Clinical predictive model of lumbar curve Cobb angle below selective fusion for thoracic adolescent idiopathic scoliosis: a longitudinal multicenter descriptive study.

PURPOSE: To implement a clinically applicable, predictive model for the lumbar Cobb angle below a selective thoracic fusion in adolescent idiopathic scoliosis. METHODS: A series of 146 adolescents with Lenke 1 or 2 idiopathic scoliosis, surgically treated with posterior selective fusion, and minimum follow-up of 5 years (average 7) was analyzed. The cohort was divided in 2 groups: if lumbar Cobb angle at last follow-up was, respectively, ≥ or < 10°. A logistic regression-based prediction model (PredictMed) was implemented to identify variables associated with the group ≥ 10°. The guidelines of the TRIPOD statement were followed. RESULTS: Mean Cobb angle of thoracic main curve was 56° preoperatively and 25° at last follow-up. Mean lumbar Cobb angle was 33° (20; 59) preoperatively and 11° (0; 35) at last follow-up. 53 patients were in group ≥ 10°. The 2 groups had similar demographics, flexibility of both main and lumbar curves, and magnitude of the preoperative main curve, p > 0.1. From univariate analysis, mean magnitude of preoperative lumbar curves (35° vs. 30°), mean correction of main curve (65% vs. 58%), mean ratio of main curve/distal curve (1.9 vs. 1.6) and distribution of lumbar modifiers were statistically different between groups (p < 0.05). PredictMed identified the following variables significantly associated with the group ≥ 10°: main curve % correction at last follow-up (p = 0.01) and distal curve angle (p = 0.04) with a prediction accuracy of 71%. CONCLUSION: The main modifiable factor influencing uninstrumented lumbar curve was the correction of main curve. The clinical model PredictMed showed an accuracy of 71% in prediction of lumbar Cobb angle ≥ 10° at last follow-up. LEVEL OF EVIDENCE IV: Longitudinal comparative study.

PredictMed: A Machine Learning Model for Identifying Risk Factors of Neuromuscular Hip Dysplasia: A Multicenter Descriptive Study.

Neuromuscular hip dysplasia (NHD) is a common and severe problem in patients with cerebral palsy (CP). Previous studies have so far identified only spasticity (SP) and high levels of Gross Motor Function Classification System as factors associated with NHD. The aim of this study is to develop a machine learning model to identify additional risk factors of NHD. This was a cross-sectional multicenter descriptive study of 102 teenagers with CP (60 males, 42 females; 60 inpatients, 42 outpatients; mean age 16.5 ± 1.2 years, range 12-18 years). Data on etiology, diagnosis, SP, epilepsy (E), clinical history, and functional assessments were collected between 2007 and 2017. Hip dysplasia was defined as femoral head lateral migration percentage > 33% on pelvic radiogram. A logistic regression-prediction model named PredictMed was developed to identify risk factors of NHD. Twenty-eight (27%) teenagers with CP had NHD, of which 18 (67%) had dislocated hips. Logistic regression model identified poor walking abilities (p < 0.001; odds ratio [OR] infinity; 95% confidence interval [CI] infinity), scoliosis (p = 0.01; OR 3.22; 95% CI 1.30-7.92), trunk muscles' tone disorder (p = 0.002; OR 4.81; 95% CI 1.75-13.25), SP (p = 0.006; OR 6.6; 95% CI 1.46-30.23), poor motor function (p = 0.02; OR 5.5; 95% CI 1.2-25.2), and E (p = 0.03; OR 2.6; standard error 0.44) as risk factors of NHD. The accuracy of the model was 77%. PredictMed identified trunk muscles' tone disorder, severe scoliosis, E, and SP as risk factors of NHD in teenagers with CP.

Botulinum Toxin in Children with Cerebral Palsy: An Update.

Injected in a muscle, the botulinum toxin causes localized and temporary paralysis by acting on the neuromuscular synapse. Currently, it is widely prescribed for the treatment of limb spasticity in children from the age of 2 years. Combined with rehabilitation and other treatments, it helps to progress in motor learning, promotes functional progression, and delays orthopaedic degradations.Numerous randomized, placebo-controlled studies have shown efficacy in reducing spasticity, improving passive and active mobility, reducing pain, and improving upper limb comfort care. The side effects are rare and commonplace.The injection technique is accessible after specific training and practice. The indication is better evaluated by a multidisciplinary team. A precise clinical evaluation, assisted by an instrumental analysis (videography, spatiotemporal parameters, kinematics, kinetics, and electromyography), makes it possible to determine the aims of the treatment and to evaluate the outcome.The objective of this review is to present current evidence base and practices regarding the use of botulinum toxin in children with cerebral palsy.

Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy.

Autism spectrum disorder (ASD) is common in adolescents with cerebral palsy (CP) and there is a lack of studies applying artificial intelligence to investigate this field and this population in particular. The aim of this study is to develop and test a predictive learning model to identify factors associated with ASD in adolescents with CP. This was a multicenter controlled cohort study of 102 adolescents with CP (61 males, 41 females; mean age ± SD [standard deviation] = 16.6 ± 1.2 years; range: 12-18 years). Data on etiology, diagnosis, spasticity, epilepsy, clinical history, communication abilities, behaviors, intellectual disability, motor skills, and eating and drinking abilities were collected between 2005 and 2015. Statistical analysis included Fisher's exact test and multiple logistic regressions to identify factors associated with ASD. A predictive learning model was implemented to identify factors associated with ASD. The guidelines of the "transparent reporting of a multivariable prediction model for individual prognosis or diagnosis" (TRIPOD) statement were followed. Type of spasticity (hemiplegia > diplegia > tri/quadriplegia; OR [odds ratio] = 1.76, SE [standard error] = 0.2785, p = 0.04), communication disorders (OR = 7.442, SE = 0.59, p < 0.001), intellectual disability (OR = 2.27, SE = 0.43, p = 0.05), feeding abilities (OR = 0.35, SE = 0.35, p = 0.002), and motor function (OR = 0.59, SE = 0.22, p = 0.01) were significantly associated with ASD. The best average prediction model score for accuracy, specificity, and sensitivity was 75%. Motor skills, feeding abilities, type of spasticity, intellectual disability, and communication disorders were associated with ASD. The prediction model was able to adequately identify adolescents at risk of ASD.

Patient-Specific Surgical Correction of Adolescent Idiopathic Scoliosis: A Systematic Review.

The restoration of sagittal alignment is fundamental to the surgical correction of adolescent idiopathic scoliosis (AIS). Despite established techniques, some patients present with inadequate postoperative thoracic kyphosis (TK), which may increase the risk of proximal junctional kyphosis (PJK) and imbalance. There is a lack of knowledge concerning the effectiveness of patient-specific rods (PSR) with measured sagittal curves in achieving a TK similar to that planned in AIS surgery, the factors influencing this congruence, and the incidence of PJK after PSR use. This is a systematic review of all types of studies reporting on the PSR surgical correction of AIS, including research articles, proceedings, and gray literature between 2013 and December 2023. From the 28,459 titles identified in the literature search, 81 were assessed for full-text reading, and 7 studies were selected. These included six cohort studies and a comparative study versus standard rods, six monocentric and one multicentric, three prospective and four retrospective studies, all with a scientific evidence level of 4 or 3. They reported a combined total of 355 AIS patients treated with PSR. The minimum follow-up was between 4 and 24 months. These studies all reported a good match between predicted and achieved TK, with the main difference ranging from 0 to 5 degrees, p > 0.05, despite the variability in surgical techniques and the rods' properties. There was no proximal junctional kyphosis, whereas the current rate from the literature is between 15 and 46% with standard rods. There are no specific complications related to PSR. The exact role of the type of implants is still unknown. The preliminary results are, therefore, encouraging and support the use of PSR in AIS surgery.

PredictMed-epilepsy: A multi-agent based system for epilepsy detection and prediction in neuropediatrics.

BACKGROUND AND OBJECTIVE: Epileptic seizures are associated with a higher incidence of Developmental Disabilities and Cerebral Palsy. Early evaluation and management of epilepsy is strongly recommended. We propose and discuss an application to predict epilespy (PredictMed-Epilepsy) and seizures via a deep-learning module (PredictMed-Seizures) encompassed within a multi-agent based healthcare system (PredictMed-MHS); this system is meant, in perspective, to be integrated into a clinical decision support system (PredictMed-CDSS). PredictMed-Epilespy, in particular, aims to identify factors associated with epilepsy in children with Developmental Disabilities and Cerebral Palsy by using a prediction-learning model named PredictMed. PredictMed-epilespy methods: We performed a longitudinal, multicenter, double-blinded, descriptive study of one hundred and two children with Developmental Disabilities and Cerebral Palsy (58 males, 44 females; 65 inpatients, 37 outpatients; 72 had epilepsy - 22 of intractable epilepsy, age: 16.6±1.2y, range: 12-18y). Data from 2005 to 2021 on Cerebral Palsy etiology, diagnosis, type of epilepsy and spasticity, clinical history, communication abilities, behaviors, intellectual disability, motor skills, and eating and drinking abilities were collected. The machine-learning model PredictMed was exploited to identify factors associated with epilepsy. The guidelines of the "Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis" Statement (TRIPOD) were followed. PredictMed-epilepsy results: Cerebral Palsy etiology [(prenatal > perinatal > postnatal causes) p=0.036], scoliosis (p=0.048), communication (p=0.018) and feeding disorders (p=0.002), poor motor function (p<0.001), intellectual disabilities (p=0.007), and type of spasticity [(quadriplegia/triplegia > diplegia > hemiplegia), p=0.002)] were associated with having epilepsy. The prediction model scored an average of 82% of accuracy, sensitivity, and specificity. Thus, PredictMed defined the computational phenotype of children with Developmental Disabilities/Cerebral Palsy at risk of epilepsy. Novel contribution of the work: We have been developing and we have prototypically implemented a Multi-Agent Systems (MAS) that encapsulates the PredictMed-Epilepsy module. More specifically, we have implemented the Patient Observing MAS (PoMAS), which, as a novelty w.r.t. the existing literature, includes a complex event processing module that provides real-time detention of short- and long-term events related to the patient's condition.

Bipolar Fusionless Versus Standard Fusion Surgery in Neuromuscular Scoliosis: A Two-center Comparative Study.

STUDY DESIGN: Nonrandomized controlled cohort. OBJECTIVE: To compare early results between bipolar fusionless construct (BFC) and single posterior fusion (SPF) surgery in neuromuscular scoliosis (NMS). BACKGROUND: Surgical treatments for NMS have traditionally been characterized by high complication rates. A mini-invasive BFC was developed to reduce these risks while maintaining adequate curve reduction. There is, however, a current lack of studies comparing clinical and radiologic perioperative outcomes between both techniques. METHODS: All patients surgically treated for NMS with to-pelvis construct between 2011 and 2021 at 2 centers were included and divided into 2 groups according to the surgical technique (BFC or SPF). Gender, age, main deformity region, etiology, preoperative and postoperative main curve magnitude and pelvic obliquity, surgery time, estimated blood loss and transfusion rates, length of hospital stay, the magnitude of main curve and pelvic obliquity correction, and early complications were compared. Quantitative data were compared through ANOVA or Mann-Whitney test. Analysis of qualitative outcomes was performed through Fisher exact test and logistic regressions. Kruskal-Wallis test was used to compare complications between groups. RESULTS: Eighty-nine NMS patients were included: 48 in the SPF group and 41 in the BFC group. Surgery time (203 vs. 241 min), rate (32 vs. 52%) and severity of complications, unplanned returns to the operating room (15 vs. 39%), estimated blood loss (179 vs. 364 cc), and transfusion rates (27 vs. 73%) were lower in the BFC group ( P <0.05). There were no significant differences in age, maturity stage, preoperative curve magnitude, preoperative pelvic obliquity and postoperative curve, and pelvic obliquity correction between groups. CONCLUSIONS: BFC may be a safer and less invasive option for NMS surgical treatment, resulting in similar curve corrections while significantly decreasing the number and severity of complications as well as intraoperative blood loss when compared with SPF. LEVEL OF EVIDENCE: Level -lll.

Prediction Model for Identifying Computational Phenotypes of Children with Cerebral Palsy Needing Neurotoxin Treatments.

Factors associated with neurotoxin treatments in children with cerebral palsy (CP) are poorly studied. We developed and externally validated a prediction model to identify the prognostic phenotype of children with CP who require neurotoxin injections. We conducted a longitudinal, international, multicenter, double-blind descriptive study of 165 children with CP (mean age 16.5 ± 1.2 years, range 12−18 years) with and without neurotoxin treatments. We collected functional and clinical data from 2005 to 2020, entered them into the BTX-PredictMed machine-learning model, and followed the guidelines, "Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis". In the univariate analysis, neuromuscular scoliosis (p = 0.0014), equines foot (p < 0.001) and type of etiology (prenatal > peri/postnatal causes, p = 0.05) were linked with neurotoxin treatments. In the multivariate analysis, upper limbs (p < 0.001) and trunk muscle tone disorders (p = 0.02), the presence of spasticity (p = 0.01), dystonia (p = 0.004), and hip dysplasia (p = 0.005) were strongly associated with neurotoxin injections; and the average accuracy, sensitivity, and specificity was 75%. These results have helped us identify, with good accuracy, the clinical features of prognostic phenotypes of subjects likely to require neurotoxin injections.

Predicting osteoarthritis in adults using statistical data mining and machine learning.

Background: Osteoarthritis (OA) has traditionally been considered a disease of older adults (⩾65 years old), but it may appear in younger adults. However, the risk factors for OA in younger adults need to be further evaluated. Objectives: To develop a prediction model for identifying risk factors of OA in subjects aged 20-50 years and compare the performance of different machine learning models. Methods: We included data from 52,512 participants of the National Health and Nutrition Examination Survey; of those, we analyzed only subjects aged 20-50 years (n = 19,133), with or without OA. The supervised machine learning model 'Deep PredictMed' based on logistic regression, deep neural network (DNN), and support vector machine was used for identifying demographic and personal characteristics that are associated with OA. Finally, we compared the performance of the different models. Results: Being a female (p < 0.001), older age (p < 0.001), a smoker (p < 0.001), higher body mass index (p < 0.001), high blood pressure (p < 0.001), race/ethnicity (lowest risk among Mexican Americans, p = 0.01), and physical and mental limitations (p < 0.001) were associated with having OA. Best predictive performance yielded a 75% area under the receiver operating characteristic curve. Conclusion: Sex (female), age (older), smoking (yes), body mass index (higher), blood pressure (high), race/ethnicity, and physical and mental limitations are risk factors for having OA in adults aged 20-50 years. The best predictive performance was achieved using DNN algorithms.

Patient-specific rods for thoracic kyphosis correction in adolescent idiopathic scoliosis surgery: Preliminary results.

INTRODUCTION: Restoring a degree of kyphosis consistent with good sagittal alignment of the spine is a key concern when performing surgery to correct adolescent idiopathic scoliosis (AIS). The objective of this study was to assess the preliminary outcomes of posterior fusion for AIS using patient-specific rods that were pre-contoured based on pelvic incidence. The primary evaluation criterion was thoracic kyphosis at last follow-up. HYPOTHESIS: The use of pre-bent patient-specific rods has a favourable effect on thoracic kyphosis at last follow-up. MATERIAL AND METHODS: A total of 37 patients with AIS, including 17 with hypokyphosis, managed with patient-specific rods were included in a prospective study. The rod contouring angles were based on predefined pelvic incidence criteria (25° to 40° for the rod on the convex side and the same value plus 10° for the rod on the concave side). Thoracic kyphosis was assessed before surgery and at last follow-up, after 12-36 months (mean, 19 months). Student's t test was applied to compare means. Multivariate linear regression analysis was performed. RESULTS: At last follow-up, the mean increase in kyphosis was 14° and was comparable to the planned increase (mean difference=0, p=0.85). Factors associated with kyphosis at last follow-up were the concave rod contouring angle and the pre-operative kyphotic angle of the thoracic segment to be instrumented (p<0.05). Mean differences between kyphosis of the instrumented thoracic segment at last follow-up and target kyphosis were -5° in the subgroup with hypokyphosis (<20°) before surgery and +4° in the subgroup with normal kyphosis before surgery. CONCLUSION: With patient-specific rods, kyphosis at last follow-up was close to the target value. Predictors of kyphosis at last follow-up were the concave rod contouring angle and pre-operative kyphotic angle of the thoracic segment to be instrumented. Over-contouring of the concave rod seems necessary in patients with preoperative hypokyphosis but not in patients with normal kyphosis. LEVEL OF EVIDENCE: III, prospective non-comparative study.

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

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.

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

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.

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

Why a P-Value is Not Enough.

BACKGROUND: All doctors know that P-value<0.05 is "the Graal," but publications require further parameters [odds ratios, confidence interval (CI), etc.] to better analyze scientific data. AIM: The aim of this study was to present P-values, CI, and common effect-sizes (Cohen d, odds ratio, and various coefficients) in a simple way. DESCRIPTION: The P-value is the probability, when the null hypothesis is true (eg, no difference or no association), of obtaining a result equal to or more extreme than what we actually observed. Simplistically, P-value quantifies the probability that the result is due to chance. It does not measure how big the association or the difference is. The CI on a value describes the probability that the true value is within a given range. A 95% CI means that the CI covers the true value in 95 of 100 performed studies. The test is significant if the CI does not include the null hypothesized difference or association (eg, 0 for difference). The effect-sizes are quantitative measures of the strength of a difference or association. If the P-value is <0.05 but the effect size is very low, the test is statistically significant but probably, clinically not so. CONCLUSIONS: Scientific publications require more parameters than a P-value. Statistical results should also include effect sizes and CIs to allow for a more complete, honest, and useful interpretation of scientific findings.

Conservative treatment of a pathologic fracture of the scaphoid bone in a child: A case report.

RATIONALE: Tumors of the scaphoid are rare, and some can cause pathological fractures. No cases of pathological fractures of the scaphoid have been reported in children. The most common treatment for pathologic fractures of the scaphoid bone associated with a benign lesion in adults is surgical, with intralesional curettage associated with autologous bone grafting and internal fixation. PATIENT CONCERNS: A 10-year-old boy presented with wrist pain after falling from his height. DIAGNOSES: X-ray, CT-scan and MRI showed a pathological undisplaced fracture of the scaphoid on a benign lytic lesion. INTERVENTIONS: The arm was immobilized in a below-elbow cast. OUTCOMES: The fracture healed within 4 months of immobilization. 3 years after the fracture, the functional status was normal, and the lytic lesion could not be seen on radiographs. LESSONS: Retrospectively, the most probable etiology was a ganglion cyst. Our case suggests that some pathological fractures of the scaphoid may not need surgery, especially not in children.

Validation of a Clinical Prediction Model for the Development of Neuromuscular Scoliosis: A Multinational Study.

BACKGROUND: The objective of this study was to evaluate the performance of a clinical prediction model of neuromuscular scoliosis via external validation. METHODS: We analyzed a series of 120 patients (mean age ± standard deviation, 15.7 ± 1.8 years; range: 12 to 18 years) with cerebral palsy, severe motor disorders, and cognitive impairment with and without neuromuscular scoliosis treated in two specialized units (70 patients from Nice, France, and 50 patients from Lublin, Poland) in a cross-sectional, double-blind study. Data on etiology, diagnosis, functional assessments, type of spasticity, epilepsy, scoliosis, and clinical history were collected prospectively between 2005 and 2015. Fisher's exact test and multiple logistic regressions were used to identify influential factors for developing spinal deformity. Thus, we applied a predictive model based on a logistic regression algorithm to predict the probability of scoliosis onset for new patients. RESULTS: Children with truncal tone disorders (P = Multivariate logistic regression highlighted previous hip surgery (P = 0.002 ≈ 0.005), intractable epilepsy (P = 0.01 ≈ 0.04) and female gender (0.07) as influent factors in the two cohorts. Average accuracy, sensitivity, and specificity of the predictive model were 74%. CONCLUSIONS: We validated a prediction model of neuromuscular scoliosis. In cerebral palsy subjects with the previouslymentioned predictors of scoliosis, the frequency of clinical examinations of spine and spinal x-ray should be increased to easily identify candidates for treatment.

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

This study aims to identify the risk factors leading to the development of severe scoliosis among children with cerebral palsy. A cross-sectional descriptive study of 70 children (aged 12-18 years) with severe spastic and/or dystonic cerebral palsy treated in a single specialist unit is described. Statistical analysis included Fisher exact test and logistic regression analysis to identify risk factors. Severe scoliosis is more likely to occur in patients with intractable epilepsy ( P = .008), poor gross motor functional assessment scores ( P = .018), limb spasticity ( P = .045), a history of previous hip surgery ( P = .048), and nonambulatory patients ( P = .013). Logistic regression model confirms the major risk factors are previous hip surgery ( P = .001), moderate to severe epilepsy ( P = .007), and female gender ( P = .03). History of previous hip surgery, intractable epilepsy, and female gender are predictors of developing severe scoliosis in children with cerebral palsy. This knowledge should aid in the early diagnosis of scoliosis and timely referral to specialist services.