PUMA
Istituto di Fisiologia Clinica     
Garne E., Dolk H., Loane M., Wellesley D., Barisic I., Calzolari E., Densem J., Greenless R., Haeusler M., Nelen V., Verellen-Dumolin C., Randrianaivo H., Khoshnood B., Doray B., Queisser-Luft A., Rissman A., O'Mahony M., McDonnel B., Mullaney C., Bianchi F., Gatt M., Bakker M., Klungsoyr Melve K., Matias Dias C., Latos-Bielenska A., Salvador J., Larraitz A., Addor M., Wertelecki W., Draper E., Rankin J., Boyd P., Tucker D. Paper 5: Surveillance of Multiple Congenital Anomalies: Implementazion of a Computer Algorithm in European Register for Classification of Cases. In: Birth Defects Research Part A-Clinical and Molecular Teratology, vol. 91 (S1) pp. 44 - 50. Willey-Liss Inc, 2011.
 
 
Abstract
(English)
BACKGROUND Surveillance of multiple congenital anomalies is considered to be more sensitive for the detection of new teratogens than surveillance of all or isolated congenital anomalies. Current literature proposes the manual review of all cases for classification into isolated or multiple congenital anomalies. METHODS Multiple anomalies were defined as two or more major congenital anomalies, excluding sequences and syndromes. A computer algorithm for classification of major congenital anomaly cases in the EUROCAT database according to International Classification of Diseases (ICD)v10 codes was programmed, further developed, and implemented for 1 year's data (2004) from 25 registries. The group of cases classified with potential multiple congenital anomalies were manually reviewed by three geneticists to reach a final agreement of classification as "multiple congenital anomaly" cases. RESULTS A total of 17,733 cases with major congenital anomalies were reported giving an overall prevalence of major congenital anomalies at 2.17%. The computer algorithm classified 10.5% of all cases as "potentially multiple congenital anomalies". After manual review of these cases, 7% were agreed to have true multiple congenital anomalies. Furthermore, the algorithm classified 15% of all cases as having chromosomal anomalies, 2% as monogenic syndromes, and 76% as isolated congenital anomalies. The proportion of multiple anomalies varies by congenital anomaly subgroup with up to 35% of cases with bilateral renal agenesis. CONCLUSIONS The implementation of the EUROCAT computer algorithm is a feasible, efficient, and transparent way to improve classification of congenital anomalies for surveillance and research. Birth Defects Research (Part A), 2011. 2011 Wiley-Liss, Inc.
URL: http://onlinelibrary.wiley.com/doi/10.1002/bdra.20777/abstract
DOI: 10.1002/bdra.20777
Subject Multiple congenital anomaly
computer algorithm
classification
surveillance
etiology


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