Evidence map›Paper›PMID 34236576›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2021

The Impact of Different Insulin-Related Measures on the Risk of Prediabetes Among the Chinese Han Population.

Huibiao Quan, Tuanyu Fang, Leweihua Lin, Lu Lin, Qianying Ou, Huachuan Zhang, Kaining Chen, Zhiguang Zhou

Open access · goldAbstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2021. 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
0.1field-weighted citation impact, top 49% 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

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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, 1 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Huibiao QuanDepartment of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No. 139, Renmin Middle Road, Furong District, Changsha, 410011, Hunan Province, China.
Tuanyu FangDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Leweihua LinDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Lu LinDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Qianying OuDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Huachuan ZhangDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Kaining ChenDepartment of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19, Xiuhua Road, Haikou, 570311, Hainan, China.
Zhiguang ZhouDepartment of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No. 139, Renmin Middle Road, Furong District, Changsha, 410011, Hunan Province, China. zhouzhiguang@csu.edu.cn.
Hainan General Hospital · CNHainan Medical University · CNSecond Xiangya Hospital of Central South University · CN

Funding

Hainan Provincial Key Research and Development Project ZDYF2018130National Natural Science Foundation of China 81820108007the National Key Research and Development Program of China 2016YFC1305000the National Key Research and Development Program of China 2016YFC1305001the National Key Research and Development Program of China 2018YFC1315603
6 · The paper itself

Abstract

introductionDiabetes mellitus (DM) has a serious impact on people's lives in the world. Interventions that affect risk factors for prediabetes can prevent and reduce diabetes occurrence. Proinsulin (PI), true insulin (TI), and proinsulin to insulin ratio (PI/TI) are risk factors for diabetes. The roles of these indicators in prediabetes are unclear. This study aimed to evaluate the impact of PI, TI, PI/TI, 2-h proinsulin (2hPI), 2-h true insulin (2hTI), and 2hPI/2hTI on the risk of prediabetes among the Chinese Han population.

methodsThis cross-sectional study recruited 1688 subjects including 718 prediabetes cases and 970 non-prediabetes controls from Hainan Affiliated Hospital of Hainan Medical University. The cases involved 292 men and 426 women. The controls involved 324 men and 646 women. The mean age was 53.62 ± 12.43 years in the prediabetes group and 44.24 ± 12.87 years in the non-prediabetes group.

resultsOur results showed that PI, TI, PI/TI, 2hPI, 2hTI, and 2hPI/2hTI were significantly correlated with prediabetes (all p < 0.05). Logistic regression analysis revealed that PI (OR 1.022, 95% CI 1.014-1.031, p = 0.00011), TI (OR 1.005, 95% CI 1.003-1.007, p = 0.00012), PI/TI (OR 1.517, 95% CI 1.080-2.131, p = 0.016), and 2hTI (OR 1.000, 95% CI 1.000-1.001, p = 0.002) were significantly associated with an increased risk of prediabetes. Receiver operating characteristic curve (ROC) analysis indicated that the area under the ROC curve (AUC) of the combination (PI + TI + PI/TI + 2hPI + 2hTI + 2hPI/2hTI) in diagnosing prediabetes was 0.627, which was larger than the diagnostic value of HOMA-IR (AUC 0.614) and HOMA-β (AUC 0.387).

conclusionsOur study showed that PI, TI, PI/TI, and 2hTI could significantly enhance the risk of prediabetes in the Chinese Han population, which suggested that PI, TI, PI/TI, and 2hTI might be available risk factors for prediabetes.

Indexed as

InsulinPrediabetesProinsulinRisk

Identifiers

PMID34236576
PMCPMC8342746
OpenAlexW3177947407

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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.