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Identifying syndromes in studies of structural birth defects: Guidance on classification and evaluation of potential impact.
Benjamin, Renata H; Mitchell, Laura E; Scheuerle, Angela E; Langlois, Peter H; Canfield, Mark A; Drummond-Borg, Margaret; Nguyen, Joanne M; Agopian, A J.
Afiliação
  • Benjamin RH; Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Houston, Texas, USA.
  • Mitchell LE; Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Houston, Texas, USA.
  • Scheuerle AE; Department of Pediatrics, Division of Genetics and Metabolism, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
  • Langlois PH; Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health at Austin, Austin, Texas, USA.
  • Canfield MA; Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, Texas, USA.
  • Drummond-Borg M; Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, Texas, USA.
  • Nguyen JM; Department of Genetics, Cook Children's Hospital, Fort Worth, Texas, USA.
  • Agopian AJ; Department of Epidemiology, Human Genetics, and Environmental Sciences, UTHealth School of Public Health, Houston, Texas, USA.
Am J Med Genet A ; 191(1): 190-204, 2023 01.
Article em En | MEDLINE | ID: mdl-36286533
ABSTRACT
Structural birth defects that occur in infants with syndromes may be etiologically distinct from those that occur in infants in whom there is not a recognized pattern of malformations; however, population-based registries often lack the resources to classify syndromic status via case reviews. We developed criteria to systematically identify infants with suspected syndromes, grouped by syndrome type and level of effort required for syndrome classification (e.g., text search). We applied this algorithm to the Texas Birth Defects Registry (TBDR) to describe the proportion of infants with syndromes delivered during 1999-2014. We also developed a bias analysis tool to estimate the potential percent bias resulting from including infants with syndromes in studies of risk factors. Among 207,880 cases with birth defects in the TBDR, 15% had suspected syndromes and 85% were assumed to be nonsyndromic, with a range across defect types from 28.5% (atrioventricular septal defects) to 98.9% (pyloric stenosis). Across hypothetical scenarios varying expected parameters (e.g., nonsyndromic proportion), the inclusion of syndromic cases in analyses resulted in up to 50.0% bias in prevalence ratios. In summary, we present a framework for identifying infants with syndromic conditions; implementation might harmonize syndromic classification across registries and reduce bias in association estimates.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Defeitos dos Septos Cardíacos Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans / Infant País como assunto: America do norte Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Defeitos dos Septos Cardíacos Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans / Infant País como assunto: America do norte Idioma: En Ano de publicação: 2023 Tipo de documento: Article