Evidence map›Paper›PMID 34420154›Full record

ArticleEuropean journal of epidemiology2021

Rationale, design and population description of the CREDENCE study: cardiovascular risk equations for diabetes patients from New Zealand and Chinese electronic health records.

Jingyuan Liang, Romana Pylypchuk, Xun Tang, Peng Shen, Xiaofei Liu, Yi Chen, Jing Tan, Jinguo Wu, Jingyi Zhang, Ping Lu and 3 more

Abstract read
In one paragraph

Article in European journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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

13 authors.

Jingyuan Liang *Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.ORCID http://orcid.org/0000-0002-3489-5776
Romana Pylypchuk *Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, 30 Park Avenue, Grafton, Auckland, 1023, New Zealand.
Xun TangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.ORCID http://orcid.org/0000-0002-6990-0168
Peng ShenYinzhou District Center for Disease Control and Prevention, Ningbo, China.
Xiaofei LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
Yi ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
Jing TanChinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.
Jinguo WuWonders Information Co. Ltd, Shanghai, China.
Jingyi ZhangWonders Information Co. Ltd, Shanghai, China.
Ping LuWonders Information Co. Ltd, Shanghai, China.
Hongbo LinYinzhou District Center for Disease Control and Prevention, Ningbo, China.
Pei GaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Beijing, 100191, China. peigao@bjmu.edu.cn.ORCID http://orcid.org/0000-0001-8649-1290
Rod JacksonSection of Epidemiology and Biostatistics, School of Population Health, University of Auckland, 30 Park Avenue, Grafton, Auckland, 1023, New Zealand. rt.jackson@auckland.ac.nz.ORCID http://orcid.org/0000-0001-5914-6934

Funding

Beijing Natural Science Foundation 7182084Health Research Council of New Zealand (HRC) HRC 03/183Health Research Council of New Zealand (HRC) HRC 08/121Health Research Council of New Zealand (HRC) HRC VIEW 11/800 programmeNational Key Research and Development Program of China No.2020YFC2003503National Natural Science Foundation of China (NSFC) 81961128006National Natural Science Foundation of China (NSFC) 81973132New Zealand Healthier Lives National Science Challenge HL-T1CR-B
6 · The paper itself

Abstract

The cardiovascular risk equations for diabetes patients from New Zealand and Chinese electronic health records (CREDENCE) study is a unique prospectively designed investigation of cardiovascular risk in two large contemporary cohorts of people with type 2 diabetes from New Zealand (NZ) and China. The study was designed to derive equivalent cardiovascular risk prediction equations in a developed and a developing country, using the same epidemiological and statistical methodology. Two similar cohorts of people with type 2 diabetes were identified from large general population studies in China and New Zealand, which had been generated from longitudinal electronic health record systems. The CREDENCE study aims to determine whether cardiovascular risk prediction equations derived in patients with type 2 diabetes in a developed country are applicable in a developing country, and vice versa, by deriving and validating equivalent diabetes-specific cardiovascular risk prediction models from the two countries. Baseline data in CREDENCE was collected from October 2004 in New Zealand and from January 2010 in China. In the first stage of CREDENCE, a total of 93,207 patients (46,649 from NZ and 46,558 from China) were followed until December 31st 2018. Median follow-up was 7.0 years (New Zealand) and 5.7 years (China). There were 5926 (7.7% fatal) CVD events in the New Zealand cohort and 3650 (8.8% fatal) in the Chinese cohort. The research results have implications for policy makers, clinicians and the public and will facilitate personalised management of cardiovascular risk in people with type 2 diabetes worldwide.

Indexed as

AlbuminuriaCardiovascular DiseasesChinaCohort StudiesCreatinineDiabetes Mellitus, Type 2Electronic Health RecordsFemaleGlycated HemoglobinHumansMaleNew ZealandRisk AssessmentRisk FactorsSensitivity and SpecificityCreatinineGlycated Hemoglobinhemoglobin A1c protein, humanCardiovascular diseaseCohortDiabetesElectronic health recordsRisk prediction

Identifiers

PMID34420154
PMCPMC8542537

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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.