Evidence map›Paper›PMID 24755655›Full record

ArticlePloS one2014

Development of an HbA1c-based conversion equation for estimating glycated albumin in a Korean population with a wide range of glucose intolerance.

Chang Hee Jung, You-Cheol Hwang, Kwang Joon Kim, Bong Soo Cha, Cheol-Young Park, Won Seon Jeon, Jae Hyeon Kim, Sang-Man Jin, Sang Youl Rhee, Jeong-Taek Woo and 1 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in PloS one, 2014. 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 26% 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, 8 citations in OpenAlex.

  1. GLYCATED ALBUMIN AT 4 WEEKS CORRELATES WITH A1C LEVELS AT 12 WEEKS AND REFLECTS SHORT-TERM GLUCOSE FLUCTUATIONS.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2015
    Trial
  2. Article
  3. Review
  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

11 authors at 6 institutions in 1 country.

Chang Hee JungDepartment of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
You-Cheol HwangDepartment of Internal Medicine, Kyung Hee University School of Medicine, Seoul, Korea.
Kwang Joon KimDepartment of Internal Medicine, Severance Hospital, University of Yonsei University College of Medicine, Seoul, Korea.
Bong Soo ChaDepartment of Internal Medicine, Severance Hospital, University of Yonsei University College of Medicine, Seoul, Korea.
Cheol-Young ParkDepartment of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
Won Seon JeonDepartment of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jae Hyeon KimDepartment of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Sang-Man JinDepartment of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Sang Youl RheeDepartment of Internal Medicine, Kyung Hee University School of Medicine, Seoul, Korea.
Jeong-Taek WooDepartment of Internal Medicine, Kyung Hee University School of Medicine, Seoul, Korea.
Byung-Wan LeeDepartment of Internal Medicine, Severance Hospital, University of Yonsei University College of Medicine, Seoul, Korea.
Kyung Hee University · KRYonsei University · KRSungkyunkwan University · KRKangbuk Samsung Hospital · KRSamsung Medical Center · KRUniversity of Ulsan · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCompared to the golden standard glycation index of HbA1c, glycated albumin (GA) has potentials for assessing insulin secretory dysfunction and glycemic fluctuation as well as predicting diabetic vascular complications. However, the reference ranges of GA and a conversion equation need to be clearly defined. We designed this study to determine the reference ranges in patients with normal glucose tolerance (NGT) based on conventional measures of glycemic status and to devise a conversion equation for calculating HbA1c and GA in a Korean population. METHODOLOGY/PRINCIPAL

findingsIn this multicenter, retrospective, cross-sectional study, we recruited antidiabetic drug-naïve patients with available glycemic variables including HbA1c, GA, and fasting plasma glucose regardless of glucose status. For the reference interval of serum GA, 5th to 95th percentile value of GA in subjects with NGT was adopted. The conversion equation between HbA1c and GA was devised using an estimating regression model with unknown break-points method. The reference range for GA was 9.0-14.0% in 2043 subjects. The 95th percentile responding values for FPG, and HbA1c were approximately 5.49 mmol/l, and 5.6%, respectively. The significant glycemic turning points were 5.868% HbA1c and 12.2% GA. The proposed conversion equation for below and above the turning point were GA (%) = 6.960+0.8963 × HbA1c (%) and GA (%) = -9.609+3.720 × HbA1c (%), respectively. CONCLUSIONS/SIGNIFICANCE: These results should be helpful in future studies on the clinical implications of high GA relative to HbA1c and the clinical implementation of diabetes management.

Indexed as

Asian PeoplePublic Health SurveillanceAdultAgedBlood GlucoseCross-Sectional StudiesFemaleGlucose IntoleranceGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, AdvancedHumansMaleMiddle AgedRepublic of KoreaRetrospective StudiesBlood GlucoseGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, AdvancedSerum Albumin

Identifiers

PMID24755655
PMCPMC3995757
OpenAlexW2007481894

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.