Evidence map›Paper›PMID 32958798›Full record

ArticleScientific reports2020

Prognostic value of long-term gamma-glutamyl transferase variability in individuals with diabetes: a nationwide population-based study.

Da Young Lee, Kyungdo Han, Ji Hee Yu, Sanghyun Park, Ji A Seo, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Seon Mee Kim, Kyung Mook Choi and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Review
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

13 authors at 2 institutions in 1 country.

Da Young Lee *Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Kyungdo Han *Department of Biostatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
Ji Hee YuDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Sanghyun ParkDepartment of Biostatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.
Ji A SeoDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Nam Hoon KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Hye Jin YooDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Sin Gon KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Seon Mee KimDepartment of Family Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Kyung Mook ChoiDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Sei Hyun BaikDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
Yong Gyu ParkDepartment of Biostatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. ygpark@catholic.ac.kr.
Nan Hee KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea. nhkendo@gmail.com.
Korea University · KRCatholic University of Korea · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We examined whether long-term gamma-glutamyl transferase (GGT) variability can predict cardiovascular disease (CVD) and mortality in individuals with diabetes. We included 698,937 Koreans diabetes patients older than 40 years without histories of CVD, chronic liver disease, or heavy alcoholics who received health exams supported by the Korean government more than once in 2009-2012 (baseline). We used Cox proportional analyses to estimate the risk of stroke, myocardial infarction (MI), and all-cause mortality until December 31, 2016, according to the quartiles of the average successive variability (ASV) of GGT measured during the five years before the baseline. A total 26,119, 15,103, and 39,982 cases of stroke, MI, and death, respectively, were found. GGT ASV quartile 4 had a significantly higher risk of stroke and all-cause mortality than quartile 1, with adjustment for risk factors, such as baseline glucose and GGT level, and comorbidities. Hazard ratios (95% confidence intervals) for GGT ASV quartile 4 were 1.06 (1.03-1.10) and 1.23 (1.20-1.27) for stroke and mortality, respectively. This significant association was shown consistently across the baseline GGT quartiles. GGT variability was related to the risk of stroke and all-cause mortality. The effect was most pronounced in all-cause mortality, irrespective of baseline GGT level.

Indexed as

Diabetes MellitusFemalegamma-GlutamyltransferaseGlucoseHumansLongitudinal StudiesMaleMiddle AgedMyocardial InfarctionPrognosisProportional Hazards ModelsRisk FactorsStrokegamma-GlutamyltransferaseGlucose

Identifiers

PMID32958798
PMCPMC7506020
OpenAlexW3087610914

What OpenQuestion holds

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LicenceCC BY
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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.