Oral-motor skills following sensorimotor intervention in the moderately eating-impaired child with cerebral palsy

Dysphagia ◽  
1994 ◽  
Vol 9 (3) ◽  
pp. 180-192 ◽  
Author(s):  
Erika G. Gisel
Keyword(s):  
Cerebral Palsy ◽  
Motor Skills ◽  
Impaired Child ◽  
Oral Motor

Oral-motor skills following sensorimotor therapy in two groups of moderately dysphagic children with cerebral palsy: Aspiration vs nonaspiration

Dysphagia ◽  
1996 ◽  
Vol 11 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Erika G. Gisel ◽  
Toni Applegate-Ferrante ◽  
Jane Benson ◽  
James F. Bosma
Keyword(s):  
Cerebral Palsy ◽  
Motor Skills ◽  
Oral Motor ◽  
Children With Cerebral Palsy

ASSESSMENT OF MOTOR SKILLS OF ADOLESCENTS WITH CEREBRAL PALSY IN THE COURSE OF HYDROTHERAPY

2017 ◽  
Vol 19 (11) ◽  
pp. 230-234 ◽  
Author(s):  
Z.S. Varfolomeeva ◽  
◽  
O.B. Podolyaka ◽  
N.A. Panova ◽  
V.A. Dobryakova ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Motor Skills

scholarly journals Comparison of motor outcomes between preschool children with univentricular and biventricular critical heart disease not diagnosed with cerebral palsy or acquired brain injury

2021 ◽  
pp. 1-8
Author(s):  
M. Florencia Ricci ◽  
Alastair Fung ◽  
Diane Moddemann ◽  
Victoria Micek ◽  
Gwen Y. Bond ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Heart Disease ◽  
Preschool Children ◽  
Brain Injury ◽  
Standard Deviation ◽  
Motor Skills ◽  
Odds Ratio ◽  
Motor Impairment ◽  
Acquired Brain Injury ◽  
Manual Dexterity

Abstract This comparison study of two groups within an inception cohort aimed to compare the frequency of motor impairment between preschool children with univentricular and biventricular critical congenital heart disease (CHD) not diagnosed with cerebral palsy/acquired brain injury, describe and compare their motor profiles and explore predictors of motor impairment in each group. Children with an intellectual quotient <70 or cerebral palsy/acquired brain injury were excluded. Motor skills were assessed with the Movement Assessment Battery for Children-2. Total scores <5th percentile indicated motor impairment. Statistical analysis included χ2 test and multiple logistic regression analysis. At a mean age of 55.4 (standard deviation 3.77) months, motor impairment was present in 11.8% of those with biventricular critical CHD, and 32.4% (p < 0.001) of those with univentricular critical CHD. The greatest difference between children with biventricular and univentricular CHD was seen in total test scores 8.73(2.9) versus 6.44(2.8) (p < 0.01) and in balance skills, 8.84 (2.8) versus 6.97 (2.5) (p = 0.001). Manual dexterity mean scores of children with univentricular CHD were significantly below the general population mean (>than one standard deviation). Independent odds ratio for motor impairment in children with biventricular critical CHD was presence of chromosomal abnormality, odds ratio 10.9 (CI 2.13–55.8) (p = 0.004); and in children with univentricular critical CHD odds ratio were: postoperative day 1–5 highest lactate (mmol/L), OR: 1.65 (C1.04–2.62) (p = 0.034), and dialysis requirement any time before the 4.5-year-old assessment, OR: 7.8 (CI 1.08–56.5) (p = 0.042). Early assessment of motor skills, particularly balance and manual dexterity, allows for intervention and supports that can address challenges during the school years.

Identifying Factors Associated With Severe Intellectual Disabilities in Teenagers With Cerebral Palsy Using a Predictive Learning Model

2019 ◽  
Vol 34 (4) ◽  
pp. 221-229 ◽  
Author(s):  
Carlo M. Bertoncelli ◽  
Paola Altamura ◽  
Edgar Ramos Vieira ◽  
Domenico Bertoncelli ◽  
Susanne Thummler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cerebral Palsy ◽  
Intellectual Disability ◽  
Prediction Model ◽  
Motor Skills ◽  
Adaptive Functioning ◽  
Learning Model ◽  
Intelligence Scale ◽  
Factors Associated ◽  
Machine Learning Model

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.

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