Evidence map›Paper›PMID 34530763›Full record

ArticleBMC pediatrics2021

Prediction of repeated intravenous immunoglobulin resistance in children with Kawasaki disease.

Yaheng Lu, Tingting Chen, Yizhou Wen, Feifei Si, Xindan Wu, Yanfeng Yang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pediatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
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  3. Observational
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
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  11. [Association between duration of fever before treatment and intravenous immunoglobulin resistance in Kawasaki disease].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2022
    Article
  12. 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

6 authors at 2 institutions in 1 country.

Yaheng LuDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China.
Tingting ChenDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China.
Yizhou WenDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China.
Feifei SiDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China.
Xindan WuDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China.
Yanfeng YangDepartment of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, 611731, Chengdu, China. yfyangcd@163.com.
Chengdu Women's and Children's Central Hospital · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRepeated intravenous immunoglobulin (IVIG) resistance prediction is one of the pivotal topics in Kawasaki disease (KD). Those non-responders of repeated IVIG treatment might be improved by an early-intensified therapy to reduce coronary artery lesion and medical costs. This study investigated predictors of resistance to repeated IVIG treatment in KD.

methodsA total of 94 children with IVIG-resistant KD treated at our hospital between January 2016 and August 2020 were retrospectively analyzed. According to the therapeutic effect of a second dose IVIG treatment, the children were divided into repeated IVIG-responsive group and repeated IVIG-resistant group, and the clinical and laboratory data were compared. Predictors of repeated IVIG resistance and the optimal cut-off value were determined by multiple logistic regression analysis and receiver operating characteristic (ROC) curve analysis.

resultsThe Pre-IVIG laboratory data showed the percentage of neutrophils (N%) and levels of serum procalcitonin (PCT), N-terminal pro-brain natriuretic peptide (NT-proBNP) were significantly higher in repeated IVIG-resistant group compared with repeated IVIG-responsive group, while levels of serum sodium and albumin (ALB) were significantly lower (P < 0.05). The post-IVIG laboratory values of N% and C-reactive protein (CRP) were significantly higher in the repeated IVIG-resistant group compared with repeated IVIG-responsive group, while hemoglobin and ALB were lower (P < 0.05). Pre-IVIG PCT and post-IVIG CRP exhibited AUC of 0.751 and 0.778 respectively in predicting repeated IVIG resistance in KD. Pre-IVIG PCT > 1.81ng/ml (OR 4.1, 95 % CI 1.4 ~ 12.0, P < 0.05) and post-IVIG CRP > 45 mg/L (OR 4.6, 95 % CI 1.3 ~ 16.2, P < 0.05) were independent predictors of repeated IVIG resistance in KD.

conclusionsOur study illustrates the serum PCT level before initial IVIG treatment and CRP after initial IVIG could be used to predict repeated IVIG resistance in KD.

Indexed as

Immunoglobulins, IntravenousMucocutaneous Lymph Node SyndromeChildC-Reactive ProteinHumansProcalcitoninRetrospective StudiesC-Reactive ProteinImmunoglobulins, IntravenousProcalcitoninKawasaki diseasePredictionRepeated intravenous immunoglobulin resistance

Identifiers

PMID34530763
PMCPMC8444587
OpenAlexW3162488978

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.