| Literature DB >> 27453749 |
O C Rogoveanu1, N C Tuțescu2, D Kamal1, D O Alexandru3, C Kamal4, L Streba5, M R Trăistaru1.
Abstract
Cerebral palsy is the most common cause of developing neuro-motor disability in children, in many cases, the triggering cause remaining unknown. Quadriplegia is the most severe spastic cerebral palsy, characterized by severe mental retardation and bi-pyramidal syndrome. The purpose of this paper was to demonstrate the importance of knowing the risk factors and the psychosomatic ones, determining to what extent they influence the functional evolution in patients diagnosed with spastic quadriplegia. 23 children diagnosed with spastic quadriplegia were included in the study, being aged between 1 year and half and 12 years. Patients were assessed at baseline (T1), at one year (T2) and after two years at the end of the study (T3). Patients received a comprehensive rehabilitation program for the motor and sensory deficits throughout the study. Initially, a comprehensive evaluation (etiopathogenic, clinical and functional) that started from a thorough medical history of children (the older ones), was conducted but chose parents to identify the risk factors, and a complete physical exam. At each assessment, joint and muscle balance was conducted. To assess functionality, the gross motor function classification systems (GMFCS) and manual ability (MACS) were used. Many risk factors that were classified according to the timeline in prenatal factors, perinatal and postnatal, were identified from a thorough history. A direct correlation was noticed between the decrease of coarse functionality and manual ability, both initially and in dynamic and low APGAR scores, low gestational age, low birth weight and a higher body mass index of the mother. A direct link was observed between the gross motor function and the manual ability. A significant improvement in the MACS score was noticed in patients with a better GMFCS score.Entities:
Keywords: GMFCS; MACS; risk factors; spastic quadriplegia
Mesh:
Year: 2016 PMID: 27453749 PMCID: PMC4863509
Source DB: PubMed Journal: J Med Life ISSN: 1844-122X
Demographics of the studied group
| Male | Female |
| 8 (34.78%) | 15 (65.22%) |
| Urban | Rural |
| 18 (78.26%) | 5 (21.74%) |
Correlations between risk factors and GMFCS and MACS scores
| APGAR | Gestational age | Fetal weight | BMI | |
|---|---|---|---|---|
| GMFCS T1 | -0.528 (0.011) | -0.627 (0.002) | -0.502 (0.016) | 0.481 (0.021) |
| GMFCS T2 | -0.493 (0.018) | -0.579 (0.004) | -0.426 (0.044) | 0.442 (0.036) |
| GMFCS T3 | -0.457 (0.030) | -0.558 (0.006) | -0.507 (0.015) | 0.372 (0.081) |
| MACS T1 | -0.523 (0.011) | -0.639 (0.001) | -0.491 (0.019) | 0.482 (0.021) |
| MACS T2 | -0.417 (0.049) | -0.496 (0.017) | -0.417 (0.049) | 0.245 (0.257) |
| MACS T3 | -0.517 (0.012) | -0.585 (0.004) | -0.363 (0.089) | 0.431 (0.041) |
Correlations between GMFCS and MACS scores
| Parameter 1 | Parameter 2 | rho Spearman | p value |
| GMFCS T1 | MACS T1 | 0.999 | <0.0001 |
|---|---|---|---|
| GMFCS T2 | MACS T2 | 0.883 | <0.0002 |
| GMFCS T3 | MACS T3 | 0.860 | <0.0003 |