Evidence map›Paper›PMID 38583933›Full record

ArticleAmerican journal of epidemiology2024

Internal validation of gestational age estimation algorithms in health-care databases using pregnancies conceived through fertility procedures.

Yu-Han Chiu, Krista F Huybrechts, Yanmin Zhu, Loreen Straub, Brian T Bateman, Roger Logan, Sonia Hernández-Díaz

Abstract readValidation Study
In one paragraph

Article in American journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Observational
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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

7 authors.

Yu-Han ChiuCAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.ORCID 0000-0002-0904-7855
Krista F HuybrechtsDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, United States.ORCID 0000-0001-5805-8430
Yanmin ZhuDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, United States.
Loreen StraubDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, United States.ORCID 0000-0003-2623-2726
Brian T BatemanDepartment of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA 94305, United States.
Roger LoganCAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Sonia Hernández-DíazCAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.

Funding

Impact of obesity treatments on subsequent pregnancy outcomesR01HD097778 · NICHD · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Sonia Hernandez-Diaz · 2019 to 2026
$4.2M
Long-term Impact of Fertility Treatment StudyR01HD088393 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI HERNAN, MIGUEL, HERNANDEZ-DIAZ, SONIA · 2017 to 2022
$2.9M
NICHD NIH HHS R01 HD088393NICHD NIH HHS R01 HD097778NIH HHS R01 HD097778
6 · The paper itself

Abstract

Fertility procedures recorded in health-care databases can be used to estimate the start of pregnancy, which can serve as a reference standard to validate gestational age estimates based on International Classification of Diseases codes. In a cohort of 17 398 US MarketScan pregnancies (2011-2020) in which conception was achieved via fertility procedures, we estimated gestational age at the end of pregnancy using algorithms based on (1) time (days) since the fertility procedure (the reference standard); (2) International Classification of Diseases, Ninth Revision (ICD-9)/International Classification of Diseases, Tenth Revision (ICD-10) (before/after October 2015) codes indicating gestational length recorded at the end of pregnancy (method A); and (3) ICD-10 end-of-pregnancy codes enhanced with Z3A codes denoting specific gestation weeks recorded at prenatal visits (method B). We calculated the proportion of pregnancies with an estimated gestational age falling within 14 days ($\pm$14 days) of the reference standard. Method A accuracy was similar for ICD-9 and ICD-10 codes. After 2015, method B was more accurate than method A: For term births, within-14-day agreement was 90.8% for method A and 98.7% for method B. Corresponding estimates were 70.1% and 95.6% for preterm births; 35.3% and 92.6% for stillbirths; 54.3% and 64.2% for spontaneous abortions; and 16.7% and 84.6% for elective terminations. ICD-10-based algorithms that incorporate Z3A codes improve the accuracy of gestational age estimation in health-care databases, especially for preterm births and non-live births.

Indexed as

AlgorithmsDatabases, FactualGestational AgeInternational Classification of DiseasesAdultFemaleHumansPregnancyReproductive Techniques, AssistedUnited StatesYoung Adultfertility proceduresgestational age estimationhealth-care databasespregnancy

Identifiers

PMID38583933
PMCPMC11299027

What OpenQuestion holds

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Registered trials

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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.