Evidence map›Paper›PMID 42903614›Full record

ArticleKidney international reports2026

High Prevalence and Limited Perinatal Prediction of Kidney Dysfunction in Adolescents Born Extremely Preterm.

Keia R Sanderson, Jesus E Vazquez, Jennifer E Flythe, David Askenazi, Michael R Kosorok, Minxin Lu, Kartikeya Makker, Matthew Laughon, Christine E Kistler, Rebecca C Fry and 1 more

Abstract read
In one paragraph

Article in Kidney international reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Keia R SandersonDepartment of Pediatrics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina USA.
Jesus E VazquezDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Jennifer E FlytheUniversity of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
David AskenaziDepartment of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Michael R KosorokDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Minxin LuDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Kartikeya MakkerDivision of Neonatology, Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Matthew LaughonDepartment of Pediatrics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina USA.
Christine E KistlerDivision of Geriatric Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Rebecca C FryDepartment of Environmental Sciences and Engineering, The University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.
Thomas Michael O'SheaDepartment of Pediatrics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina USA.

Funding

Neonatal Biomarkers in Extremely Preterm Babies Predict Childhood Brain DisordersU01NS040069 · NINDS · CHILDREN'S HOSPITAL BOSTON · PI KUBAN, KARL · 2001 to 2014
$34.0M
Environment, Epigenetics, Neurodevelopment & Health of Extremely Preterm ChildrenUG3OD023348 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FRY, REBECCA, O'SHEA, MICHAEL · 2016 to 2024
$7.4M
Machine Learning Risk Prediction of Kidney Disease After Extremely Preterm BirthK23DK131289 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SANDERSON, KEIA · 2023 to 2025
$602k
NIDDK NIH HHS K23 DK131289NIDDK NIH HHS L40 DK130155NIH HHS UG3 OD023348NINDS NIH HHS U01 NS040069
6 · The paper itself

Abstract

Introduction: Extremely preterm birth (< 28 weeks' gestation) increases chronic kidney disease (CKD) risk. However, among those born extremely preterm, the prevalence of abnormal kidney health during adolescence and its perinatal predictors remain poorly defined. Methods: Adolescents from the Extremely Low Gestational Age Newborn -Environmental influences on Child Health Outcomes (ELGAN-ECHO) cohort (14 US hospitals) were assessed for abnormal kidney health defined as ≥ 1 indicator-chronic kidney disease in children (CKiD) U25 estimated glomerular filtration rate (eGFR) < 90 ml/min per 1.73 m Results: Of the 675 adolescents (mean age 18 years), 354 (52%) had a classifiable kidney health status, as follows: 188 with all 3 measurements and 166 with partial measurements showing ≥ 1 abnormality. The prevalence of abnormal kidney health was 66% among complete cases (125/188) and 82% among all determinate cases (291/354). In the full cohort, prevalence ranged from 43% to 91% (bounding estimates accounting for missing data). Individual measurements revealed 30.5% with reduced eGFR, 42% with elevated BP, and 9% with microalbuminuria. Across all methods, perinatal covariates achieved random test-set discrimination (AUC: 0.48-0.55) for abnormal kidney health prediction, compared with training set AUCs of 0.66-0.72. Conclusion: Abnormal kidney health is highly prevalent after extremely preterm birth, underscoring the importance of protocolized longitudinal kidney health surveillance throughout childhood to enable early identification of CKD and elevated BP in children born extremely preterm. The perinatal factors we examined did not meaningfully predict kidney health abnormalities and variable importance did not translate to individual-level prediction in this cohort.

Indexed as

chronic kidney diseaseglomerular filtration ratehypertensionmachine learningpreterm birthrisk prediction

Identifiers

PMID42903614
PMCPMC13681999

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.