Evidence map›Paper›PMID 36051323›Full record

ArticleGlobal heart2022

Prediction of Five-Year Cardiovascular Disease Risk in People with Type 2 Diabetes Mellitus: Derivation in Nanjing, China and External Validation in Scotland, UK.

Cheng Wan, Stephanie Read, Honghan Wu, Shan Lu, Xin Zhang, Sarah H Wild, Yun Liu

Open access · goldAbstract read
In one paragraph

Article in Global heart, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. 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

7 authors at 4 institutions in 3 countries.

Cheng Wan *Department of Medical Informatic, School of Biomedical Engineering and Informatics, Nanjing Medical University, CN.ORCID 0000-0002-2981-5970
Stephanie Read *Women's College Research Institute, Women's College Hospital, Toronto, CA.
Honghan WuInstitute of Health Informatics, University College London, London, UK.ORCID 0000-0002-0213-5668
Shan LuOutpatient department, the First Affiliated Hospital, Nanjing Medical University, CN.ORCID 0000-0002-9534-3422
Xin ZhangDepartment of Information, the First Affiliated Hospital, Nanjing Medical University, China.ORCID 0000-0003-0047-3134
Sarah H WildUsher Institute, University of Edinburgh, GB.ORCID 0000-0001-7824-2569
Yun LiuDepartment of Medical Informatic, School of Biomedical Engineering and Informatics, Nanjing Medical University, CN.ORCID 0000-0003-4877-1878
Nanjing Medical University · CNUniversity College London · GBUniversity of Edinburgh · GBWomen's College Hospital · CA

Funding

Medical Research Council MC_PC_18029Medical Research Council MR/S004149/2
6 · The paper itself

Abstract

Background: To use routinely collected data to develop a five-year cardiovascular disease (CVD) risk prediction model for Chinese adults with type 2 diabetes with validation of its performance in a population of European ancestry. Methods: People with incident type 2 diabetes and no history of CVD at diagnosis of diabetes between 2008 and 2017 were included in derivation and validation cohorts. The derivation cohort was identified from a pseudonymized research extract of data from the First Affiliated Hospital of Nanjing Medical University (NMU). Five-year risk of CVD was estimated using basic and extended Cox proportional hazards regression models including 6 and 11 predictors respectively. The risk prediction models were internally validated and externally validated in a Scottish population-based cohort with CVD events identified from linked hospital records. Discrimination and calibration were assessed using Harrell's C-statistic and calibration plots, respectively. Results: Mean age of the derivation and validation cohorts were 58.4 and 59.2 years, respectively, with 53.5% and 56.9% men. During a median follow-up time of 4.75 [2.67, 7.42] years, 18,827 (22.25%) of the 84,630 people in the NMU-Diabetes cohort and 8,763 (7.31%) of the Scottish cohort of 119,891 people developed CVD. The extended model had a C-statistic of 0.723 [0.721-0.724] in internal validation and 0.716 [0.713-0.719] in external validation. Conclusions: It is possible to generate a risk prediction model with moderate discriminative power in internal and external validation derived from routinely collected Chinese hospital data. The proposed risk score could be used to improve CVD prevention in people with diabetes.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2AdultChinaFemaleHumansMaleMiddle AgedRisk AssessmentRisk FactorsScotlandderivation and external validationfive-year cardiovascular disease riskroutinely collected hospital datatype 2 diabetes mellitus

Identifiers

PMID36051323
PMCPMC9336685
OpenAlexW4288096175

What OpenQuestion holds

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LicenceCC BY
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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.