Risk Factors for Developing Scoliosis in Cerebral Palsy: A Cross-Sectional Descriptive Study

Bertoncelli, Carlo M.; Solla, Federico; Loughenbury, Peter; Bertoncelli, Domenico; Rampal, Virginie

doi:10.1177/0883073817701047

Cited by 32 publications

(62 citation statements)

References 32 publications

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“…This was performed with “OpenEpi,” a web‐based epidemiological calculator . In the univariate logistic regression analysis, we compared GMFCS, MACS, and EDACS levels ≤ 4 versus > 4 according with previous studies …”

Section: Methodsmentioning

confidence: 99%

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Predictive Model for Gastrostomy Placement in Adolescents With Developmental Disabilities and Cerebral Palsy

et al. 2019

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Background Factors associated with gastrostomy placement in adolescents with developmental disabilities (DDs) and cerebral palsy (CP) are poorly investigated. We aimed to develop and validate a machine learning (ML) model for gastrostomy placement in adolescents with DDs and CP. Methods We performed a multinational, double‐blinded, case‐control study including 130 adolescents with severe DD and CP (72 males, 58 females; mean age 16 ± 2 years). Data on etiology, diagnosis, spasticity, epilepsy, clinical history, and functional assessments such as the Eating and Drinking Ability Classification System, Manual Ability Classification System, and Gross Motor Function Classification System were collected between 2005 and 2015. Analysis included Fisher exact test, multiple logistic regressions, and a supervised ML model, named PredictMed, to identify factors associated with gastrostomy placement. “Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis” guidelines were followed. Results Poor motor function (P < 0.001), trunk muscle tone disorder (P < 0.001), male gender (P < 0.01), epilepsy (P = 0.01), and severe neuromuscular scoliosis (P = 0.04) were factors linked with gastrostomy placement in univariate analysis. Epilepsy (P = 0.03), poor motor function (P = 0.04), and male gender (P = 0.04) were associated with gastrostomy placement in multivariate analysis with 95% accuracy. Conclusion Epilepsy, poor motor function, trunk muscles tone disorder, and male gender were accurate, sensitive, and specific factors associated with gastrostomy need.

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Section: Methodsmentioning

confidence: 99%

“…The main objective of this study was to adapt, develop, and test the validity of a previous ML model named “PredictMed” and to identify factors associated with gastrostomy placement in adolescents with DDs and CP. The second aim was to identify factors associated with LARS in the population mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Predictive Model for Gastrostomy Placement in Adolescents With Developmental Disabilities and Cerebral Palsy

et al. 2019

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“…Children at higher GMFCS levels (ie more severely affected gross motor function) have also been reported to develop scoliosis at an earlier age . Additional risk factors for scoliosis include being female, having undergone hip surgery, moderate to severe epilepsy, poor muscle control, muscle weakness and spasticity . Treatment modalities for scoliosis can be either surgical (segmental spinal fusion) or nonsurgical (spinal bracing) .…”

Section: Introductionmentioning

confidence: 99%

Back pain is more frequent in girls and in children with scoliosis in the context of cerebral palsy

2019

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AimTo investigate the prevalence of general and back pain in children with cerebral palsy and the relationships between scoliosis and back pain.MethodsCross‐sectional register study based on data from the Swedish Cerebral Palsy Follow‐Up Programme. Descriptive analyses and logistic regression to regress age, sex, gross motor function, windswept, hip extension and source of report on the presence of pain.ResultsThe study included 3783 children (58% boys) 1‐18 (mean 10.0) years of age. General pain was reported in 1538 (44% girls, 38% boys) and back pain in 226 (7% girls, 5% boys) children. The proportion of back pain increased from <4% prior to age 12 years to >12% from 16 years of age. Back pain increased from 4% in children without scoliosis to 16% in children with severe scoliosis. Moderate/severe back pain increased from 2% in children without scoliosis to 10% in children with severe scoliosis. Increased odds of reporting back pain were found for age, girls, low gross motor function and children with scoliosis.ConclusionThe proportion of children with general pain increased with age and was more frequent in girls. Age, female sex, low gross motor function and scoliosis were significant predictors of back pain.

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“…On 2017, PredictMed highlighted the presence of hip surgery (p .002), intractable epilepsy (p .04), and female gender (p .07) as risks factors of scoliosis. 1,2 Average of accuracy, sensitivity, and specificity of the predictive model was 74%.…”

Section: Model Development Path and Its Adaptability To Multiform Neumentioning

confidence: 98%

“…Cerebral palsy (CP) is the term used for a group of nonprogressive disorders of motor control and posture that occur secondary to damage to the developing brain during the early stages of its development. 1 Predictive models using logistic regression (LR) are widely used in the healthcare, but only recently, they started to be used to predict health-related outcomes in subjects with CP. [2][3][4] This article discusses the potential of using a LR-based predictive model (hereby named PredictMed) for health outcomes and presents examples of the application of the model.…”

Section: Introductionmentioning

confidence: 99%

PredictMed: A logistic regression–based model to predict health conditions in cerebral palsy

Bertoncelli

Altamura

Vieira³

et al. 2020

Health Informatics J

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Logistic regression–based predictive models are widely used in the healthcare field but just recently are used to predict comorbidities in children with cerebral palsy. This article presents a logistic regression approach to predict health conditions in children with cerebral palsy and a few examples from recent research. The model named PredictMed was trained, tested, and validated for predicting the development of scoliosis, intellectual disabilities, autistic features, and in the present study, feeding disorders needing gastrostomy. This was a multinational, cross-sectional descriptive study. Data of 130 children (aged 12–18 years) with cerebral palsy were collected between June 2005 and June 2015. The logistic regression–based model uses an algorithm implemented in R programming language. After splitting the patients in training and testing sets, logistic regressions are performed on every possible subset (tuple) of independent variables. The tuple that shows the best predictive performance in terms of accuracy, sensitivity, and specificity is chosen as a set of independent variables in another logistic regression to calculate the probability to develop the specific health condition (e.g. the need for gastrostomy). The average of accuracy, sensitivity, and specificity score was 90%. Our model represents a novelty in the field of some cerebral palsy–related health outcomes treatment, and it should significantly help doctors’ decision-making process regarding patient prognosis.

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Risk Factors for Developing Scoliosis in Cerebral Palsy: A Cross-Sectional Descriptive Study

Cited by 32 publications

References 32 publications

Predictive Model for Gastrostomy Placement in Adolescents With Developmental Disabilities and Cerebral Palsy

Predictive Model for Gastrostomy Placement in Adolescents With Developmental Disabilities and Cerebral Palsy

Back pain is more frequent in girls and in children with scoliosis in the context of cerebral palsy

PredictMed: A logistic regression–based model to predict health conditions in cerebral palsy

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