Evidence map›Paper›PMID 32006292›Full record

ArticleEndocrine2020

Impact of acute-phase insulin secretion on glycemic variability in insulin-treated patients with type 2 diabetes.

Yiming Si, Yun Shen, Jingyi Lu, Xiaojing Ma, Lei Zhang, Yifei Mo, Wei Lu, Wei Zhu, Yuqian Bao, Gang Hu and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Endocrine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Exploring the potential role of C-peptide in type 2 diabetes management.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  5. Article
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 2 institutions in 2 countries.

Yiming Si *Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Yun Shen *Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Jingyi Lu *Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Xiaojing MaDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Lei ZhangDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Yifei MoDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Wei LuDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Wei ZhuDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Yuqian BaoDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China.
Gang HuPennington Biomedical Research Center, Baton Rouge, LA, USA. gang.hu@pbrc.edu.ORCID http://orcid.org/0000-0002-6172-8017
Jian ZhouDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, 200233, Shanghai, China. zhoujian@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-1534-2279
Shanghai Jiao Tong University · CNPennington Biomedical Research Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThe association between β-cell function and glycemic variability remains to be clarified in insulin-treated patients with type 2 diabetes. Therefore, the study sought to examine the association of various indices of β-cell function with glycemic variability in Chinese insulin-treated patients with type 2 diabetes.

methodsGlycemic variability was assessed by the coefficient of variation (CV) of glucose levels with the use of continuous glucose monitoring (CGM). Basal β-cell function was evaluated by fasting C-peptide (FCP) and the homeostasis model assessment 2 for β-cell function (HOMA2-%β). Postload β-cell function was measured by 2-hour C-peptide (2hCP) and the acute C-peptide response (ACPR) to arginine.

resultsWhen a cutoff value of CV ≥ 36% was used to define unstable glucose, the multivariable-adjusted odds ratios for labile glycemic control were 0.34 (95% CI 0.18-0.64) for each 1 ng/mL increase in ACPR, 0.47 (95% CI 0.27-0.81) for each 1 ng/mL increase in FCP, 0.77 (95% CI 0.61-0.97) for each 1 ng/mL increase in 2hCP, and 1.00 (95% CI 0.98-1.01) for each 1% increase in HOMA2-%β. When we further adjusted for 2hCP and HOMA2-%β in the ACPR and FCP analyses, and adjusted for ACPR or FCP in the 2hCP analyses, only ACPR but not FCP or 2hPC remained to be a significant and inverse predictor for labile glycemic control.

conclusionsACPR evaluated by the arginine stimulation test may be superior to other commonly used β-cell function parameters to reflect glycemic fluctuation in insulin-treated patients with type 2 diabetes.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2Blood Glucose Self-MonitoringGlycated HemoglobinHumansInsulinInsulin SecretionBlood GlucoseGlycated HemoglobinInsulinArginine stimulation testGlycemic variabilityInsulin treatmentThe acute C-peptide responseType 2 diabetesβ-cell function

Identifiers

PMID32006292
OpenAlexW3003677150

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.