Evidence map›Paper›PMID 24099651›Full record

ArticleBMC endocrine disorders2013

Combining glycosylated hemoglobin A1c and fasting plasma glucose for diagnosis of type 2 diabetes in Chinese adults.

Miao Mo, Weijian Zhong, Genming Zhao, Ye Ruan, Hua Zhang, Liang Shi, Dajiang Lu, Qundi Yang, Yanyun Li, Qingwu Jiang and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 16 citations in OpenAlex.

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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

12 authors at 4 institutions in 2 countries.

Miao MoDepartment of Epidemiology, School of Public Health; Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai 200032, People's Republic of China. rli@scdc.sh.cn.
Weijian Zhong
Genming Zhao
Ye Ruan
Hua Zhang
Liang Shi
Dajiang Lu
Qundi Yang
Yanyun Li
Qingwu Jiang
Rui Li
Wang-Hong Xu
Shanghai Municipal Center For Disease Control Prevention · CNFudan University · CNMinistry of Education · KRShanghai University of Sport · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlycosylated hemoglobin A1c (HbA1c) has been applied to identify type 2 diabetes (T2DM) in the U.S. and European countries. It has not been used in China mainly due to lack of a standardized approach to measure HbA1c, short of knowledge about racial-specific standard and deficiency of an optimal cut-off point.

methodsTo evaluate combination of HbA1c and fasting plasma glucose (FPG) in diagnosing T2DM in Chinese adults, a multistage sampling cross-sectional study was conducted in Shanghai, China, in 2009. The FPG measurement, HbA1c assay, and oral glucose tolerance test (OGTT) were performed in 6,661 Chinese adults (3057 men, 3604 women) who had no prior history of diabetes to identify the unrecognized T2DM.

resultsA total of 454 participants were identified as T2DM based on the 1999 World Health Organization (WHO) diagnostic criteria. Of these patients, 239 were detected using an FPG ≥ 7.0 mmol/l and 141 were further identified using an HbA1c ≥ 43 mmol/mol (6.1%), achieving a sensitivity of 83.7% and a specificity of 89.3% for combining use of FPG and HbA1c. In subjects at high risk of diabetes, the combining use of FPG and HbA1c produced a higher sensitivity and an improved positive predictive value (PPV), and had a satisfactory specificity and negative predictive value (NPV).

conclusionsThe combining use of FPG and HbA1c is a potential screening and diagnosis approach for T2DM in Chinese adults, especially among those at high risk of the disease.

Identifiers

PMID24099651
PMCPMC3853138
OpenAlexW1968402626

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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.