Evidence mapPaperPMID 41580734Full record

ReviewJournal of translational medicine2026

The silent epidemic within the pandemic: pathophysiology and prediction of post-COVID-19 diabetes.

Hongjuan Fang, Qiang Wang

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Hongjuan FangDepartment of Endocrinology, Aviation General Hospital, No.3 Anwai Beiyuan Road, Beijing, 100012, China. tthfhj@163.com.
Qiang WangChinese PLA Center for Disease Control and Prevention, 20 Dongda Street, Beijing, 100071, China. wang76qiang@163.com.ORCID http://orcid.org/0000-0003-4392-0889

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) pandemic has presented extraordinary challenges to global public health, with impacts reaching beyond acute respiratory manifestations to include long-term metabolic disturbances. Emerging evidence indicates a significant link between SARS-CoV-2 infection and the onset of diabetes mellitus, establishing this condition as a major element of the post-acute sequelae of COVID-19, often referred to as Long COVID. MAIN BODY: This review synthesizes epidemiological findings that demonstrate a elevated incidence of new-onset diabetes following COVID-19, particularly among certain high-risk demographic groups. We examine the molecular mechanisms underpinning this association, such as viral entry into pancreatic β-cells via ACE2 receptors, systemic inflammation leading to insulin resistance, and the potential diabetogenic effects of glucocorticoids used in COVID-19 treatment. Furthermore, this review outlines biomarker profiles that distinguish COVID-19-associated diabetes from traditional type 2 diabetes, underscoring important pathophysiological differences. Additionally, we evaluate advances and ongoing challenges in developing predictive risk models that combine clinical and molecular data to identify individuals at elevated risk for post-COVID diabetes.

conclusionsBy integrating multidisciplinary evidence, this comprehensive narrative review aims to guide future research and shape clinical approaches for early detection, prevention, and management of diabetes following COVID-19, thereby confronting a latent health crisis emerging within the broader pandemic context.

Indexed as

COVID-19Diabetes MellitusDiabetes Mellitus, Type 2BiomarkersHumansPandemicsPost-Acute COVID-19 SyndromeRisk FactorsSARS-CoV-2BiomarkersACE2 receptorCOVID-19Inflammatory responseLong COVIDNew-onset diabetesPancreatic β-cellsRisk prediction model

Identifiers

PMID41580734
PMCPMC12911156

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.