Neurocognitive and Motor Functions in Biliary Atresia Patients: A Cross-sectional, Prospective National Cohort Study.

OBJECTIVES: The aim of the study was to evaluate the neurocognitive and motor development of biliary atresia (BA) patients in childhood and adolescence and to identify risk factors for impaired outcome. METHODS: We invited all BA patients between ages 1 and 20 years followed up at Helsinki University Children's Hospital in Finland between 1 January 2019 to 31 January 2020 to participate. All participants underwent age-appropriate validated neurocognitive tests. Participants between 3.0 and 16.9 years of age were assessed with the Movement Assessment Battery for children, version 2. Guardians of participants between ages 5 and 17 years filled the Five-to-Fifteen-Revised (5-15R) parental questionnaire. RESULTS: The mean (±standard deviation [SD]) total intelligence quotient (IQ) of the 39 participants was 91 ±â€Š15, lower compared with test norms (mean IQ 100 ±â€Š15, P < 0.01). Earlier clearance of jaundice (COJ) had a positive effect on mean (±SD) total IQ (COJ <3 months 96 ±â€Š13 vs COJ ≥3 months post-portoenterostomy 84 ±â€Š13, P < 0.05). Out of 30 participants assessed, 13 (43%) were either at risk or fulfilled the criteria for impaired motor development. Guardians reported elevated rates of functional difficulties affecting everyday life. There were no significant differences between native liver and liver transplanted (16/41%) groups. CONCLUSIONS: IQ is moderately, and motor scores markedly impaired in BA patients compared with normative data. Standardised cognitive and motor assessment before school-age for all BA patients is advisable to identify individuals in need of additional support.

Neonatal Intestinal Failure Is Independently Associated With Impaired Cognitive Development Later in Childhood.

OBJECTIVE: The impact of pediatric intestinal failure (IF) on neurodevelopment beyond infancy has not been systematically studied. Our aim was to evaluate cognitive and motor impairment and to identify risk factors for adverse outcomes among children with IF. METHODS: We conducted a cross-sectional single-center study at the Helsinki University Children's Hospital. Patients with IF with >60 days of parental nutrition (PN) dependency aged between 3 and 16 years (n = 40) were invited to participate. The cognitive and motor skills were evaluated using validated tests: Wechsler Preschool and Primary Scale of Intelligence, 3rd edition, Wechsler Intelligence Scale for Children, 4th edition, and Movement Assessment Battery for Children, 2nd edition. RESULTS: All the patients attending the study tests (n = 30, males = 24) were included. Their median age, gestational age, and birth weight was 7.5 (range 3-16) years, 35 (interquartile range [IQR] 28-38) weeks and 2238 (IQR 1040-3288) grams, respectively. Median duration of PN was 13 (IQR 5-37) months and 9 patients were currently on PN. Median intelligence quotient was 78 (IQR 65-91) and 10 (35%) patients had an intelligence quotient under 70 (-2 standard deviation). Significant motor impairment was detected in 10 patients (36%) and milder difficulties in 8 (28%). Adverse cognitive outcome was associated with neonatal short bowel syndrome, number of interventions under general anesthesia, and length of inpatient status, whereas adverse motor outcome was associated with prematurity. CONCLUSION: Clinically significant cognitive and motor impairments are alarmingly common among neonatal patients with IF. We recommend early neurodevelopmental follow-up for all children with IF.

Intelligent wearable allows out-of-the-lab tracking of developing motor abilities in infants.

Background: Early neurodevelopmental care needs better, effective and objective solutions for assessing infants' motor abilities. Novel wearable technology opens possibilities for characterizing spontaneous movement behavior. This work seeks to construct and validate a generalizable, scalable, and effective method to measure infants' spontaneous motor abilities across all motor milestones from lying supine to fluent walking. Methods: A multi-sensor infant wearable was constructed, and 59 infants (age 5-19 months) were recorded during their spontaneous play. A novel gross motor description scheme was used for human visual classification of postures and movements at a second-level time resolution. A deep learning -based classifier was then trained to mimic human annotations, and aggregated recording-level outputs were used to provide posture- and movement-specific developmental trajectories, which enabled more holistic assessments of motor maturity. Results: Recordings were technically successful in all infants, and the algorithmic analysis showed human-equivalent-level accuracy in quantifying the observed postures and movements. The aggregated recordings were used to train an algorithm for predicting a novel neurodevelopmental measure, Baba Infant Motor Score (BIMS). This index estimates maturity of infants' motor abilities, and it correlates very strongly (Pearson's r = 0.89, p < 1e-20) to the chronological age of the infant. Conclusions: The results show that out-of-hospital assessment of infants' motor ability is possible using a multi-sensor wearable. The algorithmic analysis provides metrics of motility that are transparent, objective, intuitively interpretable, and they link strongly to infants' age. Such a solution could be automated and scaled to a global extent, holding promise for functional benchmarking in individualized patient care or early intervention trials.

Recording activity in proximal muscle networks with surface EMG in assessing infant motor development.

OBJECTIVE: To develop methods for recording and analysing infant's proximal muscle activations. METHODS: Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks. RESULTS: The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants.The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance. CONCLUSIONS: The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility. SIGNIFICANCE: Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.

The Attention and Executive Function Rating Inventory (ATTEX): Psychometric properties and clinical utility in diagnosing ADHD subtypes.

This study presents a new inventory, the Attention and Executive Function Rating Inventory (ATTEX), and examines the psychometric properties and the clinical utility of ATTEX in identifying the attention deficit hyperactivity disorder combined type (ADHD-C) and the ADHD predominantly inattentive type (ADHD-I) in school environments. A normative sample of Finnish 7- to 15-year-old children and adolescents (N = 701) and a clinical sample consisting of children with ADHD-C (N = 190) and ADHD-I (N = 25) were examined with the ATTEX and the ADHD Rating Scale-IV. The ATTEX and its scales had good internal consistency reliability (0.67-0.98) and criterion validity (0.68-0.95). Normative data was provided for the total normative sample and for boys and girls separately. Gender differences were noted in the ATTEX scores, boys having consistently higher scores on all ATTEX scales. The effect of age was significant only for one of the ten scales, the Motor hyperactivity scale, 7-year-olds having more problems of hyperactivity than 14-year-olds. Lower parent education level and the child's learning difficulties were related to higher ratings of EF problems in ATTEX. When different cutoff scores for boys and girls were applied, ATTEX was sensitive in identifying children with attention deficit disorders. In addition, ATTEX was accurate in differentiating children with ADHD-I from children with ADHD-C. In this Finnish sample, ATTEX showed solid psychometric properties and could be used as a reliable tool in the diagnostic evaluation of ADHD-C and ADHD-I.

Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors.

Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.