Evidence map›Paper›PMID 36538557›Full record

ArticlePloS one2022

Newborn genetic testing in the United States and access to needed specialist care, National Survey of Children's Health, 2020: A cross-sectional study.

R Constance Wiener

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

1 author.

R Constance WienerDepartment of Dental Public Health and Professional Practice, West Virginia University, Morgantown, West Virginia, United States of America.ORCID 0000-0003-0371-6699

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Newborn screening tests (NST) are important public health procedures with potential to improve quality of life, and decrease morbidity/mortality by identifying metabolic, genetic, enzymatic, and endocrinological diseases/conditions. In the United States (U.S.), Hawaii conducts the fewest NST (28) and Connecticut conducts the most (75). The purpose of this research is to determine if difficulty receiving specialty care for children with genetic diseases is associated with NST determination of the genetic condition. The research hypothesis is that parents/guardians of children with determination of genetic disease from NST are more likely to report no/slight difficulty accessing specialty care versus parents/guardians of children with genetic diseases whose determination was other than NST. This study has a cross-sectional design with National Survey of Children's Health, 2020 data. Data were analyzed for frequency, Rao Scott Chi square, and logistic regression analyses. Of 833 children with genetic diseases, most parents/guardians reported no/slight difficulty in receiving needed specialty care; however, children whose determination of a genetic condition was other than NST were 4.82 times as likely (95%CI: 1.66, 14.02; p = 0.0040) to have difficulty. In analysis adjusted for sex, race, age, premature birth, and birthweight, the adjusted odds ratio was 6.71 (95% CI:1.91, 23.60 p = 0.0031). Parents/guardians of children screened with a positive NST reported less difficulty in receiving needed specialist care as compared with reports of parents/guardians of children with genetic conditions who were diagnosed later. The implication is there would be greater population level benefits realized in the U.S. if NST were expanded in states conducting minimal testing.

Indexed as

Child HealthQuality of LifeChildCross-Sectional StudiesFemaleGenetic TestingHawaiiHumansInfant, NewbornPregnancyUnited States

Identifiers

PMID36538557
PMCPMC9767346

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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.