Evidence map›Paper›PMID 41409266›Full record

ArticleFrontiers in pediatrics2025

A prediction model for post-treatment presence of coronary artery abnormality before initial treatment in Kawasaki disease in Japan.

Takayuki Suzuki, Naomi Kitano, Nobuyuki Kakimoto, Tomohiro Suenaga, Shoichi Shibuta, Takashi Takeuchi, Hiroyuki Suzuki, Kota Abe, Kumi Yasukawa, Kentaro Okunushi and 2 more

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2025. 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

12 authors.

Takayuki SuzukiDepartment of Pediatrics, School of Medicine, Wakayama Medical University, Wakayama, Japan.
Naomi KitanoDivision of Public Health and Health Management Center, School of Medicine, Wakayama Medical University, Wakayama, Japan.
Nobuyuki KakimotoDepartment of Pediatrics, School of Medicine, Wakayama Medical University, Wakayama, Japan.
Tomohiro SuenagaDepartment of Pediatrics, School of Medicine, Wakayama Medical University, Wakayama, Japan.
Shoichi ShibutaDivision of Pediatrics, Kinan Hospital, Tanabe, Japan.
Takashi TakeuchiDivision of Pediatrics, Kinan Hospital, Tanabe, Japan.
Hiroyuki SuzukiDivision of Pediatrics, Tsukushi Medical and Welfare Center, Iwade, Japan.
Kota AbeDivision of Pediatrics, Tokyo Women's Medical University Yachiyo Medical Center, Yachiyo, Japan.
Kumi YasukawaDivision of Pediatrics, Tokyo Women's Medical University Yachiyo Medical Center, Yachiyo, Japan.
Kentaro OkunushiDepartment of Pediatrics, Graduate School of Medicine, Chiba University, Chiba, Japan.
Hiromichi HamadaDepartment of Pediatrics, Graduate School of Medicine, Chiba University, Chiba, Japan.
Daisuke TokuharaDepartment of Pediatrics, School of Medicine, Wakayama Medical University, Wakayama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to develop and validate a predictive model for the presence of coronary artery abnormality (CAA) after treatment using pre-treatment clinical and laboratory parameters, including coronary Method and results: A retrospective multicenter cohort study was conducted, analyzing 1,565 patients diagnosed with KD across eight medical institutions within the Wakayama Kawasaki Disease Clinical Research Group, with validation performed at Chiba University and Tokyo Women's Medical University. A predictive model was developed using data from a primary cohort ( Conclusions: The developed model accurately predicts post-treatment CAA presence, emphasizing the importance of early coronary

Indexed as

coronary artery abnormalitycoronary artery z-scoreechocardiographyKawasaki diseasepredictors

Identifiers

PMID41409266
PMCPMC12705635

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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.