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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Bruggink, JLM; Einspieler, C; Butcher, PR; Van Braeckel, KNJA; Prechtl, HFR; Bos, AF.
The quality of the early motor repertoire in preterm infants predicts minor neurologic dysfunction at school age.
J PEDIAT. 2008; 153(1): 32-39. Doi: 10.1016/j.jpeds.2007.12.047
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Co-Autor*innen der Med Uni Graz
Einspieler Christa
Prechtl Heinz
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Abstract:
OBJECTIVE: The quality of a child's motor repertoire at age 3 to 4 months postterm is predictive of later cerebral palsy (CP). Its predictive power for minor neurologic dysfunction (MND) is unclear. This study aimed to investigate the predictive value of the quality of the early motor repertoire for the development of MND at school age. STUDY DESIGN: We assessed the motor repertoire from video recordings made at 6 to 24 weeks postterm in 82 preterm infants (mean gestational age, 29.7 +/- 1.9 weeks; mean birth weight, 1183 +/- 302 g). At age 7 to 11 years, Touwen's neurologic examination was performed, and the children were classified as normal (n = 49; 60%), MND (n = 18; 22%), or CP (n = 15; 18%). RESULTS: Multiple logistic regression analysis showed that the quality of fidgety movements (FMs) and the quality of the concurrent motor repertoire had independent prognostic value for MND at school age. Abnormal FMs evolved into MND in 64% of the children. Nine of the 28 children with normal FMs and an abnormal concurrent motor repertoire developed abnormally (32%). Only 1 child of the 21 children with normal FMs and a normal concurrent motor repertoire developed MND (5%). CONCLUSIONS: Assessment of the quality of the early motor repertoire can accurately identify individual infants at high and low risk for MND at school age.
Find related publications in this database (using NLM MeSH Indexing)
Adrenal Cortex Hormones - adverse effects
Child -
Female -
Humans -
Infant -
Infant, Newborn -
Infant, Premature -
Male -
Maternal Exposure -
Motor Activity -
Motor Neurons - metabolism
Nervous System Diseases - diagnosis
Neurologic Examination -
Prognosis -
Regression Analysis -

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