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Neurological assessment of preterm infants for predicting neuromotor status at 2 years: results from the LIFT cohort
OBJECTIVE: To develop a predictive risk stratification model for the identification of preterm infants at risk of 2-year suboptimal neuromotor status. DESIGN: Population-based observational study. SETTING: Regional preterm infant follow-up programme (Loire Infant Follow-up Team (LIFT) cohort) implem...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3586154/ https://www.ncbi.nlm.nih.gov/pubmed/23435797 http://dx.doi.org/10.1136/bmjopen-2012-002431 |
Sumario: | OBJECTIVE: To develop a predictive risk stratification model for the identification of preterm infants at risk of 2-year suboptimal neuromotor status. DESIGN: Population-based observational study. SETTING: Regional preterm infant follow-up programme (Loire Infant Follow-up Team (LIFT) cohort) implemented in 2003. PARTICIPANTS: 4030 preterm infants were enrolled in the LIFT cohort, and examined by neonatologists using a modified version of the Amiel-Tison neurological assessment tool. MAIN OUTCOME CRITERIA: 2 year neuromotor status based on clinical examinations was conducted by trained paediatricians and parents’ responses to the Ages and Stages Questionnaire were reported. RESULTS: At 2 years of corrected age, 3321 preterm infants were examined, and suboptimal neuromotor status was found in 355 (10.7%). The study population was divided into training and validation sets. In the training set, 13 neonatal neurological items were associated with a 2-year suboptimal neuromotor status. Having at least one abnormal item was defined as an abnormal neurological status at term. In the validation set, these data predicted a 2-year suboptimal neuromotor status with a sensitivity of 0.55 (95% CI 0.47 to 0.62) and a specificity of 0.65 (95% CI 0.62 to 0.67). Two predictive risk stratification trees were built using the training set, which were based on the neurological assessment at term along with either gestational age or severe cranial lesions or birth weight. Using the validation set, the first tree identified a subgroup with a relatively low risk of suboptimal neuromotor status (3%), representing 32% of infants, and the second tree identified a subgroup with a risk of 5%, representing 42% of infants. CONCLUSION: A normal neurological assessment at term allows the identification of a subgroup of preterm infants with a lower risk of non-optimal neuromotor development at 2 years. |
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