Evidence mapPaperPMID 29164077Full record

ReviewJournal of diabetes and metabolic disorders2017

Glucose variability for cardiovascular risk factors in type 2 diabetes: a meta-analysis.

Shuang Liang, Hang Yin, Chunxiang Wei, Linjun Xie, Hua He, Xiaoquan Liu

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of diabetes and metabolic disorders, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 53 citations in OpenAlex.

  1. Trial
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  6. Perioperative glycemic control in patients undergoing cardiac surgery.Kardiochirurgia i torakochirurgia polska = Polish journal of cardio-thoracic surgery · 2025
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  7. Observational
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  18. The Role of Glycemic Variability in Cardiovascular Disorders.International journal of molecular sciences · 2021
    Review
  19. Observational
  20. Observational
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

6 authors at 1 institution in 1 country.

Shuang LiangDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.
Hang YinDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.
Chunxiang WeiDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.
Linjun XieDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.
Hua HeDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.
Xiaoquan LiuDepartment of Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China.ORCID 0000-0002-6224-1024
China Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsIt is consensus that glucose variability (GV) plays an important role in maccomplications of type 2 diabetes, but whether GV has a causal role is not yet clear for cardiovascular disease (CVD). This study sought to explore the effect on GV for CVD risk factors with type 2 diabetes.

methodsThe systematic literature search was performed to identify all GV and CVD risk factors, including total cholesterol (TC), LDL cholesterol (LDL-C), triglyceride (TG), HDL cholesterol (HDL-C), Body Mass Index (BMI), waist circumference (WC), High-Sensitivity C-reactive protein (Hs-CRP), Homeostasis model assessment (HOMA) and carotid intima-media thickness (IMT). Preferred Reporting Items was synthesized for Systematic reviews and Meta Analyses guideline. And the pooled analyses were undertaken using Review Manager 5.3.

resultsTwenty two studies were included with a total of 1143 patients in high glucose variability group (HGVG) and 1275 patients low glucose variability group (LGVG). Among these selected CVD risk factors, HOMA-IR and reduced IMT were affected by GV. HOMA-IR level was significantly lower in LGVG than in HGVG (MD = 0.58, 95% CI: 0.26 to 0.91,

conclusionsAmong these selected CVD risk factors in type 2 diabetes, minimizing GV could improve insulin resistance and reduced IMT, consistent with a lowering in risk of CVD.

Identifiers

PMID29164077
PMCPMC5686902
OpenAlexW2768276443

What Socratic holds

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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.