Low but Increasing Prevalence of Autism Spectrum Disorders in a French Area from Register-Based Data

Bakel, Marit Maria Elisabeth van; Delobel‐Ayoub, Malika; Cans, Christine; Assouline, Brigitte; Jouk, Pierre‐Simon; Raynaud, J.-P.; Arnaud, Catherine

doi:10.1007/s10803-015-2486-6

Cited by 40 publications

(32 citation statements)

References 32 publications

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“…Nevertheless, our estimate is very close to a value estimated in less recent years 37–39. It is also similar to the prevalence reported using administrative databases in Germany during 201240 for age groups ranging from 6 to 11 years (0.6%) and in France (0.35%) from register-based data 41. In Italy, few studies reporting autism prevalence have been carried out; in a recent paper, Narzisi et al 42 estimated a prevalence of 0.8% in children aged 7–9.…”

Section: Discussionsupporting

confidence: 90%

Do autistic patients change healthcare services utilisation through the transition age? An Italian longitudinal retrospective study

Tùnesi¹,

Bosio²,

Russo

2019

BMJ Open

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ObjectivesThis paper aims to provide an estimate of the prevalence rate of autism spectrum disorder (ASD) in 8-year-olds in 2017 based on administrative databases and to investigate the change in healthcare service use during the healthcare transition age of 18.DesignThis research is based on a longitudinal retrospective cohort study.SettingThe data is drawn from the Italian Administrative Healthcare Database (2010–2017).ParticipantsWe identified 5607 ASD patients; 331 ASD patients from 2012 to 2015 in the calendar year of their 18th birthday were selected and their health service utilisation during a 5-year period—ranging from 2 years preceding and succeeding their 18th year—were investigated.InterventionsNone.Primary and secondary outcome measuresPrevalence, incidence and proportion of ASD patients receiving specific healthcare services were included in the outcome measures.ResultsPrevalence of ASD at age 8 was 5.4/1000. Global access to health and social services was lower both before and after age 18 (46.5% at 16; 68.0% at 18; 54.1% at 20). The percentage of patients receiving a neuropsychiatric consultation decreased after age 18 (30.8% at 18; 5.4% at 20). Community mental health services (CMHS) utilisation rate increased above 18 years of age. Regarding psychiatric visits, for both outpatient and CMHS, an increase was observed from 17.8% at age 18 to 25.4% at age 20. The utilisation of rehabilitation services decreased with age, dropping from 17.8% at age 16 to 1.8% at age 20. Psychiatric outpatient services remained stable across ages at about 14%.ConclusionOur findings suggest that ASD patients changed clinical reference services with age from neuropsychiatric and rehabilitative services towards psychiatric and community-based services as they transitioned from paediatric to adult healthcare services.

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Section: Discussionsupporting

confidence: 90%

Do autistic patients change healthcare services utilisation through the transition age? An Italian longitudinal retrospective study

Tùnesi¹,

Bosio²,

Russo

2019

BMJ Open

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“…22 The impact of this increase among children with CP is not known and we cannot rule out the possibility that the proportion of children with CP and co-occurring ASD may significantly increase among future generations. This probably reflects differences in the methodologies of the systematic assessment for all children with CP: for some this included systematic and specific screening for ASD; for others, not.…”

Section: Discussionmentioning

confidence: 96%

“…Moreover, in France the increased prevalence of ASD in the general population in recent years seems to have been delayed compared with other countries. 22 The impact of this increase among children with CP is not known and we cannot rule out the possibility that the proportion of children with CP and co-occurring ASD may significantly increase among future generations. In North East England the large age range in this cohort may possibly have led to underestimation of ASD diagnosis in very young children, compared with ASD screening which may be done much later in other areas.…”

Section: Discussionmentioning

confidence: 96%

Prevalence and characteristics of autism spectrum disorders in children with cerebral palsy

Delobel‐Ayoub

Klapouszczak

Bakel³

et al. 2017

Develop Med Child Neuro

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“…1 The prevalence of ASD was recently estimated in France to 36.5/10 000 children with a sex ratio of 4.1 boys for 1 girl. 2 Autism is typically diagnosed before 3 years of age, 3 and ASD children are characterized by deficits in social communication and social interaction, as well as restricted and repetitive behaviors and interests, as listed in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-V).…”

Section: ■ Introductionmentioning

confidence: 99%

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

et al. 2015

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Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using 1 H and 1 H− 13C NMR-based approaches and LC−HRMS-based approaches (ESI+ and ESI− on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R 2 Y(cum) = 0.88, Q 2 (cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-L-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.

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Low but Increasing Prevalence of Autism Spectrum Disorders in a French Area from Register-Based Data

Cited by 40 publications

References 32 publications

Do autistic patients change healthcare services utilisation through the transition age? An Italian longitudinal retrospective study

Do autistic patients change healthcare services utilisation through the transition age? An Italian longitudinal retrospective study

Prevalence and characteristics of autism spectrum disorders in children with cerebral palsy

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

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