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Seizure prevalence in children aged up to 3 years: a longitudinal population-based cohort study in Japan

et al. 2020

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Scalp Ripples Can Predict Development of Epilepsy After First Unprovoked Seizure in Childhood

Klotz

Sağ

Schönberger

et al. 2020

Annals of Neurology

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Objective Identification of children at risk of developing epilepsy after a first unprovoked seizure can be challenging. Interictal epileptiform discharges are associated with higher risk but have limited sensitivity and specificity. High frequency oscillations (HFOs) are newer biomarkers for epileptogenesis. We prospectively evaluated the predictive value of HFOs for developing epilepsy in scalp electroencephalogram (EEG) of children after a first unprovoked seizure. Methods After their first seizure, 56 children were followed prospectively over 12 months and then grouped in “epilepsy” or “no epilepsy.” Initial EEGs were visually analyzed for spikes, spike ripples, and ripples. Inter‐group comparisons of spike‐rates and HFO‐rates were done by Mann–Whitney U test. Predictive values and optimal thresholds were calculated by receiver operating characteristic (ROC) curves. Results In the epilepsy group (n = 26, 46%), mean rates of ripples (0.3 vs 0.09 / minute, p < 0.0001) and spike ripples (0.6 vs 0.06 / minute, p < 0.05) were significantly higher, with no difference in spike rates (1.7 vs 3.0 / minute, p = 0.38). Of those 3 markers, ripples showed the best predictive value (area under the curve [AUC]ripples = 0.88). The optimal threshold for ripples was calculated to be ≥ 0.125 / minute with a sensitivity of 87% and specificity of 85%. Ripple rates were negatively correlated to days passing before epilepsy‐diagnosis (R = −0.59, p < 0.0001) and time to a second seizure (R = −0.64, 95% confidence interval [CI] = −0.77 to 0.43, p < 0.0001). Interpretation We could show that in a cohort of children with a first unprovoked seizure, ripples predict the development of epilepsy better than spikes or spike ripples and might be useful biomarkers in the estimation of prognosis and question of treatment. ANN NEUROL 2021;89:134–142

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Methodology for computing the burden of disease of adverse events following immunization

McDonald

Nijsten

Bollaerts

et al. 2018

Pharmacoepidemiology and Drug

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PurposeComposite disease burden measures such as disability‐adjusted life‐years (DALY) have been widely used to quantify the population‐level health impact of disease or injury, but application has been limited for the estimation of the burden of adverse events following immunization. Our objective was to assess the feasibility of adapting the DALY approach for estimating adverse event burden.MethodsWe developed a practical methodological framework, explicitly describing all steps involved: acquisition of relative or absolute risks and background event incidence rates, selection of disability weights and durations, and computation of the years lived with disability (YLD) measure, with appropriate estimation of uncertainty. We present a worked example, in which YLD is computed for 3 recognized adverse reactions following 3 childhood vaccination types, based on background incidence rates and relative/absolute risks retrieved from the literature.ResultsYLD provided extra insight into the health impact of an adverse event over presentation of incidence rates only, as severity and duration are additionally incorporated. As well as providing guidance for the deployment of DALY methodology in the context of adverse events associated with vaccination, we also identified where data limitations potentially occur.ConclusionsBurden of disease methodology can be applied to estimate the health burden of adverse events following vaccination in a systematic way. As with all burden of disease studies, interpretation of the estimates must consider the quality and accuracy of the data sources contributing to the DALY computation.

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The incidence of childhood and adolescent seizures in the UK from 1999 to 2011: A retrospective cohort study using the Clinical Practice Research Datalink

Abstract: The rates reported in this study could be used in the postmarketing surveillance of infant vaccines. However, given the variation across strata, and the potential underascertainment of seizure events presenting to A&E, care must be taken when interpreting and using these rates.

Cited by 11 publications

References 22 publications

Seizure prevalence in children aged up to 3 years: a longitudinal population-based cohort study in Japan

Seizure prevalence in children aged up to 3 years: a longitudinal population-based cohort study in Japan

Scalp Ripples Can Predict Development of Epilepsy After First Unprovoked Seizure in Childhood

Methodology for computing the burden of disease of adverse events following immunization

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