Evidence map›Paper›PMID 42618046›Full record

ArticlePharmacoepidemiology and drug safety2026

Validation of Claims-Based Algorithms for Identifying Congenital Urinary Tract, Genital, Gastrointestinal, and Musculoskeletal Malformations.

Kelly Fung, Stephanie A Leonard, Krista F Huybrechts, Sonia Hernandez-Diaz, Brian T Bateman, Loreen Straub, Ayesha Sujan, Kathryn J Gray, Kylie Andersen, Eric Y Chen and 9 more

Abstract readValidation Study
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2026. 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

19 authors.

Kelly FungDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0004-6282-1362
Stephanie A LeonardDivision of Maternal-Fetal Medicine and Obstetrics, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0001-8213-1319
Krista F HuybrechtsDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-5805-8430
Sonia Hernandez-DiazDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-1458-7642
Brian T BatemanDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA.
Loreen StraubDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-2623-2726
Ayesha SujanDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0002-4374-9949
Kathryn J GrayDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Washington School of Medicine, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-3541-3724
Kylie AndersenDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Eric Y ChenDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Kareem El-TayebDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Murka JeancharlesDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Allison A MootzDepartment of Anesthesiology and Pain Management, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Amanda E WinklerDivision of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0002-5626-3769
Amali Maria FernandoDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Caroline X QinDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Emily Walker StockertDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0001-5593-6218
Helen MogunDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Yanmin ZhuDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-6697-6450

Funding

Research in Anesthesia Training Program (ReAP)T32GM089626 · NIGMS · STANFORD UNIVERSITY · PI Vivianne L Tawfik · 2010 to 2026
$5.2M
Safety of Benzodiazepines and Non-Benzodiazepine Sedative Hypnotics in PregnancyR01HD107772 · NICHD · BRIGHAM AND WOMEN'S HOSPITAL · PI Brian Thomas Bateman, Krista F Huybrechts · 2022 to 2026
$3.2M
Comparative Safety of Antibiotics for Common Bacterial Infections During PregnancyR01HD107759 · NICHD · BRIGHAM AND WOMEN'S HOSPITAL · PI Yanmin Zhu · 2022 to 2026
$2.9M
Interdisciplinary research training in maternal and childhood painT90HD118400 · NICHD · STANFORD UNIVERSITY · PI Nima Aghaeepour, Jennifer Rabbitts · 2024 to 2026
$1.1M
Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD107759Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD107772NICHD NIH HHS R01 HD107759NICHD NIH HHS R01 HD107772NICHD NIH HHS T90 HD118400NIGMS NIH HHS T32 GM089626the National Institute of General Medical Sciences NIH T32GM089626the National Institute of Neurological Disorders and Stroke NIH T90HD118400
6 · The paper itself

Abstract

aimCongenital malformations are important outcomes when evaluating medication safety in pregnancy. However, the accuracy of claims-based algorithms for identifying organ-specific malformations remains understudied. We validated algorithms for four malformation groups: urinary tract, genital, gastrointestinal, and musculoskeletal. MATERIALS AND

methodsUsing the Mass General Brigham (MGB, 2007-2020) and Stanford Medicine (2016-2023) databases, we identified infants with potential malformations of interest based on diagnosis and procedure codes within 90 days of birth. A total of 150 cases were sampled for each malformation group. Positive predictive values (PPV) were estimated to quantify the validity of the algorithms, separately by site and by International Classification of Diseases (ICD) coding system.

resultsFor MGB ICD-9, MGB ICD-10, and Stanford ICD-10 algorithms, respectively, PPVs were 100%, 98.0%, and 95.8% for urinary tract malformations; 98.0%, 95.9%, and 93.8% for genital malformations; 76.0%, 78.0%, and 76.0% for gastrointestinal malformations; and 85.4%, 84.0%, and 62.0% for musculoskeletal malformations. False positives were primarily attributed to suspected malformations that were later ruled out and to broader or inaccurate coding for diagnoses that were not major malformations.

conclusionsClaims-based algorithms demonstrated high PPVs for urinary tract and genital malformations and moderate for gastrointestinal malformations, but there was variation in musculoskeletal PPVs between the institutions with different patient populations.

Indexed as

Abnormalities, Drug-InducedAlgorithmsMusculoskeletal AbnormalitiesUrogenital AbnormalitiesDatabases, FactualFemaleHumansInfant, NewbornInternational Classification of DiseasesMalePredictive Value of TestsPregnancyUrinary Tractcongenital malformationdatabasespharmacoepidemiologypregnancyvalidation

Identifiers

PMID42618046
PMCPMC13489719

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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.