Evidence map›Paper›PMID 42533063›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2026

CAKUT calculator: a clinical risk prediction tool for in-hospital mortality in neonates with congenital anomalies of the kidney and urinary tract admitted to level IV NICUs.

Jennifer A Rumpel, Isabella Zaniletti, Christine Stoops, Courtney P Verscaj, Matthew W Harer, Andrew M South, Catherine Joseph, Semsa Gogcu, Mary Revenis, Mona Khattab and 5 more

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Article in Journal of perinatology : official journal of the California Perinatal Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

15 authors.

Jennifer A RumpelUniversity of Arkansas for Medical Sciences, Little Rock, AR, USA. Jarumpel@uams.edu.ORCID http://orcid.org/0000-0002-5883-218X
Isabella ZanilettiChildren's Hospitals Neonatal Consortium, Dover, DE, USA.ORCID http://orcid.org/0000-0003-1234-3468
Christine StoopsUniversity of Alabama at Birmingham, Birmingham, AL, USA.ORCID http://orcid.org/0000-0003-2252-5724
Courtney P VerscajBoston Children's Hospital, Boston, MA, USA.
Matthew W HarerUniversity of Wisconsin School of Medicine and Public Health, Madison, WI, USA.ORCID http://orcid.org/0000-0001-5493-3269
Andrew M SouthAtrium Health Levine Children's Brenner Children's Hospital, Winston Salem, NC, USA.ORCID http://orcid.org/0000-0002-3204-4142
Catherine JosephBaylor College of Medicine, Texas Children's Hospital, Houston, Texas, USA.
Semsa GogcuWake Forest University School of Medicine, Winston Salem, NC, USA.
Mary RevenisGeorge Washington University School of Medicine and Health Sciences, Washington, DC, USA.
Mona KhattabBaylor College of Medicine, Texas Children's Hospital, Houston, Texas, USA.
Michael PadulaChildren's Hospitals Neonatal Consortium, Dover, DE, USA.ORCID http://orcid.org/0000-0003-2050-5930
Theresa GroverChildren's Hospitals Neonatal Consortium, Dover, DE, USA.
Karna MurthyChildren's Hospitals Neonatal Consortium, Dover, DE, USA.
Sofia I PerazzoGeorge Washington University School of Medicine and Health Sciences, Washington, DC, USA.ORCID http://orcid.org/0000-0003-0718-7771
Children’s Hospitals Neonatal Consortium Kidney Focus Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo predict in-hospital mortality for infants with congenital anomalies of the kidney and urinary tract (CAKUT) using perinatal factors and use the resultant model to create an interactive clinical risk calculator. STUDY

designA retrospective cohort study included 13,233 neonates with CAKUT diagnoses admitted to forty-six level IV neonatal intensive care units participating in the Children's Hospitals Neonatal Consortium from 2010 to 2024. A predictive model for in-hospital mortality was built using perinatal risk factors.

results1353 (10.2%) neonates died. Eight perinatal factors predicted mortality with strong model performance (area under the curve: 0.87 (95% confidence interval [CI]: 0.85, 0.88) training; 0.84 (95% CI: 0.82, 0.86) validation).

conclusionFor newborn infants with CAKUT, prediction of in-hospital mortality can be estimated using 8 factors identifiable during the immediate perinatal period. Correspondingly, an on-line calculator that is publicly available for clinicians, researchers, and families of affected infants can be integrated in perinatal management.

Identifiers

PMID42533063

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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.