Evidence map›Paper›PMID 36918446›Full record

ArticleClinical rheumatology2023

Correction to: A simple scoring model based on machine learning predicts intravenous immunoglobulin resistance in Kawasaki disease.

Yuto Sunaga, Atsushi Watanabe, Nobuyuki Katsumata, Takako Toda, Masashi Yoshizawa, Yosuke Kono, Yohei Hasebe, Keiichi Koizumi, Minako Hoshiai, Eiryo Kawakami and 1 more

Abstract readPublished Erratum
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical rheumatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Yuto SunagaFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Atsushi WatanabeFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Nobuyuki KatsumataFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Takako TodaFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan. takakotojp@yahoo.co.jp.ORCID https://orcid.org/0000-0003-0947-1290
Masashi YoshizawaFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Yosuke KonoFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Yohei HasebeFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Keiichi KoizumiFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Minako HoshiaiFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.
Eiryo KawakamiArtificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan.
Takeshi InukaiFaculty of Medicine, Department of Pediatrics, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi, 409-3898, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID36918446
PMCPMC10102140

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.