1. Erdle S, Conway M, Weinstein M. {{A six-year-old boy with autism and left hip pain}}. {CMAJ}. 2016.
Lien vers le texte intégral (Open Access ou abonnement)
2. Hodgson AR, Grahame V, Garland D, Gaultier F, Lecouturier J, Le Couteur A. {{Parents’ Opinions about an Intervention to Manage Repetitive Behaviours in Young Children with Autism Spectrum Disorder: A Qualitative Study}}. {J Appl Res Intellect Disabil}. 2016.
BACKGROUND: Early intervention for autism spectrum disorder (ASD) tends to focus on enhancing social communication skills. We report data collected via focus group discussions as part of a feasibility and acceptability pilot randomized controlled trial (RCT) about a new parent group intervention to manage restricted and repetitive behaviours (RRB) in young children with ASD. METHODS: The focus groups were led by two independent facilitators and followed a semi-structured topic guide with the aim of considering three key topics: experiences of participating in a RCT, opinions about the intervention and the impact of the intervention on the participants, their children and the family. RESULTS: Fourteen participants attended the focus groups. Most participants reported that they had little knowledge of RRB before attending the intervention and that it had had a positive impact on them, their children and their family. CONCLUSION: The findings support the view that there is an unmet need for a parent-mediated intervention focusing on RRB.
Lien vers le texte intégral (Open Access ou abonnement)
3. Hoyos LR, Thakur M. {{Fragile X premutation in women: recognizing the health challenges beyond primary ovarian insufficiency}}. {J Assist Reprod Genet}. 2016.
Fragile X premutation carriers have 55-200 CGG repeats in the 5′ untranslated region of the FMR1 gene. Women with this premutation face many physical and emotional challenges in their life. Approximately 20% of these women will develop fragile X-associated primary ovarian insufficiency (FXPOI). In addition, they suffer from increased rates of menstrual dysfunction, diminished ovarian reserve, reduction in age of menopause, infertility, dizygotic twinning, and risk of having an offspring with a premutation or full mutation. Consequent chronic hypoestrogenism may result in impaired bone health and increased cardiovascular risk. Neuropsychiatric issues include risk of developing fragile X-associated tremor/ataxia syndrome, neuropathy, musculoskeletal problems, increased prevalence of anxiety, depression, and sleep disturbances independent of the stress of raising an offspring with fragile X syndrome and higher risk of postpartum depression. Some studies have reported a higher prevalence of thyroid abnormalities and hypertension in these women. Reproductive health providers play an important role in the health supervision of women with fragile X premutation. Awareness of these risks and correlation of the various manifestations could help in early diagnosis and coordination of care and services for these women and their families. This paper reviews current evidence regarding the possible conditions that may present in women with premutation-sized repeats beyond FXPOI.
Lien vers le texte intégral (Open Access ou abonnement)
4. Thackeray LA, Eatough V. {{‘Shutting the World Out’: An Interpretative Phenomenological Analysis Exploring the Paternal Experience of Parenting a Young Adult with a Developmental Disability}}. {J Appl Res Intellect Disabil}. 2016.
BACKGROUND: An in-depth exploration of the experience of midlife fathers of developmentally disabled young adults (aged 19-32 years) was motivated by a dearth of research in this area (McKnight, PsyPAG Quarterly, 94, 2015, 10). METHOD: Five fathers participated in semi-structured interviews which were subjected to interpretative phenomenological analysis (Smith, Flowers and Larkin, 2009, Interpretative Phenomenological Analysis: Theory, Method, and Research. London: Sage). RESULTS: The final thematic structure comprises four inter-related themes. They demonstrate a high degree of concern for children’s well-being; the joy adult children confers on their father’s lives as well as the difficulties men experience in response to the limited opportunities available to their offspring. Importantly findings also illustrate the way in which men struggle to contend with painful emotions. CONCLUSIONS: Societal conceptions of masculinity, fatherhood and disability necessarily influence the way fathers experience the world (Yarwood, Fathering, 9, 2011, 150). It is imperative that service providers recognize the particular challenges faced by fathers, seeking ways to better engage and support them.
Lien vers le texte intégral (Open Access ou abonnement)
5. Vignoli A, Savini MN, Nowbut MS, Peron A, Turner K, La Briola F, Canevini MP. {{Effectiveness and tolerability of antiepileptic drugs in 104 girls with Rett syndrome}}. {Epilepsy Behav}. 2016; 66: 27-33.
Approximately 60-80% of girls with Rett Syndrome (RTT) have epilepsy, which represents one of the most severe problems clinicians have to deal with, especially when patients are 7-12years old. The aim of this study was to analyze the antiepileptic drugs (AEDs) prescribed in RTT, and to assess their effectiveness and tolerability in different age groups from early infancy to adulthood. We included in this study 104 girls, aged 2-42years (mean age 13.9years): 89 had a mutation in MECP2, 5 in CDKL5, 2 in FOXG1, and the mutational status was unknown in the remaining 8. Epilepsy was present in 82 patients (79%). Mean age at epilepsy onset was 4.1years. We divided the girls into 5 groups according to age: <5, 5-9, 10-14, 15-19, 20years and older. Valproic acid (VPA) was the most prescribed single therapy in young patients (<15years), whereas carbamazepine (CBZ) was preferred by clinicians in older patients. The most frequently adopted AED combination in the patients younger than 10years and older than 15 was VPA and lamotrigine (LTG). Seizures in the group aged 10-14years were the most difficult to treat, requiring a mean of three different AEDs, often used in combination and mostly including VPA. Seizures in fifteen patients (18%) were considered drug resistant. VPA was reported as the most effective AED in younger girls (in 40% of the patients aged <5years, in 19% of the girls aged 5-9years), and CBZ the most effective in the patients 15years or older. Adverse reactions did not differ from expected: agitation, drowsiness, and weight loss were the most frequently reported. In our sample, LTG was the least tolerated AED. We did not find correlations with MECP2 mutations in terms of effectiveness or adverse reactions. CONCLUSION: in this study we observed different effectiveness of AEDs based on age, and suggest that clinicians consider age-dependency when prescribing appropriate AEDs in the RTT population. Lien vers le texte intégral (Open Access ou abonnement)
6. Kassraian-Fard P, Matthis C, Balsters JH, Maathuis MH, Wenderoth N. {{Promises, Pitfalls, and Basic Guidelines for Applying Machine Learning Classifiers to Psychiatric Imaging Data, with Autism as an Example}}. {Front Psychiatry}. 2016; 7: 177.
Most psychiatric disorders are associated with subtle alterations in brain function and are subject to large interindividual differences. Typically, the diagnosis of these disorders requires time-consuming behavioral assessments administered by a multidisciplinary team with extensive experience. While the application of Machine Learning classification methods (ML classifiers) to neuroimaging data has the potential to speed and simplify diagnosis of psychiatric disorders, the methods, assumptions, and analytical steps are currently opaque and not accessible to researchers and clinicians outside the field. In this paper, we describe potential classification pipelines for autism spectrum disorder, as an example of a psychiatric disorder. The analyses are based on resting-state fMRI data derived from a multisite data repository (ABIDE). We compare several popular ML classifiers such as support vector machines, neural networks, and regression approaches, among others. In a tutorial style, written to be equally accessible for researchers and clinicians, we explain the rationale of each classification approach, clarify the underlying assumptions, and discuss possible pitfalls and challenges. We also provide the data as well as the MATLAB code we used to achieve our results. We show that out-of-the-box ML classifiers can yield classification accuracies of about 60-70%. Finally, we discuss how classification accuracy can be further improved, and we mention methodological developments that are needed to pave the way for the use of ML classifiers in clinical practice.
