Evidence map›Paper›PMID 34563210›Full record

ArticlePediatric rheumatology online journal2021

Predictive value of Albumin-Bilirubin grade for intravenous immunoglobulin resistance in a large cohort of patients with Kawasaki disease: a prospective study.

Yu Yan, Lina Qiao, Yimin Hua, Shuran Shao, Nanjun Zhang, Mei Wu, Lei Liu, Kaiyu Zhou, Xiaoliang Liu, Chuan Wang

Open access · goldAbstract read
In one paragraph

Article in Pediatric rheumatology online journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 9 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 3 institutions in 1 country.

Yu Yan *Department of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Lina Qiao *Department of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Yimin Hua *Department of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Shuran ShaoDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Nanjun ZhangDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Mei WuKey Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Sichuan, 610041, Chengdu, China.
Lei LiuDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Kaiyu ZhouDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
Xiaoliang LiuDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China. sdigjoy@qq.com.
Chuan WangDepartment of Pediatric Cardiology, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China. 805101396@qq.com.
Sichuan University · CNWest China Second University Hospital of Sichuan University · CNWest China Medical Center of Sichuan University · CN

Funding

National Key R&D Program of China 2018YFC1002301National Natural Science Foundation of China 81800288National Natural Science Foundation of China 81971457National Natural Science Foundation of China 82070324Science-technology Support Plan Projects in Sichuan province 2017SZ0117Science-technology Support Plan Projects in Sichuan province 2019YFS0243Science-technology Support Plan Projects in Sichuan province 2020YFS0101Science-technology Support Plan Projects in Sichuan province 2020YJ0234
6 · The paper itself

Abstract

backgroundIntravenous immunoglobulin (IVIG) resistance prediction is one of the primary clinical issues and study hotspots in KD. This study aimed to prospectively investigate the value of albumin-bilirubin grade (ALBI) in predicting IVIG resistance in KD and to assess whether ALBI has more predictive value or accuracy than either ALB or TBil alone in predicting IVIG resistance.

methodsA total of 823 patients with KD were prospectively enrolled. The clinical and laboratory data were compared between the IVIG-response group (n = 708) and the IVIG-resistance group (n = 115). Multivariate logistic regression analysis was performed to identify the independent risk factors for IVIG resistance. Receiver operating characteristic (ROC) curves analysis was applied to assess the validity of ALBI, ALB, and TBil in predicting IVIG resistance.

resultsALBI was significantly higher in patients with IVIG resistance and was identified as an independent risk factor for IVIG resistance in KD. The parameter of ALBI ≥ - 2.57 (AUC: 0.705, 95 %CI: 0.672-0.736), ALB ≤ 33.0 g/L (AUC: 0.659, 95 %CI: 0.626-0.692), and TBil ≥ 16.0µmol/L (AUC: 0.626, 95 %CI: 0.592-0.659), produced a sensitivity, specificity, PPV, and NPV of 0.617, 0.657, 0.226 and 0.914; 0.374, 0.850, 0.289 and 0.893; 0.269, 0.941, 0.425 and 0.888, respectively.

conclusionsA higher ALBI was an independent risk factor for IVIG resistance in KD. It yielded better predictive ability than ALB and TBil alone for initial IVIG resistance.

Indexed as

BilirubinChild, PreschoolCohort StudiesDrug ResistanceFemaleHumansImmunoglobulins, IntravenousInfantMaleMucocutaneous Lymph Node SyndromePredictive Value of TestsProspective StudiesSerum AlbuminBilirubinImmunoglobulins, IntravenousSerum Albuminalbumin-bilirubin gradeintravenous immunoglobulin resistanceKawasaki disease

Identifiers

PMID34563210
PMCPMC8467146
OpenAlexW3161526339

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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.