Evidence map›Paper›PMID 41034417›Full record

ReviewEuropean journal of pediatrics2025

Neonatal hyperbilirubinemia: past lessons, current practices, and future directions.

Ramesh Vidavalur

Abstract readReview
PubMed Publisher
In one paragraph

Review in European journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

1 author.

Ramesh VidavalurWeill Cornell Medical College, Cornell University, Ithaca, New York, USA. rav2016@med.cornell.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neonatal hyperbilirubinemia is a common clinical condition that, if not promptly and effectively managed, may lead to rare but severe neurodevelopmental complications. This review traces the historical progression of screening, diagnostic, and therapeutic approaches, highlights current standards such as phototherapy and immunotherapy, and examines emerging innovations including artificial intelligence and novel pharmacologic agents. It also addresses persistent global health disparities and explores future directions in research and precision medicine. A comprehensive literature search was conducted using PubMed, Scopus, and Cochrane databases, focusing on studies related to epidemiology, diagnostic strategies, and clinical management guidelines. Early recognition and intervention are essential to prevent both acute and long-term consequences. While phototherapy remains the mainstay of treatment, other adjunctive therapies are increasingly utilized in high-risk populations. Advances in screening and diagnostic technologies are reshaping individualized care, particularly in low-resource settings. Achieving global equity in neonatal jaundice outcomes requires technological advancement coupled with coordinated policy efforts, health system investment, and cross-sector collaboration to reduce preventable deaths and disability worldwide. Conclusion: Timely recognition and management of neonatal hyperbilirubinemia remain essential to prevent adverse outcomes. Advances in diagnostics, therapeutics, and global implementation strategies offer promising avenues to improve care and reduce disparities across diverse healthcare settings to reduce neonatal morbidity and mortality.

Indexed as

Hyperbilirubinemia, NeonatalHumansInfant, NewbornNeonatal ScreeningPhototherapyGlobal healthHyperbilirubinemiaKernicterusNeonatal jaundiceNeonatologyPhototherapyPrecision medicine

Identifiers

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.