BACKGROUND AND AIMS: The Bayley scales of infant development (BSID) is the most widely used measure to assess neurodevelopment of very preterm (gestational age ≤32 weeks) and very low birth weight (VLBW, ≤1500 g) infants in the first three years of life. This meta-analysis determines the predictive value of the mental developmental index (MDI) and the psychomotor developmental index (PDI)/motor composite, collectively referred to as Bayley motor scale, of the BSID-I, -II and Bayley-III for later cognitive and motor functioning in very preterm/VLBW children. METHODS: Cochrane Library, PubMed, PsychINFO and CINAHL were searched for English-language peer-reviewed studies published before March 2013. Studies were included if they reported odds ratios or correlations between the MDI or Bayley motor scale scores obtained in the first three years of life, and standardized cognitive or motor assessment obtained later in life in very preterm/VLBW children. Meta-analytic methods were applied to aggregate available data. RESULTS: A total of 16 studies met inclusion criteria. Across 14 studies (n=1330 children), MDI scores were strongly predictive for later cognitive functioning, r=0.61 (95% CI: 0.57-0.64), explained variance 37%, p<.001. The relationship between MDI scores and later cognitive function was not mediated by birth weight (p=.56), gestational age (p=.70), and time interval between assessments (p=.55). Across five studies (n=555 children), Bayley motor scale scores were moderately predictive for later motor function, r=0.34 (95% CI: 0.26-0.42), explained variance 12%, p<.001. CONCLUSIONS: In very preterm/VLBW children, MDI scores explain 37% of the variance in later cognitive functioning, whereas Bayley motor scale scores explain 12% of later motor function. Thus a large proportion of the variance remains unexplained, underlining the importance of enhancing prediction of developmental delay in very preterm children.
BACKGROUND AND AIMS: The Bayley scales of infant development (BSID) is the most widely used measure to assess neurodevelopment of very preterm (gestational age ≤32 weeks) and very low birth weight (VLBW, ≤1500 g) infants in the first three years of life. This meta-analysis determines the predictive value of the mental developmental index (MDI) and the psychomotor developmental index (PDI)/motor composite, collectively referred to as Bayley motor scale, of the BSID-I, -II and Bayley-III for later cognitive and motor functioning in very preterm/VLBW children. METHODS: Cochrane Library, PubMed, PsychINFO and CINAHL were searched for English-language peer-reviewed studies published before March 2013. Studies were included if they reported odds ratios or correlations between the MDI or Bayley motor scale scores obtained in the first three years of life, and standardized cognitive or motor assessment obtained later in life in very preterm/VLBW children. Meta-analytic methods were applied to aggregate available data. RESULTS: A total of 16 studies met inclusion criteria. Across 14 studies (n=1330 children), MDI scores were strongly predictive for later cognitive functioning, r=0.61 (95% CI: 0.57-0.64), explained variance 37%, p<.001. The relationship between MDI scores and later cognitive function was not mediated by birth weight (p=.56), gestational age (p=.70), and time interval between assessments (p=.55). Across five studies (n=555 children), Bayley motor scale scores were moderately predictive for later motor function, r=0.34 (95% CI: 0.26-0.42), explained variance 12%, p<.001. CONCLUSIONS: In very preterm/VLBW children, MDI scores explain 37% of the variance in later cognitive functioning, whereas Bayley motor scale scores explain 12% of later motor function. Thus a large proportion of the variance remains unexplained, underlining the importance of enhancing prediction of developmental delay in very preterm children.
Authors: Noelle Younge; Ricki F Goldstein; Carla M Bann; Susan R Hintz; Ravi M Patel; P Brian Smith; Edward F Bell; Matthew A Rysavy; Andrea F Duncan; Betty R Vohr; Abhik Das; Ronald N Goldberg; Rosemary D Higgins; C Michael Cotten Journal: N Engl J Med Date: 2017-02-16 Impact factor: 91.245
Authors: Deborah J Watkins; Gamola Z Fortenberry; Brisa N Sánchez; Dana Boyd Barr; Parinya Panuwet; Lourdes Schnaas; Erika Osorio-Valencia; Maritsa Solano-González; Adrienne S Ettinger; Mauricio Hernández-Ávila; Howard Hu; Martha María Téllez-Rojo; John D Meeker Journal: Environ Res Date: 2016-02-27 Impact factor: 6.498
Authors: Lillian G Matthews; T E Inder; L Pascoe; K Kapur; K J Lee; B B Monson; L W Doyle; D K Thompson; P J Anderson Journal: Cerebellum Date: 2018-10 Impact factor: 3.847
Authors: Arin A Balalian; Robin M Whyatt; Xinhua Liu; Beverly J Insel; Virginia A Rauh; Julie Herbstman; Pam Factor-Litvak Journal: Environ Res Date: 2019-01-29 Impact factor: 6.498
Authors: Mandy B Belfort; Peter J Anderson; Victoria A Nowak; Katherine J Lee; Charlotte Molesworth; Deanne K Thompson; Lex W Doyle; Terrie E Inder Journal: J Pediatr Date: 2016-07-29 Impact factor: 4.406
Authors: Kristen E Gray; Kathleen A Kapp-Simon; Jacqueline R Starr; Brent R Collett; Erin R Wallace; Matthew L Speltz Journal: Dev Med Child Neurol Date: 2014-11-23 Impact factor: 5.449
Authors: Verena Walsh; Jennifer Valeska Elli Brown; Lisa M Askie; Nicholas D Embleton; William McGuire Journal: Cochrane Database Syst Rev Date: 2019-07-17