Evidence map›Paper›PMID 26576838›Full record

ArticleQJM : monthly journal of the Association of Physicians2016

Normal fasting plasma glucose predicts type 2 diabetes and cardiovascular disease in elderly population in Taiwan.

C-L Huang, H-W Chang, J-B Chang, J-H Chen, J-D Lin, C-Z Wu, D Pei, Y-J Hung, C-H Lee, Y-L Chen and 1 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in QJM : monthly journal of the Association of Physicians, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

6 citing papers in PubMed, 12 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

11 authors at 4 institutions in 1 country.

C-L HuangFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
H-W ChangFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
J-B ChangDivision of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
J-H ChenFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
J-D LinDivision of Endocrinology and Metabolism, Department of Internal Medicine, Shuang-Ho Hospital, Taipei Medical University, Taipei, Taiwan.
C-Z WuDivision of Endocrinology and Metabolism, Cardinal Tien Hospital, New Taipei City, Taiwan and.
D PeiDivision of Endocrinology and Metabolism, Cardinal Tien Hospital, New Taipei City, Taiwan and.
Y-J HungFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
C-H LeeFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
Y-L ChenDepartment of Pathology, Cardinal Tien Hospital, New Taipei City, Taiwan.
C-H HsiehFrom the Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan 10324peter@gmail.com.
Tri-Service General Hospital · TWCardinal Tien Hospital · TWNational Defense Medical Center · TWTaipei Medical University-Shuang Ho Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperglycemia increases prevalence of metabolic syndrome (MetS), type 2 diabetes (T2D) and cardiovascular disease (CVD). But the role of normoglycemia on the development of T2D and CVD in elderly population remains unclear.

aimTo determine an optimal cut-off for fasting plasma glucose (FPG) to predict MetS and subsequent risk of T2D and CVD in an elderly Taiwanese population with normal FPG levels.

designTwo stages included cross-sectional (Stage 1) and prospective (Stage 2) cohort study.

methodsIn Stage 1 18 287 subjects aged  ≥60 years were enrolled; of these, 5039 without T2D and CVD advanced to Stage 2 and a mean follow-up of 3.8 years. MetS components were analysed, and in Stage 1, FPG cut-offs for MetS risk were calculated using receiver operating characteristic (ROC) curve analyses. In Stage 2, subjects without T2D and CVD in Stage 1 were classified into high-FPG and low-FPG groups based on cut-offs, and sex specific differences in incidence for T2D and CVD were calculated.

resultsROC curve analysis gave an optimal FPG cut-off for MetS of 93 mg/dl and 92 mg/dl for males and females, respectively. The high-FPG group had a 1.599- and 1.353-fold higher chance of developing T2D compared with the low-FPG group for males and females, respectively (95% CI: 1.606-2.721 and 1.000-1.831, P  =  0.015 and 0.05). The high-FPG group had a 1.24-fold higher chance of developing CVD for females (95% CI: 1.015-1.515, P  =  0.035); however, there was no difference for males.

conclusionsOur results suggest that FPG within the normal range was associated with MetS, and elderly subjects with high normal levels have a higher incidence of developing T2D for both sexes, and CVD for females, over the short-term.

Indexed as

AgedAnthropometryBlood GlucoseCardiovascular DiseasesCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleHumansLinear ModelsMaleMetabolic SyndromeMiddle AgedMultivariate AnalysisProportional Hazards ModelsProspective StudiesROC CurveBlood Glucose

Identifiers

PMID26576838
PMCPMC4986423
OpenAlexW2179638484

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.