Evidence map›Paper›PMID 36977496›Full record

ArticleJornal de pediatria

Prediction of coronary artery lesions based on C-reactive protein levels in children with Kawasaki Disease: a retrospective cohort study.

ShuPing Shuai, HongXi Zhang, Rui Zhang, Mi Tang, ErDan Luo, YanFeng Yang, Yu Gao, ShanLan Yue, Hua Liang, JiangHui Cai

Open access · goldAbstract read
In one paragraph

Article in Jornal de pediatria. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
7.6field-weighted citation impact, top 2% of its field
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

21 citing papers in PubMed, 24 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

ShuPing ShuaiUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
HongXi ZhangUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
Rui ZhangUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
Mi TangUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu, China; University of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Office of Good Clinical Practice, Chengdu, China.
ErDan LuoUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu, China; University of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Office of Good Clinical Practice, Chengdu, China.
YanFeng YangUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pediatric Cardiology, Chengdu, China.
Yu GaoUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
ShanLan YueUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
Hua LiangUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China.
JiangHui CaiUniversity of Electronic Science and Technology of China, School of Medicine, Chengdu Women's and Children's Central Hospital, Department of Pharmacy, Chengdu, China. Electronic address: 776773221@qq.com.
University of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveSince coronary artery lesions (CALs) are the most severe complication of Kawasaki disease (KD), clinically speaking, early prediction of CALs is crucial. The authors aimed to investigate the predictive value of C-reactive protein (CRP) in predicting CALs in KD patients.

methodsKD patients were divided into the CALs group and the non-CALs group. The clinical and laboratory parameters were collected and compared. Multivariate logistic regression analysis was used to determine the independent risk factors of CALs. The receiver operating characteristic curve was applied to determine the optimal cut-off value.

results851 KD patients who met the inclusion criteria were studied, including 206 in the CALs group and 645 in the non-CALs group. Children in the CALs group had significantly higher CRP levels than the non-CALs group (p < 0.05). Multivariable logistic regression analysis showed that incomplete KD, male, lower hemoglobin, and higher CRP were independent risk factors for predicting CAL (all p < 0.05). The optimal cut-off value of initial serum CRP for predicting CALs was 105.5 mg/L, with a sensitivity of 47.57% and a specificity of 69.61%. In addition, KD patients with high CRP (≥105.5 mg/L) had a higher occurrence of CALs than those with low CRP (<105.5 mg/L) (33% vs 19%, p < 0.001).

conclusionThe incidence of CALs was significantly higher in patients with high CRP. CRP is an independent risk factor for CALs formation and may be useful for predicting CALs in KD patients.

Indexed as

C-Reactive ProteinMucocutaneous Lymph Node SyndromeChildCoronary VesselsHumansImmunoglobulins, IntravenousInfantMaleRetrospective StudiesC-Reactive ProteinImmunoglobulins, IntravenousCoronary artery lesions, CALsC-reactive protein, CRPKawasaki disease, KD

Identifiers

PMID36977496
PMCPMC10373155
OpenAlexW4360955449

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.