Evidence map›Paper›PMID 42272207›Full record

ArticleAcute and critical care2026

From scores to signals: evolution and innovations in pediatric early warning systems.

Wonjin Jang, Bongjin Lee

Abstract read
In one paragraph

Article in Acute and critical care, 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

2 authors.

Wonjin JangDepartment of Pediatrics, Seoul National University Hospital, Seoul, Korea.
Bongjin LeeDepartment of Pediatrics, Seoul National University Hospital, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early identification of clinical deterioration in hospitalized children is essential to improve outcomes and prevent critical events. Over the past two decades, structured approaches such as pediatric early warning scores and rapid response systems have provided a framework for systematic risk detection in general wards. More recently, artificial intelligence and continuous monitoring technologies have begun to transform this field, offering the potential for more timely and accurate recognition of subtle changes in patient status. Despite these advances, challenges remain before seamless integration of these technologies into routine clinical decision-making can be achieved. This review explores the evolution of pediatric early warning systems and examines how emerging innovations may shape the future of predictive monitoring and clinical decision support in pediatric care.

Indexed as

artificial intelligencehospital rapid response teammonitoring, physiologic measurementspatient safetypediatrics

Identifiers

PMID42272207
PMCPMC13268725

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.