Evidence map›Paper›PMID 35059265›Full record

ArticleDiabetology international2022

Japanese Type 1 Diabetes Database Study (TIDE-J): rationale and study design.

Daisuke Chujo, Akihisa Imagawa, Kazuki Yasuda, Norio Abiru, Takuya Awata, Tomoyasu Fukui, Hiroshi Ikegami, Eiji Kawasaki, Takeshi Katsuki, Tetsuro Kobayashi and 13 more

Abstract read
In one paragraph

Article in Diabetology international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Protocol of a Prospective Observational Study on Lifestyle and Quality of Life in Adults with Type 1 Diabetes in Japan.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024
    Article
  7. Review
  8. Article
  9. 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

23 authors.

Daisuke ChujoDepartment of Diabetes, Endocrinology, and Metabolism, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjuku, Tokyo, 162-8655 Japan.
Akihisa ImagawaDepartment of Internal Medicine (I), Osaka Medical and Pharmaceutical University, Takatsuki, Japan.
Kazuki YasudaDepartment of Diabetes, Endocrinology, and Metabolism, Kyorin University, Mitaka, Japan.
Norio AbiruDepartment of Endocrinology and Metabolism, Nagasaki University Hospital, Nagasaki, Japan.
Takuya AwataCenter for University-Wide Education, School of Health and Social Service, Saitama Prefectural University, Saitama, Japan.
Tomoyasu FukuiDivision of Diabetes and Endocrinology, Showa University School of Medicine, Tokyo, Japan.
Hiroshi IkegamiDepartment of Endocrinology, Metabolism and Diabetes, Faculty of Medicine, Kindai University, Higashi-Osaka, Japan.
Eiji KawasakiDiabetes Center, Shin-Koga Hospital, Kurume, Japan.
Takeshi KatsukiDepartment of Diabetes and Endocrinology, Tokyo Saiseikai Central Hospital, Tokyo, Japan.
Tetsuro KobayashiDivision of Immunology and Molecular Medicine, Okinaka Memorial Institute for Medical Research, Tokyo, Japan.
Junji KozawaDepartment of Metabolic Medicine, Graduate School of Medicine, Osaka University, Suita, Japan.
Kan NagasawaDivision of Diabetes, Metabolism, and Endocrine Medicine Field, Iwate Medical University, Shiwa, Japan.
Hiroshi OhtsuDepartment of Date Science, National Center for Global Health and Medicine, Tokyo, Japan.
Yoichi OikawaDepartment of Endocrinology and Diabetes, School of Medicine, Saitama Medical University, Iruma, Japan.
Haruhiko OsawaDepartment of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Toon, Japan.
Akira ShimadaDepartment of Endocrinology and Diabetes, School of Medicine, Saitama Medical University, Iruma, Japan.
Masayuki ShimodaIslet Cell Transplantation Project, National Center for Global Health and Medicine, Tokyo, Japan.
Kazuma TakahashiIwate Prefectural University, Takizawa, Japan.
Kyoichiro TsuchiyaDepartment of Diabetes and Endocrinology, University of Yamanashi Hospital, Yamanashi, Japan.
Tetsuro TsujimotoDepartment of Diabetes and Endocrinology, Toranomon Hospital Kajigaya, Kawasaki, Japan.
Hisafumi YasudaDivision of Health Sciences, Department of Public Health, Kobe University Graduate School of Health Sciences, Kobe, Japan.
Toshiaki HanafusaDepartment of Internal Medicine (I), Osaka Medical and Pharmaceutical University, Takatsuki, Japan.
Hiroshi KajioDepartment of Diabetes, Endocrinology, and Metabolism, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjuku, Tokyo, 162-8655 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 1 diabetes (T1D) is classified into three subtypes: acute-onset, slowly progressive, and fulminant T1D, according to the heterogeneity of clinical course in Japan. Although several cross-sectional databases of T1D have been reported, prospective longitudinal databases to investigate clinical outcomes are lacking in our country. Therefore, we herein construct multi-center prospective longitudinal database of the three subtypes of T1D, accompanied with genetic information and biobanking, which is named Japanese Type 1 Diabetes Database Study (TIDE-J). Inclusion criteria of this study are as follows: (1) the duration of T1D was less than 5 years, (2) the patients had one or more islet-related autoantibodies and/or fasting serum C-peptide levels were less than 1.0 ng/mL, (3) the patients could clearly understand the study consent in writing. In the TIDE-J, clinical data, including glycemic control, endogenous insulin secretion, islet-related autoantibodies, diabetic complications, and treatment, are collected annually using electric data collection system, which is named REDCap. Furthermore, HLA genotypes of each participant were analyzed at entry and the blood samples were stored for assessing exploratory markers and further genetic analysis annually. The TIDE-J certainly helps in revealing distinct clinical course of each T1D subtype. Moreover, this database may help in identifying novel markers for diagnosing each subtype of T1D and predicting clinical outcomes (including pancreatic beta cell function and disease severity) in patients.

Indexed as

DatabaseElectric data collectionMulti-centerType 1 diabetes

Identifiers

PMID35059265
PMCPMC8733142

What OpenQuestion holds

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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.