Evidence mapPaperPMID 35101050Full record

ArticleCardiovascular diabetology2022

Implications of fasting plasma glucose variability on the risk of incident peripheral artery disease in a population without diabetes: a nationwide population-based cohort study.

Hye Soo Chung, Soon Young Hwang, Jung A Kim, Eun Roh, Hye Jin Yoo, Sei Hyun Baik, Nan Hee Kim, Ji A Seo, Sin Gon Kim, Nam Hoon Kim and 1 more

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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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 3 institutions in 2 countries.

Hye Soo ChungDivision of Endocrinology and Metabolism, Department of Internal Medicine, Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, Seoul, South Korea.
Soon Young HwangDepartment of Biostatistics, College of Medicine, Korea University, South Seoul, South Korea.
Jung A KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Eun RohDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Hye Jin YooDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Sei Hyun BaikDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Nan Hee KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Ji A SeoDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Sin Gon KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Nam Hoon KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea.
Kyung Mook ChoiDivision of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, South Korea. medica7@gmail.com.ORCID 0000-0001-6175-0225
Korea University · KRHallym University Kangnam Sacred Heart Hospital · KRKorea University Medical Center · KR

Funding

Korea University Medicine K2115701National Research Foundation of Korea 2018R1D1A1B07049605
6 · The paper itself

Abstract

backgroundDiabetes have been known as a traditional risk factor of developing peripheral artery disease (PAD). However, the study evaluating the impact of long-term glycemic variability on the risk of developing PAD is limited, especially in a general population without diabetes.

methodsWe included 152,931 individuals without diabetes from the Korean National Health Insurance Service-Health Screening Cohort. Fasting plasma glucose (FPG) variability was measured using coefficient variance (FPG-CV), standard deviation (FPG-SD), and variability independent of the mean (FPG-VIM).

resultsA total of 16,863 (11.0%) incident cases of PAD were identified during a median follow-up of 8.3 years. Kaplan-Meier curves showed a progressively increasing risk of PAD in the higher quartile group of FPG variability than in the lowest quartile group (log rank P < 0.001). Multivariable Cox proportional hazard analysis showed the hazard ratio for PAD prevalence as 1.11 (95% CI 1.07-1.16, P < 0.001) in the highest FPG-CV quartile than in the lowest FPG-CV quartile after adjusting for confounding variables, including mean FPG. Similar degree of association was shown in the FPG-SD and FPG-VIM. In sensitivity analysis, the association between FPG variability and the risk of developing PAD persisted even after the participants were excluded based on previously diagnosed diseases, including stroke, coronary artery disease, congestive heart failure, chronic kidney disease, or current smokers or drinkers. Subgroup analysis demonstrated that the effects of FPG variability on the risk of PAD were more powerful in subgroups of younger age, regular exercisers, and those with higher income.

conclusionsIncreased long-term glycemic variability may have a significant prognostic effect for incident PAD in individuals without diabetes.

Indexed as

AdultAgedAge FactorsBiomarkersBlood GlucoseDatabases, FactualExerciseFastingFemaleHumansIncidenceIncomeMaleMiddle AgedPeripheral Arterial DiseasePredictive Value of TestsBiomarkersBlood GlucoseFasting plasma glucoseGlycemic variabilityPeripheral artery disease

Identifiers

PMID35101050
PMCPMC8805289
OpenAlexW4220937328

What Socratic holds

Textmetadata
LicenceCC BY
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.