Evidence map›Paper›PMID 41774249›Full record

ArticleEuropean journal of pediatrics2026

A nomogram for predicting Kawasaki Disease in acutely febrile children with liver injury.

Pingping Yang, Guina Wang, Jing Guo, Wenlong Yan, Lingfen Xu, Lingzhe Meng

Abstract readValidation Study
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In one paragraph

Article in European journal of pediatrics, 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

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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.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pingping Yang *Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Guina Wang *Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Jing GuoDepartment of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Wenlong YanDepartment of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Lingfen Xu *Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China. xulingfen7408@163.com.
Lingzhe Meng *Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China. svtopman@qq.com.

Funding

National Key Research and Development Program of China 2023YFC2706503
6 · The paper itself

Abstract

Liver injury is a common but nonspecific feature of acute Kawasaki disease (KD), often obscuring the diagnosis and delaying treatment. This study aimed to develop and validate a nomogram to predict KD risk in febrile children with liver injury. We conducted a retrospective study of children admitted with fever and liver injury between January 2019 and December 2024. A nomogram was developed using multivariable logistic regression in a training cohort, internally validated, and further evaluated in an independent temporal validation cohort (January-September 2025). Among 1,031 children, KD was the second most common specific diagnosis (13.4%). Nine independent predictors were identified: duration of fever, absolute neutrophil count, absolute lymphocyte count, C-reactive protein, albumin, gamma-glutamyl transferase, total bilirubin, high-density lipoprotein, and serum potassium. The nomogram demonstrated excellent discrimination, with AUCs of 0.983 (training test), 0.962 (internal test), and 0.996 (temporal validation). Calibration and decision-curve analyses confirmed clinical utility.

conclusionWe constructed and validated a robust nomogram using accessible clinical variables. As a supplementary risk-assessment tool, it is designed to raise clinical suspicion of KD in febrile children with liver injury, thereby facilitating earlier intervention and optimized management. WHAT IS KNOWN: • Liver injury, a common complication of Kawasaki disease (KD), closely correlates with greater inflammation, intravenous immunoglobulin (IVIG) resistance, and higher coronary risk. • No specific predictive tool exists to identify KD among febrile children presenting with liver injury. WHAT IS NEW: • This study developed and validated the first nomogram to predict KD risk in febrile children with liver injury, using nine clinical parameters. • The model demonstrates excellent performance in both internal and prospective temporal validation. • It highlights low high-density lipoprotein (HDL) as a novel biomarker, useful not only for early diagnosis but also for monitoring acute inflammation in KD.

Indexed as

FeverLiver DiseasesMucocutaneous Lymph Node SyndromeNomogramsChild, PreschoolFemaleHumansInfantMalePredictive Value of TestsRetrospective StudiesRisk AssessmentRisk FactorsFebrileKawasaki diseaseLiver injuryNomogramRisk prediction

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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.