Evidence map›Paper›PMID 38467385›Full record

ArticleDiabetes & metabolism journal2024

A Prospective 1-Year Follow-up of Glycemic Status and C-Peptide Levels of COVID-19 Survivors with Dysglycemia in Acute COVID-19 Infection.

David Tak Wai Lui, Chi Ho Lee, Ying Wong, Carol Ho Yi Fong, Kimberly Hang Tsoi, Yu Cho Woo, Kathryn Choon Beng Tan

Abstract read
In one paragraph

Article in Diabetes & metabolism journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Leveraging Machine Learning to Assess Post-COVID-19 Glycemic Control in Diabetic Patients.International journal of environmental research and public health · 2026
    Article
  4. 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

7 authors.

David Tak Wai LuiDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Chi Ho LeeDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Ying WongDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Carol Ho Yi FongDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Kimberly Hang TsoiDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Yu Cho WooDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
Kathryn Choon Beng TanDepartment of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.

Funding

Diabetes Hongkong RF202201Li Ka Shing Medical Fellowship for Internal Medicine
6 · The paper itself

Abstract

backgruoundWe evaluated changes in glycemic status, over 1 year, of coronavirus disease 2019 (COVID-19) survivors with dysglycemia in acute COVID-19.

methodsCOVID-19 survivors who had dysglycemia (defined by glycosylated hemoglobin [HbA1c] 5.7% to 6.4% or random glucose ≥10.0 mmol/L) in acute COVID-19 were recruited from a major COVID-19 treatment center from September to October 2020. Matched non-COVID controls were recruited from community. The 75-g oral glucose tolerance test (OGTT) were performed at baseline (6 weeks after acute COVID-19) and 1 year after acute COVID-19, with HbA1c, insulin and C-peptide measurements. Progression in glycemic status was defined by progression from normoglycemia to prediabetes/diabetes, or prediabetes to diabetes.

resultsFifty-two COVID-19 survivors were recruited. Compared with non-COVID controls, they had higher C-peptide (P< 0.001) and trend towards higher homeostasis model assessment of insulin resistance (P=0.065). Forty-three COVID-19 survivors attended 1-year reassessment. HbA1c increased from 5.5%±0.3% to 5.7%±0.2% (P<0.001), with increases in glucose on OGTT at fasting (P=0.089), 30-minute (P=0.126), 1-hour (P=0.014), and 2-hour (P=0.165). At baseline, 19 subjects had normoglycemia, 23 had prediabetes, and one had diabetes. Over 1 year, 10 subjects (23.8%; of 42 non-diabetes subjects at baseline) had progression in glycemic status. C-peptide levels remained unchanged (P=0.835). Matsuda index decreased (P=0.007) and there was a trend of body mass index increase from 24.4±2.7 kg/m2 to 25.6±5.2 (P=0.083). Subjects with progression in glycemic status had more severe COVID-19 illness than non-progressors (P=0.030). Reassessment was not performed in the control group.

conclusionSubjects who had dysglycemia in acute COVID-19 were characterized by insulin resistance. Over 1 year, a quarter had progression in glycemic status, especially those with more severe COVID-19. Importantly, there was no significant deterioration in insulin secretory capacity.

Indexed as

Blood GlucoseCOVID-19C-PeptideGlucose Tolerance TestGlycated HemoglobinPrediabetic StateAdultAgedCase-Control StudiesDiabetes MellitusDisease ProgressionFemaleFollow-Up StudiesHumansHyperglycemiaInsulinBlood GlucoseC-PeptideGlycated Hemoglobinhemoglobin A1c protein, humanInsulinCOVID-19C-peptideDiabetes mellitusInsulin resistanceInsulin secretionSARS-CoV-2

Identifiers

PMID38467385
PMCPMC11307110

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.