Evidence map›Paper›PMID 39253580›Full record

SynthesisFrontiers in endocrinology2024

Association of COVID-19 infection and the risk of new incident diabetes: a systematic review and meta-analysis.

Jingye Zhou, Yuzhu Wang, Ruolan Xu

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

3 authors.

Jingye ZhouInternational Medical College, Chongqing Medical University, Chongqing, China.
Yuzhu WangInternational Medical College, Chongqing Medical University, Chongqing, China.
Ruolan XuInternational Medical College, Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the world population recovers from the COVID-19 infection, a series of acute sequelae emerge including new incident diabetes. However, the association between COVID-19 infection and new incident diabetes is not fully understood. We purpose to determine the risk of new incident diabetes after COVID-19 infection. Methods: PubMed, Embase, and Cochrane Library were used as databases to search for cohort studies published from database inception to February 4, 2024. Two reviewers independently conducted the study screening, data extraction, and risk of bias assessment. A random-effects model was adopted to pool the hazard ratio (HR) with corresponding 95% confidence intervals (CI). Subgroup analysis was conducted to explore the potential influencing factors. Results: A total of 20 cohort studies with over 60 million individuals were included. The pooling analysis illustrates the association between COVID-19 infection and an increased risk of new incident diabetes (HR = 1.46; 95% CI: 1.38-1.55). In subgroup analysis, the risk of type 1 diabetes was HR=1.44 (95% CI: 1.13-1.82), and type 2 diabetes was HR=1.47 (95% CI: 1.36-1.59). A slightly higher risk of diabetes was found in males (HR=1.37; 95% CI: 1.30-1.45) than in females (HR=1.29; 95% CI: 1.22-1.365). The risk of incident diabetes is associated with hospitalization: non-hospitalized patients have an HR of 1.16 (95% CI: 1.07-1.26), normal hospitalized patients have an HR of 2.15 (95% CI: 1.33-3.49), and patients receiving intensive care have the highest HR of 2.88 (95% CI: 1.73-4.79). Conclusions: COVID-19 infection is associated with an elevated risk of new incident diabetes. Patients ever infected with COVID-19 should be recognized as a high-risk population with diabetes. Systematic review registration: https://www.crd.york.ac.uk/prospero, identifier CRD42024522050.

Indexed as

COVID-19Diabetes Mellitus, Type 1Diabetes Mellitus, Type 2HumansIncidenceRisk FactorsCOVID-19diabetes mellituslong COVIDpublic healthSARS-CoV-2

Identifiers

PMID39253580
PMCPMC11381376

What OpenQuestion holds

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Registered trials

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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.