scholarly journals Severe microbrachycephaly-intellectual disability-athetoid cerebral palsy syndrome

2020 ◽  
Author(s):  
2013 ◽  
Vol 23 (7) ◽  
pp. 1464-1471 ◽  
Author(s):  
Keung Nyun Kim ◽  
Poong Gee Ahn ◽  
Mi Jung Ryu ◽  
Dong Ah Shin ◽  
Seong Yi ◽  
...  

1987 ◽  
Vol 35 (3) ◽  
pp. 784-788
Author(s):  
Shoichi Kawagoe ◽  
Naoya Tajima ◽  
Keiichiro Kawano ◽  
Yoshihiro Deguchi

2019 ◽  
Vol 34 (4) ◽  
pp. 221-229 ◽  
Author(s):  
Carlo M. Bertoncelli ◽  
Paola Altamura ◽  
Edgar Ramos Vieira ◽  
Domenico Bertoncelli ◽  
Susanne Thummler ◽  
...  

Background: Intellectual disability and impaired adaptive functioning are common in children with cerebral palsy, but there is a lack of studies assessing these issues in teenagers with cerebral palsy. Therefore, the aim of this study was to develop and test a predictive machine learning model to identify factors associated with intellectual disability in teenagers with cerebral palsy. Methods: This was a multicenter controlled cohort study of 91 teenagers with cerebral palsy (53 males, 38 females; mean age ± SD = 17 ± 1 y; range: 12-18 y). Data on etiology, diagnosis, spasticity, epilepsy, clinical history, communication abilities, behaviors, motor skills, eating, and drinking abilities were collected between 2005 and 2015. Intellectual disability was classified as “mild,” “moderate,” “severe,” or “profound” based on adaptive functioning, and according to the DSM-5 after 2013 and DSM-IV before 2013, the Wechsler Intelligence Scale for Children for patients up to ages 16 years, 11 months, and the Wechsler Adult Intelligence Scale for patients ages 17-18. Statistical analysis included Fisher’s exact test and multiple logistic regressions to identify factors associated with intellectual disability. A predictive machine learning model was developed to identify factors associated with having profound intellectual disability. The guidelines of the “Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis Statement” were followed. Results: Poor manual abilities ( P ≤ .001), gross motor function ( P ≤ .001), and type of epilepsy (intractable: P = .04; well controlled: P = .01) were significantly associated with profound intellectual disability. The average model accuracy, specificity, and sensitivity was 78%. Conclusion: Poor motor skills and epilepsy were associated with profound intellectual disability. The machine learning prediction model was able to adequately identify high likelihood of severe intellectual disability in teenagers with cerebral palsy.


2013 ◽  
Vol 3 (3) ◽  
pp. 262-268
Author(s):  
R Lakhan

Background   Cerebral palsy (CP) is a global public health problem affecting 2.12 to 2.45 per 1000 live birth across the world. Cerebral palsy is an upper motor neuron, non-progressive disorder commonly associated with intellectual disability. The presence of cerebral palsy effects person’s overall life. Objectives This study primarily sought predictive capacity of social, environmental and biological determinants of CP in ID. Materials and Methods This is a cross-sectional study design. A total of 262 children, aged 3 to 18 years, with ID were assessed for cerebral palsy and diagnosed on basis of clinical examination in a community based rehabilitation project in Barwani, India. Information was collected by parent interviews, on social, environmental and biological determinants. A logistic regression model has been applied between determinants and CP.  Results Logistic regression demonstrated that likelihood of CP in ID children can be predicted on bases of their age (odd ratio = 0.856, CI 95% - 0.76-0.95), intelligence quotients (IQ) (odd ratio = 0.782, CI 95% - 0.73-0.83) and family history of intellectual disabilities (odd ratio = 0.051, CI 95% - 2.36 -0.99) and epilepsy (odd ratio = 0.008, CI 95% - 2.58-1.28). Comorbid conditions of downs syndrome and epilepsy also predicts likelihood of CP in ID. Conclusion Likelihood of CP in ID children can be predicted by their age, IQ, family history of intellectual disability, epilepsy and comorbid conditions of downs syndrome and epilepsy. Gender, socio-economic status and population (tribal versus non-tribal) determinants have no predictive relation with CP in the group. DOI: http://dx.doi.org/10.3126/nje.v3i3.9187 Nepal Journal of Epidemiology 2013;3(3): 262-268


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Tono Djuwantono ◽  
Jenifer Kiem Aviani ◽  
Wiryawan Permadi ◽  
Tri Hanggono Achmad ◽  
Danny Halim

Abstract Background Various techniques in assisted reproductive technology (ART) have been developed as solutions for specific infertility problems. It is important to gain consensual conclusions on the actual risks of neurodevelopmental disorders among children who are born from ART. This study aimed to quantify the relative risks of cerebral palsy, intellectual disability, autism spectrum disorder (ASD), and behavioral problems in children from different ART methods by using systematic review and meta-analysis. Healthcare providers could use the results of this study to suggest the suitable ART technique and plan optimum postnatal care. Methods Pubmed, Google Scholar, and Scopus databases were used to search for studies up to January 2020. Of the 181 screened full manuscripts, 17 studies (9.39%) fulfilled the selection criteria. Based on the Newcastle-Ottawa scale ratings, 7 studies were excluded, resulting in 10 studies that were eventually included in the meta-analyses. Mantel-Haenszel risk ratio model was used in the meta-analysis, and the results are described using forest plot with 95% confidence interval. Heterogeneity was assessed using the I2 value. Results Pooled evaluation of 10 studies showed that the risk of cerebral palsy in children from assisted reproductive technology (ART) is higher than children from natural conceptions (risk ratio [RR] 1.82, [1.41, 2.34]; P = 0.00001). Risk of intellectual disability (RR 1.46, [1.03, 2.08]; P = 0.03) and ASD (RR 1.49 [1.05, 2.11]; P = 0.03) are higher in intracytoplasmic sperm injection (ICSI) children compared to conventional in vitro fertilization (IVF) children. The differences in the risk of neurodevelopmental disorders in children born after frozen and fresh embryo transfers are not significant. Analysis on potential cofounder effects, including multiple birth, preterm birth, and low birth body weight highlight possibilities of significant correlation to the risks of neurodevelopmental disorders. Conclusions Pooled estimates suggest that children born after ART are at higher risk of acquiring cerebral palsy. ICSI treatment causes higher risk of intellectual disability and ASD. These findings suggest the importance of the availability of intensive care unit at the time of delivery and long-term developmental evaluation particularly in children from ICSI.


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