Evidence map›Paper›PMID 32838756›Full record

ArticleBMC pediatrics2020

Neutrophil-to-lymphocyte ratio and scoring system for predicting coronary artery lesions of Kawasaki disease.

Ling-Sai Chang, Yi-Ju Lin, Jia-Huei Yan, Mindy Ming-Huey Guo, Mao-Hung Lo, Ho-Chang Kuo

Open access · goldAbstract read
In one paragraph

Article in BMC pediatrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 3 pooled it
8.0field-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

47 citing papers in PubMed, 3 syntheses or guidelines pooled it, 65 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. METTL3-mediated mApplied biochemistry and biotechnology · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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 3 institutions in 1 country.

Ling-Sai ChangDepartment of Pediatrics and Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, #123 Da-Pei Road, Niaosong District, 83301, Kaohsiung, Taiwan.
Yi-Ju LinDepartment of Pediatrics and Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, #123 Da-Pei Road, Niaosong District, 83301, Kaohsiung, Taiwan.
Jia-Huei YanDepartment of Pediatrics, Chiayi Chang Gung Memorial Hospital, Chiayi City, Taiwan.
Mindy Ming-Huey GuoDepartment of Pediatrics and Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, #123 Da-Pei Road, Niaosong District, 83301, Kaohsiung, Taiwan.
Mao-Hung LoDepartment of Pediatrics and Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, #123 Da-Pei Road, Niaosong District, 83301, Kaohsiung, Taiwan.
Ho-Chang KuoDepartment of Pediatrics and Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, #123 Da-Pei Road, Niaosong District, 83301, Kaohsiung, Taiwan. erickuo48@yahoo.com.tw.
Kaohsiung Chang Gung Memorial Hospital · TWChang Gung University · TWChiayi Chang Gung Memorial Hospital · TW

Funding

Chang Gung Memorial Hospital 8F1911, 1921, 1931, and 1941; 8E0212; and CORPG8F0012Chang Gung Memorial Hospital CMRPG8K0641, 8H1161the Ministry of Science and Technology, Taiwan MOST 108-2314-B-182 -037 -MY3
6 · The paper itself

Abstract

backgroundKawasaki disease (KD) causes coronary artery lesions (CAL) and is the leading cause of acquired heart disease in children. The aim of this study is to evaluate the risk factors and set-up a scoring system for predicting CAL of KD.

methodsWe retrospectively reviewed a total of 478 patients diagnosed with KD. We compared age, gender, laboratory data, and treatment response in two groups and developed a scoring system for predicting CAL.

resultsDuring the study period, 365 of these patients had complete medical records of coronary surveys by echocardiography. Anemia, hypoalbuminemia, C reactive protein (CRP), alanine aminotransferase, neutrophil count, and neutrophil/lymphocyte ratio (NLR) showed significant differences with CAL formation. We determined the cut-off value using a receiver-operating-characteristic (ROC) curve, and following multivariate logistic regression analysis, four independent risk factors demonstrated a significant difference with CAL formation, including CRP > 103 mg/L, NLR > 3.5, male gender, and intravenous immunoglobulin (IVIG) resistance. We established a score system based on the above evaluation, for which a ROC curve was performed, and a total score of ≥ 2 points showed a sensitivity of 60.8% and a specificity of 70.6%, with an area under the ROC curve of 0.696.

conclusionsIdentifying children at risk is important in order to prevent CAL from developing. Four independent risk factors that can predict CAL formation were CRP > 103 mg/L, NLR > 3.5, male gender, and IVIG resistance. This first report incorporated NLR into score systems to predict CAL reinforces previously well-known risk factors for the CAL formation among KD patients.

Indexed as

Coronary Artery DiseaseMucocutaneous Lymph Node SyndromeChildCoronary VesselsHumansImmunoglobulins, IntravenousInfantLymphocytesMaleNeutrophilsRetrospective StudiesImmunoglobulins, IntravenousCoronary Artery LesionsCRPIVIG resistanceKawasaki DiseaseNeutrophil-to-Lymphocyte RatioScoring System

Identifiers

PMID32838756
PMCPMC7446151
OpenAlexW3081389914

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.