Stability of general cognition in children born extremely preterm as they grow older: good or bad news?

Doyle, Lex W.; Anderson, Peter J.

doi:10.1136/archdischild-2017-313987

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…Another limitation of our study was the relatively high attrition rate at age 15 years. One of the main challenges with longitudinal studies is retention of participants ( Doyle and Anderson, 2018 ), and our retention rate of 58% at age 15 is consistent with other studies that have followed preterm cohorts into their teenage years ( Johnson et al, 2019 ). This loss was mitigated somewhat by including data from the larger sample at age 10.…”

Section: Discussionsupporting

confidence: 85%

Association of prenatal modifiable risk factors with attention-deficit hyperactivity disorder outcomes at age 10 and 15 in an extremely low gestational age cohort

Cochran¹,

Jensen²,

Frazier³

et al. 2022

Front. Hum. Neurosci.

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BackgroundThe increased risk of developing attention-deficit hyperactivity disorder (ADHD) in extremely preterm infants is well-documented. Better understanding of perinatal risk factors, particularly those that are modifiable, can inform prevention efforts.MethodsWe examined data from the Extremely Low Gestational Age Newborns (ELGAN) Study. Participants were screened for ADHD at age 10 with the Child Symptom Inventory-4 (N = 734) and assessed at age 15 with a structured diagnostic interview (MINI-KID) to evaluate for the diagnosis of ADHD (N = 575). We studied associations of pre-pregnancy maternal body mass index (BMI), pregestational and/or gestational diabetes, maternal smoking during pregnancy (MSDP), and hypertensive disorders of pregnancy (HDP) with 10-year and 15-year ADHD outcomes. Relative risks were calculated using Poisson regression models with robust error variance, adjusted for maternal age, maternal educational status, use of food stamps, public insurance status, marital status at birth, and family history of ADHD. We defined ADHD as a positive screen on the CSI-4 at age 10 and/or meeting DSM-5 criteria at age 15 on the MINI-KID. We evaluated the robustness of the associations to broadening or restricting the definition of ADHD. We limited the analysis to individuals with IQ ≥ 70 to decrease confounding by cognitive functioning. We evaluated interactions between maternal BMI and diabetes status. We assessed for mediation of risk increase by alterations in inflammatory or neurotrophic protein levels in the first week of life.ResultsElevated maternal BMI and maternal diabetes were each associated with a 55–65% increase in risk of ADHD, with evidence of both additive and multiplicative interactions between the two exposures. MSDP and HDP were not associated with the risk of ADHD outcomes. There was some evidence for association of ADHD outcomes with high levels of inflammatory proteins or moderate levels of neurotrophic proteins, but there was no evidence that these mediated the risk associated with maternal BMI or diabetes.ConclusionContrary to previous population-based studies, MSDP and HDP did not predict ADHD outcomes in this extremely preterm cohort, but elevated maternal pre-pregnancy BMI, maternal diabetes, and perinatal inflammatory markers were associated with increased risk of ADHD at age 10 and/or 15, with positive interaction between pre-pregnancy BMI and maternal diabetes.

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Section: Discussionsupporting

confidence: 85%

Association of prenatal modifiable risk factors with attention-deficit hyperactivity disorder outcomes at age 10 and 15 in an extremely low gestational age cohort

Cochran¹,

Jensen²,

Frazier³

et al. 2022

Front. Hum. Neurosci.

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“…In this study, we jointly predicted abnormal neurodevelopmental outcomes at 2 years of age in very preterm infants using neuroimaging and clinical data collected at term-equivalent age. While some studies have shown that neurocognitive development do not stabilize until adolescence, more recent studies have shown that general cognition in extremely preterm infants remains stable from 2 years of age until adolescence [47][48][49] , and valuable information can still be obtained through standardized cognitive testing at age 24 months corrected age. For example, a cohort study of extremely preterm infants showed that standardized cognitive scores at 24 months corrected age explained 38% of the variance in IQ scores at age 8-9 in extremely preterm infants 50 .…”

Section: Discussionmentioning

confidence: 99%

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants

Wang

et al. 2020

Sci Rep

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Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodevelopmental deficits. Deep learning models typically require training on large datasets, and unfortunately, large neuroimaging datasets with clinical outcome annotations are typically limited, especially in neonates. Transfer learning represents an important step to solve the fundamental problem of insufficient training data in deep learning. In this work, we developed a multi-task, multi-stage deep transfer learning framework using the fusion of brain connectome and clinical data for early joint prediction of multiple abnormal neurodevelopmental (cognitive, language and motor) outcomes at 2 years corrected age in very preterm infants. The proposed framework maximizes the value of both available annotated and non-annotated data in model training by performing both supervised and unsupervised learning. We first pre-trained a deep neural network prototype in a supervised fashion using 884 older children and adult subjects, and then re-trained this prototype using 291 neonatal subjects without supervision. Finally, we fine-tuned and validated the pre-trained model using 33 preterm infants. Our proposed model identified very preterm infants at high-risk for cognitive, language, and motor deficits at 2 years corrected age with an area under the receiver operating characteristic curve of 0.86, 0.66 and 0.84, respectively. Employing such a deep learning model, once externally validated, may facilitate risk stratification at term-equivalent age for early identification of long-term neurodevelopmental deficits and targeted early interventions to improve clinical outcomes in very preterm infants.

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“…Based on our study design and results we find it important to take into account that time points and time between cognitive assessments can affect findings in cognitive follow-up of preterm children. Of equal importance are longitudinal studies, and maintaining high retention throughout follow-up (Doyle and Anderson, 2018). Recently, the longitudinal EPI Cure study showed that cognitive test score in infancy and early childhood reflect early adult outcomes (Linsell et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Cognitive Development Trajectories in Preterm Children With Very Low Birth Weight Longitudinally Followed Until 11 Years of Age

Stålnacke¹,

Tessma²,

Böhm³

et al. 2019

Front. Physiol.

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Background: There is a high prevalence of cognitive dysfunction in very low birthweight (500–1250 g) infants (VLBW). Understanding long-term risk factors associated with cognitive development in preterm children requires longitudinal characterization. Thus, follow-up evaluations, including identification of risks and resilience influences–are important to promote health and cognitive abilities of children born preterm. Aim: To examine changes in cognitive development from birth until 11 years of age in preterm children with very low birthweight. Methods: 24 VLBW infants, at the Karolinska University Hospital, Stockholm, were assessed with regards to cognitive functioning at three times during development at 18 months, 5 and 11 years of age using standardized tests. Longitudinal data were analyzed using Generalized Estimating Equation (GEE) univariate and multivariate models. Results: The follow-up rate was 100%. Level of cognitive functioning at 18 months and at 11 years was similar. Females had higher cognitive scores than males at all three timepoints. We found that intraventricular hemorrhage (IVH) and prolonged invasive ventilatory support (>7 days) had a negative effect on cognitive functioning. Higher levels of parental education had a favorable influence on cognitive functioning over time. Conclusion: Level of cognitive development at 18 months was highly predictive of level of cognitive function at 11 years of age and differences in assessment scores between male and female VLBW infants persisted. Additional longitudinal studies, performed before school entry and across childhood, are needed to further elucidate the cognitive trajectories of preterm children.

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Stability of general cognition in children born extremely preterm as they grow older: good or bad news?

Cited by 5 publications

References 8 publications

Association of prenatal modifiable risk factors with attention-deficit hyperactivity disorder outcomes at age 10 and 15 in an extremely low gestational age cohort

Association of prenatal modifiable risk factors with attention-deficit hyperactivity disorder outcomes at age 10 and 15 in an extremely low gestational age cohort

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants

Cognitive Development Trajectories in Preterm Children With Very Low Birth Weight Longitudinally Followed Until 11 Years of Age

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