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论文5:多种先天性异常的监测:在欧洲登记系统中实施计算机算法对病例进行分类

Paper 5: Surveillance of multiple congenital anomalies: implementation of a computer algorithm in European registers for classification of cases.

作者信息

Garne Ester, Dolk Helen, Loane Maria, Wellesley Diana, Barisic Ingeborg, Calzolari Elisa, Densem James

机构信息

Paediatric Department, Hospital Lillebaelt, Kolding, Denmark.

出版信息

Birth Defects Res A Clin Mol Teratol. 2011 Mar;91 Suppl 1:S44-50. doi: 10.1002/bdra.20777. Epub 2011 Mar 7.

Abstract

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.

摘要

背景

与监测所有先天性异常或孤立性先天性异常相比,监测多种先天性异常被认为对发现新的致畸物更为敏感。当前文献建议对所有病例进行人工审查,以分类为孤立性或多种先天性异常。

方法

多种异常被定义为两个或更多主要先天性异常,不包括序列和综合征。根据国际疾病分类(ICD)第10版编码,为EUROCAT数据库中的主要先天性异常病例分类编写了计算机算法,并进行了进一步开发和实施,用于来自25个登记处的1年数据(2004年)。由三位遗传学家对分类为潜在多种先天性异常的病例组进行人工审查,以达成将其分类为“多种先天性异常”病例的最终共识。

结果

共报告了17733例主要先天性异常病例,主要先天性异常的总体患病率为2.17%。计算机算法将所有病例的10.5%分类为“潜在多种先天性异常”。对这些病例进行人工审查后,7%被确认为真正的多种先天性异常。此外,该算法将所有病例的15%分类为患有染色体异常,2%为单基因综合征,76%为孤立性先天性异常。多种异常的比例因先天性异常亚组而异,双侧肾缺如病例中高达35%。

结论

实施EUROCAT计算机算法是一种可行、高效且透明的方法,可改善先天性异常的分类,用于监测和研究。

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