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Prediction of Recovery in Spastic Cerebral Palsy.
Until now, for children with cerebral palsy (CP) , diagnostic and some prognostic predictive machine learning studies have been conducted, but prognostic studies targeted specific milestone according to specific gross motor function measure (GMFCS) levels; such as walking and running predictors at GMFCS II and III and GMFCS II respectively, and not covered specific types of cerebral palsy. Predictions studies were limited by the lack of specificity of child and family characteristics was not taken into the account prospectively. It is therefore the utmost need to support clinical decision making by predicting the recovery in spastic cerebral palsy. Recovery predictive factors can play an important role for this purpose. Thus, this study aims to predict the recovery in spastic cerebral palsy according to all GMFCS level by means of a prediction index/model.
Details
| Lead sponsor | Riphah International University |
|---|---|
| Status | UNKNOWN |
| Enrolment | 125 |
| Start date | Mon Jun 14 2021 00:00:00 GMT+0000 (Coordinated Universal Time) |
| Completion | Sat Apr 30 2022 00:00:00 GMT+0000 (Coordinated Universal Time) |
Conditions
- Spastic Cerebral Palsy
Interventions
- Standardized treatment protocol for cerebral palsy
Countries
Pakistan