Evidence map›Paper›PMID 35435323›Full record

ArticleJournal of diabetes investigation2022

Comparison of glucose time in range and area under curve in range in relation to risk of diabetic retinopathy in type 2 diabetes patients.

Yaxin Wang, Jingyi Lu, Yun Shen, Jiaying Ni, Lei Zhang, Wei Lu, Wei Zhu, Yuqian Bao, Jian Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes investigation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Observational
  4. Article
  5. Article
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  7. Review
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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

9 authors.

Yaxin WangShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Jingyi LuShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Yun ShenShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Jiaying NiShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Lei ZhangShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Wei LuShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Wei ZhuShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Yuqian BaoShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
Jian ZhouShanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.ORCID https://orcid.org/0000-0002-1534-2279

Funding

National Key Research and Development Program of China 2018YFC2001004Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant 20161430Shanghai "Rising Stars of Medical Talent" Youth Development Program-Outstanding Youth Medical Talents N/A
6 · The paper itself

Abstract

AIMS/

introductionWe proposed a novel continuous glucose monitoring (CGM)-based metric, area under the curve in range (AucIR), for integrating both the amplitude and duration of dysglycemia, and further compared AucIR with the emerging key CGM-derived metric, time in range (TIR). MATERIALS AND

methodsA total of 2,030 adult patients with type 2 diabetes were enrolled during May 2020 to October 2021. AucIR and TIR were measured with 7-day CGM data. Logistic regression analysis and the C-statistic was carried out to assess the association of AucIR and TIR with diabetic retinopathy (DR).

resultsBoth AucIR (r = -0.89) and TIR (r = -0.95) were strongly correlated with mean glucose levels. Compared with TIR, AucIR showed a tighter relationship with parameters of glycemic variability, including the coefficient of variation (r = -0.56), standard deviation (r = -0.89) and mean amplitude of glycemic excursions (r = -0.70). For each absolute 10% decrease in AucIR, the risk of DR was increased by 7% (95% confidence interval 1.02-1.13) after adjustment for confounders. With respect to TIR, each absolute 10% decrease was associated with an 8% (95% confidence interval 1.03-1.14) increased risk of DR. The model discrimination for DR, as measured by C-statistic, did not differ significantly between the two metrics (P > 0.05).

conclusionsAucIR did not provide added benefit over TIR in the assessment of DR risk among patients with type 2 diabetes. The potential value of AucIR needs to be explored in future studies.

Indexed as

Diabetes Mellitus, Type 2Diabetic RetinopathyAdultArea Under CurveBlood GlucoseBlood Glucose Self-MonitoringGlucoseGlycated HemoglobinHumansBlood GlucoseGlucoseGlycated HemoglobinArea under the curve in rangeContinuous glucose monitoringTime in range

Identifiers

PMID35435323
PMCPMC9434583

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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.