Evidence map›Paper›PMID 39169811›Full record

ArticleBirth defects research2024

Enhancing the Classification of Congenital Heart Defects for Outcome Association Studies in Birth Defects Registries.

Sara B Stephens, Renata H Benjamin, Keila N Lopez, Brett R Anderson, Angela E Lin, Charles J Shumate, Wendy N Nembhard, Shaine A Morris, A J Agopian

Abstract read
In one paragraph

Article in Birth defects research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sara B StephensDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.ORCID 0000-0002-2180-2198
Renata H BenjaminDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.ORCID 0000-0001-6406-4247
Keila N LopezDivision of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas, USA.ORCID 0000-0002-2710-6257
Brett R AndersonDivision of Pediatric Cardiology, New York-Presbyterian and Columbia University Irving Medical Center, New York, New York, USA.
Angela E LinDepartment of Pediatrics, Medical Genetics Unit, Mass General for Children and Harvard University School of Medicine, Boston, Massachusetts, USA.
Charles J ShumateTexas Department of State Health Services, Austin, Texas, USA.ORCID 0000-0003-2884-2835
Wendy N NembhardArkansas Center for Birth Defects Research and Prevention and Arkansas Reproductive Health Monitoring System, Fay Boozman College of Public Health, Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.ORCID 0000-0002-8318-4049
Shaine A MorrisDivision of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas, USA.ORCID 0000-0002-8056-0934
A J AgopianDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.ORCID 0000-0002-5874-4155

Funding

A multidisciplinary approach for identifying and characterizing novel congenital malformation syndromesR01HD093660 · NICHD · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI AGOPIAN, A.J., LUPO, PHILIP · 2018 to 2022
$2.0M
CDC HHSHRSA HHSNICHD NIH HHS R01 HD093660Texas Department of State Health Services HHS 00096260001Texas Department of State Health Services NU50DD000102
6 · The paper itself

Abstract

introductionTraditional strategies for grouping congenital heart defects (CHDs) using birth defect registry data do not adequately address differences in expected clinical consequences between different combinations of CHDs. We report a lesion-specific classification system for birth defect registry-based outcome studies.

methodsFor Core Cardiac Lesion Outcome Classifications (C-CLOC) groups, common CHDs expected to have reasonable clinical homogeneity were defined. Criteria based on combinations of Centers for Disease and Control-modified British Pediatric Association (BPA) codes were defined for each C-CLOC group. To demonstrate proof of concept and retention of reasonable case counts within C-CLOC groups, Texas Birth Defect Registry data (1999-2017 deliveries) were used to compare case counts and neonatal mortality between traditional vs. C-CLOC classification approaches.

resultsC-CLOC defined 59 CHD groups among 62,262 infants with CHDs. Classifying cases into the single, mutually exclusive C-CLOC group reflecting the highest complexity CHD present reduced case counts among lower complexity lesions (e.g., 86.5% of cases with a common atrium BPA code were reclassified to a higher complexity group for a co-occurring CHD). As expected, C-CLOC groups had retained larger sample sizes (i.e., representing presumably better-powered analytic groups) compared to cases with only one CHD code and no occurring CHDs. DISCUSSION: This new CHD classification system for investigators using birth defect registry data, C-CLOC, is expected to balance clinical outcome homogeneity in analytic groups while maintaining sufficiently large case counts within categories, thus improving power for CHD-specific outcome association comparisons. Future outcome studies utilizing C-CLOC-based classifications are planned.

Indexed as

Heart Defects, CongenitalRegistriesCongenital AbnormalitiesFemaleHumansInfantInfant MortalityInfant, NewbornMaleOutcome Assessment, Health CareTexasbirth defect registryclassificationcongenital anomaliescongenital heart defectssurveillance programs

Identifiers

PMID39169811
PMCPMC11421657

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.