Perinatal Risk Factors in Motor Development

Overview

The aim of this study is to analyze the effect of preterm gestational age, birth weight and perinatal risks factors on gross motor development of preterm infants. We will compare the data of infants evaluated by the Alberta Infant Motor Scale (AIMS) and the Perinatal Risk Inventory (PERI) in an Infant Development and Early Intervention Center (IDEIC).

An assessment of the infants' gross motor development will be carried out at admission, of IDEIC following the AIMS scale and bearing in mind their corrected age. Importantly, the trimester according to their corrected age was also recorded. The gestational age of each infant will be recorded and used to group participants according to the following classification: late preterm newborn infant (LPNI; born between 34+1 and 36+6 weeks of gestation); moderate preterm newborn infant (MPNI; born between 32+1 to 34 weeks of gestation); very preterm newborn infant (VPNI; born between 28 to 32 weeks of gestation); and extreme preterm newborn infant (EPNI; born before 28 weeks of gestation). The birth weight will be recorded and the infants will be grouped according to the following classification: newborns with adequate birth (birth weight of \>2500 g), low birth weight (LBW; \<2500 g and \>1500 g); very low birth weight (VLBW; \<2500 g and \>1000 g), and extreme low birth weight (ELBW; \<1000 g). The infants will be assessed by the PERI test accounting for their discharge medical records. The infants will be then classified according to the biological risk level, in low, moderate and high risk. Both the PERI and the AIMS test were assessed by three physiotherapists from the IDEIC with 10 to 20 years of experience. Afterwards data will be analyzed using the Statistical Package for the Social Sciences Statistics (IBM SPSS) software for Windows version 22.0. From all data collected as described in the brief summary, descriptive analysis and correlations between variables will be performed. Samples will be classified using descriptive and frequency analysis. One-factor ANOVA, bivariate correlations will be carried out. Correlations between variables will be evaluated using Pearson's coefficient (bivariate correlation) or Spearman's coefficient (rank correlation). Frequencies analysis, square Chi test and backwards regression analysis will be used when appropriate. AIMS direct scores will be standardized by converting them into Z scores. AIMS standard mean and deviation by age and gender will be used.

Conditions

Eligibility

Locations (1)

Outcomes

Central Contacts