Evidence map›Paper›PMID 36940011›Full record

ArticleEndocrine2023

Development and validation of a nomogram to estimate future risk of type 2 diabetes mellitus in adults with metabolic syndrome: prospective cohort study.

Tongyue Yang, Jiao Wang, Lina Wu, Feng Guo, Fengjuan Huang, Yi Song, Na Jing, Mengxing Pan, Xiaoxu Ding, Zhe Cao and 3 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Endocrine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

13 authors at 1 institution in 1 country.

Tongyue YangDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Jiao WangDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Lina WuDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Feng GuoDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Fengjuan HuangDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Yi SongDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Na JingDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Mengxing PanDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Xiaoxu DingDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Zhe CaoDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Shiyu LiuDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Guijun QinDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Yanyan ZhaoDivision of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. fcczhaoyy1@zzu.edu.cn.ORCID 0000-0001-6294-9447
First Affiliated Hospital of Zhengzhou University · CN

Funding

National Key Research and Development Program of China 2017YFC1309800National Natural Science Foundation of China U2004116
6 · The paper itself

Abstract

objectivesTo develop and validate the 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome.

designRetrospective cohort study of a large multicenter cohort with broad validation. SETTINGS: The derivation cohort was from 32 sites in China and the geographic validation cohort was from Henan population-based cohort study.

results568 (17.63) and 53 (18.67%) participants diagnosed diabetes during 4-year follow-up in the developing and validation cohort, separately. Age, gender, body mass index, diastolic blood pressure, fasting plasma glucose and alanine aminotransferase were included in the final model. The area under curve for the training and external validation cohort was 0.824 (95% CI, 0.759-0.889) and 0.732 (95% CI, 0.594-0.871), respectively. Both the internal and external validation have good calibration plot. A nomogram was constructed to predict the probability of diabetes during 4-year follow-up, and on online calculator is also available for a more convenient usage ( https://lucky0708.shinyapps.io/dynnomapp/ ).

conclusionWe developed a simple diagnostic model to predict 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome, which is also available as web-based tools ( https://lucky0708.shinyapps.io/dynnomapp/ ).

Indexed as

Diabetes Mellitus, Type 2Metabolic SyndromeAdultCohort StudiesHumansNomogramsProspective StudiesRetrospective StudiesDiagnostic modelMetabolic syndromeNomogramRisk factorsType 2 diabetes mellitus

Identifiers

PMID36940011
OpenAlexW4327893417

What OpenQuestion holds

Textmetadata
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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.