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DOI: 10.1055/a-1808-2843
Unterschiede in der Verteilung der General Movements-Klassifikation zwischen neonatalen Risikogruppen im Kinderspital Zürich: Eine Beobachtungsstudie
Differences in the Distribution of the General Movements Classification Between Neonatal Risk Groups in the Children’s Hospital Zurich: An Observational StudyZusammenfassung
Einleitung Kinder auf der Neonatologie weisen ein erhöhtes Risiko für motorische Entwicklungsstörungen auf.
Ziel Vergleich der General Movements (GMs)-Klassifikation zwischen drei neonatalen Risikogruppen, Korrelation des GMs-Assessment (GMA) mit einer standardisierten, entwicklungsneurologischen Untersuchung (SENU) sowie Bestimmung von Risikofaktoren für abnormale GMs.
Methodik Monozentrische Beobachtungsstudie mit drei Risikogruppen (Kinder mit operierten, angeborenen Herzfehlern (aHF) n=26, mit operierten, angeborenen, gastrointestinalen Fehlbildungen (GIF) n=17 und mit fetal operierter Myelomeningozele (MMC) n=12, die stationär videobasiert untersucht wurden. Das GMA wurde gemäss Klassifikation nach Hadders-Algra bewertet und in 4 Kategorien eingeteilt: normal optimal (NO), normal suboptimal (NS), leicht abnormal (LA), deutlich abnormal (DA).
Ergebnisse Es zeigte sich folgende Verteilung: aHF 80,8% NS, 19,2% LA, GIF 5,9% NO, 64,7% NS, 29,4% LA, MMC obere Extremitäten 100% NS, untere Extremitäten 33,3% NS, 33,3% LA und 33,3% DA (Gruppenvergleich Kruskal-Wallis 10 729, p=0,003). Das GMA korrelierte signifikant mit der SENU (Spearman rs=0,869, p<0,001). Die binär logistische Regressionsanalyse zeigte, dass nur das Gestationsalter (Chi2=11,93, p<0,001) mit abnormalen GMs korrelierte.
Schlussfolgerung Die Mehrheit der Kinder zeigte normale GMs. Kinder mit MMC und solche mit tieferem Gestationsalter wiesen ein erhöhtes Risiko für abnormale GMs auf. Das GMA und die SENU stellen ergänzende «bedside tools» dar, um früh motorische Auffälligkeiten zu erkennen.
Abstract
Introduction Neonatal infants are at increased risk for motor development disorders.
Objective To compare General Movements (GMs) classification between three neonatal risk groups, correlate the GMs Assessment (GMA) with a standardized developmental neurological examination (SDNE) and determine risk factors for abnormal GMs.
Methods Monocentric observational study with three risk groups (children with operated congenital heart disease (CHD) n=26, with operated congenital gastrointestinal malformations (CGM) n=17 and with fetal operated myelomeningocele (MMC) n=12 who underwent inpatient video-based examination. GMA was evaluated according to Hadders-Algra classification and divided into 4 categories: normal optimal (NO), normal suboptimal (NS), mildly abnormal (MA), definitely abnormal (DA).
Results The distribution was as follows: CHD 80.8% NS, 19.2% MA, CGM 5.9% NO, 64.7% NS, 29.4% MA, MMC upper extremities 100% NS, lower extremities 33.3% NS, 33.3% MA and 33.3% DA (group comparison Kruskal-Wallis 10.729, p=0.003). GMA correlated significantly with SDNE (Spearman r s=0.869, p<0.001). Binary logistic regression analysis showed that only gestational age (Chi2=11.93, p<0.001) correlated with abnormal GMs.
Conclusion The majority of children showed normal GMs. Children with MMC and those with lower gestational age showed an increased risk of abnormal GMs. The GMA and SDNE represent complementary “bedside tools” to detect early motor abnormalities.
Key words
General movements assessment - congenital heart disease - gastrointestinal malformations - MMCPublication History
Received: 27 January 2022
Accepted after revision: 14 March 2022
Article published online:
07 June 2022
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Literatur
- 1 Walker K, Badawi N, Halliday R. et al. Early developmental outcomes following major noncardiac and cardiac surgery in term infants: a population-based study. The Journal of pediatrics 2012; 161: 748-752.e741 DOI: 10.1016/j.jpeds.2012.03.044.
- 2 Crowle C, Galea C, Walker K. et al. Prediction of neurodevelopment at one year of age using the General Movements assessment in the neonatal surgical population. Early human development 2018; 118: 42-47 DOI: 10.1016/j.earlhumdev.2018.02.001.
- 3 Latal B. Neurodevelopmental Outcomes of the Child with Congenital Heart Disease. Clin Perinatol 2016; 43: 173-185 DOI: 10.1016/j.clp.2015.11.012.
- 4 Garne E, Rasmussen L, Husby S. Gastrointestinal malformations in Funen county, Denmark – epidemiology, associated malformations, surgery and mortality. European journal of pediatric surgery: official journal of Austrian Association of Pediatric Surgery [et al.]=Zeitschrift fur Kinderchirurgie 2002; 12: 101-106 DOI: 10.1055/s-2002-30158.
- 5 Crowle C, Loughran Fowlds A, Novak I. et al. Use of the General Movements Assessment for the Early Detection of Cerebral Palsy in Infants with Congenital Anomalies Requiring Surgery. J Clin Med 2019; 8 DOI: 10.3390/jcm8091286.
- 6 Mohrlen U, Ochsenbein-Kolble N, Mazzone L. et al. Benchmarking against the MOMS Trial: Zurich Results of Open Fetal Surgery for Spina Bifida. Fetal diagnosis and therapy 2019; 1-7 DOI: 10.1159/000500049.
- 7 Adzick NS, Thom EA, Spong CY. et al. A randomized trial of prenatal versus postnatal repair of myelomeningocele. New England Journal of Medicine 2011; 364: 993-1004
- 8 Novak I, Morgan C, Adde L. et al. Early, Accurate Diagnosis and Early Intervention in Cerebral Palsy: Advances in Diagnosis and Treatment. JAMA Pediatr 2017; 171: 897-907 DOI: 10.1001/jamapediatrics.2017.1689.
- 9 Prechtl HF, Einspieler C, Cioni G. et al. An early marker for neurological deficits after perinatal brain lesions. Lancet (London, England) 1997; 349: 1361-1363 DOI: 10.1016/s0140-6736(96)10182-3.
- 10 Bouwstra H, Dijk-Stigter GR, Grooten HM. et al. Prevalence of abnormal general movements in three-month-old infants. Early human development 2009; 85: 399-403 DOI: 10.1016/j.earlhumdev.2009.01.003.
- 11 Bouwstra H, Dijk-Stigter GR, Grooten HM. et al. Predictive value of definitely abnormal general movements in the general population. Developmental medicine and child neurology 2010; 52: 456-461 DOI: 10.1111/j.1469-8749.2009.03529.x.
- 12 Burger M, Louw QA. The predictive validity of general movements – a systematic review. European journal of paediatric neurology: EJPN : official journal of the European Paediatric Neurology Society 2009; 13: 408-420 DOI: 10.1016/j.ejpn.2008.09.004.
- 13 Hadders-Algra M, Mavinkurve-Groothuis AM, Groen SE. et al. Quality of general movements and the development of minor neurological dysfunction at toddler and school age. Clin Rehabil 2004; 18: 287-299 DOI: 10.1191/0269215504cr730oa.
- 14 van Iersel PA, Bakker SC, Jonker AJ. et al. Quality of general movements in term infants with asphyxia. Early human development 2009; 85: 7-12 DOI: 10.1016/j.earlhumdev.2008.05.006.
- 15 van Iersel PA, Bakker SC, Jonker AJ. et al. Does perinatal asphyxia contribute to neurological dysfunction in preterm infants?. Early human development 2010; 86: 457-461 DOI: 10.1016/j.earlhumdev.2010.06.003.
- 16 Campbell MJ, Ziviani JM, Stocker CF. et al. Neuromotor performance in infants before and after early open-heart surgery and risk factors for delayed development at 6 months of age. Cardiol Young 2019; 29: 100-109 DOI: 10.1017/s1047951118001622.
- 17 Crowle C, Walker K, Galea C. et al. General movement trajectories and neurodevelopment at 3months of age following neonatal surgery. Early human development 2017; 111: 42-48 DOI: 10.1016/j.earlhumdev.2017.05.010.
- 18 Huisenga DC, Van Bergen AH, Sweeney JK. et al. The quality of general movements in infants with complex congenital heart disease undergoing surgery in the neonatal period. Early human development 2020; 151: 105167 DOI: 10.1016/j.earlhumdev.2020.105167.
- 19 Moehrlen U, Ochsenbein N, Vonzun L. et al. Fetal surgery for spina bifida in Zurich: results from 150 cases. Pediatric surgery international 2021; 37: 311-316 DOI: 10.1007/s00383-020-04824-8.
- 20 Hadders-Algra M. General movements: A window for early identification of children at high risk for developmental disorders. The Journal of pediatrics 2004; 145: S12-S18 DOI: 10.1016/j.jpeds.2004.05.017.
- 21 Landis JR, Koch GG. An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics 1977; 33: 363-374
- 22 Kuenzle C, Baenziger O, Martin E. et al. Prognostic value of early MR imaging in term infants with severe perinatal asphyxia. Neuropediatrics 1994; 25: 191-200 DOI: 10.1055/s-2008-1073021.
- 23 Prechtl HF. The behavioural states of the newborn infant (a review). Brain research 1974; 76: 185-212 DOI: 10.1016/0006-8993(74)90454-5.
- 24 Cohen J. A power primer. Psychological bulletin 1992; 112: 155-159 DOI: 10.1037//0033-2909.112.1.155.
- 25 Crowle C, Badawi N, Walker K. et al. General Movements Assessment of infants in the neonatal intensive care unit following surgery. J Paediatr Child Health 2015; 51: 1007-1011 DOI: 10.1111/jpc.12886.
- 26 Bennema AN, Schendelaar P, Seggers J. et al. Predictive value of general movements’ quality in low-risk infants for minor neurological dysfunction and behavioural problems at preschool age. Early human development 2016; 94: 19-24 DOI: 10.1016/j.earlhumdev.2016.01.010.
- 27 Ploegstra WM, Bos AF, de Vries NK. General movements in healthy full term infants during the first week after birth. Early human development 2014; 90: 55-60 DOI: 10.1016/j.earlhumdev.2013.10.004.
- 28 Wu YC, van Rijssen IM, Buurman MT. et al. Temporal and spatial localisation of general movement complexity and variation-Why Gestalt assessment requires experience. Acta paediatrica (Oslo, Norway : 1992) 2021; 110: 290-300 DOI: 10.1111/apa.15300.
- 29 Silva N, Zhang D, Kulvicius T. et al. The future of General Movement Assessment: The role of computer vision and machine learning – A scoping review. Res Dev Disabil 2021; 110: 103854 DOI: 10.1016/j.ridd.2021.103854.
- 30 Ihlen EAF, Støen R, Boswell L. et al. Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study. J Clin Med 2019; 9 DOI: 10.3390/jcm9010005.
- 31 Irshad MT, Nisar MA, Gouverneur P. et al. AI Approaches Towards Prechtl’s Assessment of General Movements: A Systematic Literature Review. Sensors (Basel, Switzerland) 2020; 20 DOI: 10.3390/s20185321.
- 32 Doroniewicz I, Ledwoń DJ, Affanasowicz A. et al. Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification. Sensors (Basel, Switzerland) 2020; 20 DOI: 10.3390/s20215986.
- 33 Crowle C, Galea C, Morgan C. et al. Inter-observer agreement of the General Movements Assessment with infants following surgery. Early human development 2017; 104: 17-21 DOI: 10.1016/j.earlhumdev.2016.11.001.