Publications by authors named "Adde Lars"

Background: Exposure to alcohol and/or other addictive drugs in pregnancy is a documented risk factor for neurological impairment. We aimed to assess neurodevelopmental outcome at two years of age in infants exposed to prenatal alcohol and/or other addictive drugs and to examine the predictive value of early motor assessment.

Methods: This was a follow-up at two years of age in the prospective cohort study Children Exposed to Alcohol and/or Drugs in Intrauterine Life (CEADIL).

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Background: General Movement Assessment (GMA) is recommended for early detection of risk for cerebral palsy but requires trained clinical experts. We aimed to implement home- and hospital-based filming for remote GMA in a Norwegian high-risk infant cohort, as well as evaluating parents' experiences in filming their infant at home.

Methods: This knowledge translational study used a prospective cohort design including participants referred to neurodevelopmental follow-up across three sites in the Central Norway Regional Health Authority.

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Objective: The objective of this study was to investigate the influences on motor development in infants who are at low risk from Belgium, India, Norway, and the United States using the General Movement Assessment at 10-16 weeks postterm age.

Methods: This was a cross-sectional study of prospectively enrolled full-term infants at low risk (n = 186). Certified General Movement Assessment observers rated the fidgety movements, quality of the movement patterns, age-adequacy of the movement repertoire, postural patterns, movement character, and overall Motor Optimality Score-Revised (MOS-R).

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Background: A neurological assessment before discharge from the NICU would enable early targeted intervention to mitigate the risk and severity of cerebral palsy (CP) and neurodevelop-mental disability.

Objective: To assess the accuracy of general movements (GM) in the preterm and fidgety movement periods in predicting neurodevelopmental disability and cerebral palsy in very preterm infants (≤32 weeks gestational age) at 18-24 months corrected gestational age.

Study Design: Prospective cohort study.

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Importance: Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity.

Objective: To develop and assess the external validity of a novel deep learning-based method to predict CP based on videos of infants' spontaneous movements at 9 to 18 weeks' corrected age.

Design, Setting, And Participants: This prognostic study of a deep learning-based method to predict CP at a corrected age of 12 to 89 months involved 557 infants with a high risk of perinatal brain injury who were enrolled in previous studies conducted at 13 hospitals in Belgium, India, Norway, and the US between September 10, 2001, and October 25, 2018.

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Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants. In order to develop algorithms for automated prediction of later disorders, highly precise localization of segments and joints by infant pose estimation is required. Four types of convolutional neural networks were trained and evaluated on a novel infant pose dataset, covering the large variation in 1424 videos from a clinical international community.

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Objective: To evaluate the accuracy of neonatal MRI and general movements assessment (GMA) in predicting neurodevelopmental outcomes in infants with hypoxic-ischaemic encephalopathy (HIE).

Design: Secondary analyses of a randomised controlled trial (RCT).

Setting: Tertiary neonatal intensive care unit in India.

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Importance: Cerebral palsy (CP) is the most common childhood physical disability. Early intervention for children younger than 2 years with or at risk of CP is critical. Now that an evidence-based guideline for early accurate diagnosis of CP exists, there is a need to summarize effective, CP-specific early intervention and conduct new trials that harness plasticity to improve function and increase participation.

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Objectives: To determine whether videos taken by parents of their infants' spontaneous movements were in accordance with required standards in the In-Motion-App, and whether the videos could be remotely scored by a trained General Movement Assessment (GMA) observer. Additionally, to assess the feasibility of using home-based video recordings for automated tracking of spontaneous movements, and to examine parents' perceptions and experiences of taking videos in their homes.

Design: The study was a multi-centre prospective observational study.

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Aim: To investigate the inter- and intrarater reliability of the Woods and Teuber scale to detect mirror movements in children and adolescents with unilateral cerebral palsy (CP).

Method: A convenience sample of children and adolescents with unilateral CP (n=68; 31 males, 37 females; mean age 12y 2mo, SD 3y 6mo) in Manual Ability Classification levels I to III was recruited from Norway, Australia, and Belgium. Three therapists scored mirror movements according to the Woods and Teuber scale from three video-recorded tasks at two separate time points.

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Background: Unilateral spastic cerebral palsy (USCP) occurs in 30%-68% of infants with perinatal stroke. Early detection of USCP is essential for referring infants to early intervention. The aims of this study were to report motor outcomes after perinatal stroke, and to determine the predictive value of the General Movements Assessment (GMA) and Hand Assessment for Infants (HAI) for detection of USCP.

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Background: The Prechtl General Movement Assessment (GMA) predicts various neurological and developmental disorders while also documenting therapeutic effects.

Aims: To describe the temporal organization of fidgety general movements in infants with mild to moderate postural asymmetries and/or tonus regulation problems, and to analyze to what extent the temporal organization of fidgety movements will change after physiotherapy.

Study Design: Repeated measure design.

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Preterm infants born before 32 weeks gestation have increased risks for neurodevelopmental impairment at two years of age. How brain function differs between preterm infants with normal or impaired development is unknown. However, abnormal spontaneous motor behavior at 12-15 weeks post-term age is associated with neurodevelopmental impairment.

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Background: Early identification of cerebral palsy (CP) during infancy will provide opportunities for early therapies and treatments. The aim of the present study was to present a novel machine-learning model, the Computer-based Infant Movement Assessment (CIMA) model, for clinically feasible early CP prediction based on infant video recordings.

Methods: The CIMA model was designed to assess the proportion (%) of CP risk-related movements using a time-frequency decomposition of the movement trajectories of the infant's body parts.

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Background: Early prediction of cerebral palsy (CP) using the General Movement Assessment (GMA) during the fidgety movements (FM) period has been recommended as standard of care in high-risk infants. The aim of this study was to determine the accuracy of GMA, alone or in combination with neonatal imaging, in predicting cerebral palsy (CP).

Methods: Infants with increased risk of perinatal brain injury were prospectively enrolled from 2009-2014 in this multi-center, observational study.

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Aim: We compared the pain relieving effect of skin-to-skin contact versus standard care in the incubator during screening for retinopathy of prematurity.

Methods: This randomised crossover study included 35 preterm infants of less than 32 weeks of gestational age admitted to St Olavs University Hospital, Trondheim, Norway, between January 2014 and June 2016. Randomisation was for skin-to-skin with one of the parents or standard care with supportive positioning by parents for the first of two consecutive eye examinations.

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Background: Previous evidence suggests that the variability of the spatial center of infant movements, calculated by computer-based video analysis software, can identify fidgety general movements (GMs) and predict cerebral palsy.

Aim: To evaluate whether computer-based video analysis quantifies specific characteristics of normal fidgety movements as opposed to writhing general movements.

Methods: A longitudinal study design was applied.

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BackgroundAbsence of fidgety movements (FMs) at 3 months' corrected age is a strong predictor of cerebral palsy (CP) in high-risk infants. This study evaluates the association between computer-based video analysis and the temporal organization of FMs assessed with the General Movement Assessment (GMA).MethodsInfants were eligible for this prospective cohort study if referred to a high-risk follow-up program in a participating hospital.

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Importance: Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months' corrected age.

Objectives: To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy-specific early intervention that should follow early diagnosis to optimize neuroplasticity and function.

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Background: Most studies on Prechtl's method of assessing General Movements (GMA) in young infants originate in Europe.

Aim: To determine if motor behavior at an age of 3 months post term is associated with motor development at 12 months post age in VLBW infants in India.

Methods: 243 VLBW infants (135 boys, 108 girls; median gestational age 31wks, range 26-39wks) were video-recorded at a median age of 11wks post term (range 9-16wks).

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Aim: General movement assessment (GMA) at 9-20 weeks post-term, can effectively predict cerebral palsy. Our aim was to evaluate intra-individual variability of the temporal organization of fidgety movements (FMs) in high risk infants.

Material And Methods: 104 High risk infants (66 males) with at least two video recordings from the FMs period participated.

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The aim of this paper is to achieve a model for prediction of cerebral palsy based on motion data of young infants. The prediction is formulated as a classification problem to assign each of the infants to one of the healthy or with cerebral palsy groups. Unlike formerly proposed features that are mostly defined in the time domain, this study proposes a set of features derived from frequency analysis of infants' motions.

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Background: Cerebral Magnetic Resonance Imaging, the General Movement Assessment, and the Test of Infant Motor Performance are all tools that can predict neurodevelopmental outcome in preterm infants. However, how these tests relate to each other is unclear.

Aims: To examine the relationship between cerebral Magnetic Resonance Imaging measured at term age, and the General Movement Assessment and Test of Infant Motor Performance measured at 10-15 weeks post-term age.

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Aims: To compare early motor repertoire between extremely preterm and term-born infants. An association between the motor repertoire and gestational age and birth weight was explored in extremely preterm infants without severe ultrasound abnormalities.

Methods: In a multicentre study, the early motor repertoire of 82 infants born extremely preterm (ELGAN:<28 weeks) and/or with extremely low birth weight (ELBW:<1000 g) and 87 term-born infants were assessed by the "Assessment of Motor Repertoire - 2 to 5 Months" (AMR) which is part of Prechtl's "General Movement Assessment", at 12 weeks post-term age.

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In this paper we aim at predicting cerebral palsy, the most serious and lifelong motor function disorder in children, at an early age by analysing infants' motion data. An essential step for doing so is to extract informative features with high class separability. We propose a set of features derived from frequency analysis of the motion data.

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