Evidence mapPaperPMID 36826982Full record

SynthesisDiabetes care2023

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis.

Rui Li, Mingwang Shen, Qianqian Yang, Christopher K Fairley, Zhonglin Chai, Robert McIntyre, Jason J Ong, Hanting Liu, Pengyi Lu, Wenyi Hu and 5 more

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Diabetes care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 3 pooled it
10.5field-weighted citation impact, top 1% 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

42 citing papers in PubMed, 3 syntheses or guidelines pooled it, 54 citations in OpenAlex.

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  7. Metformin and Severe Post-COVID-19 Outcomes Among Individuals with Diabetes Mellitus.medRxiv : the preprint server for health sciences · 2026
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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

15 authors at 5 institutions in 3 countries.

Rui LiChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Mingwang ShenChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Qianqian YangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Christopher K FairleyMelbourne Sexual Health Centre, Alfred Health, Melbourne, Australia.
Zhonglin ChaiDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0001-8182-8579
Robert McIntyreBariatric and Metabolic Surgery, King's College Hospital, London, U.K.
Jason J OngMelbourne Sexual Health Centre, Alfred Health, Melbourne, Australia.
Hanting LiuChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Pengyi LuChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Wenyi HuCentre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.
Zhuoru ZouChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Zengbin LiChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Shihao HeChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Guihua ZhuangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.ORCID 0000-0003-2343-084X
Xi'an Jiaotong University · CNMelbourne Sexual Health Centre · AUKing's College Hospital · GBMonash University · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 and diabetes both contribute to large global disease burdens. PURPOSE: To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality. DATA SOURCES: Systematic review identified 729 studies with 29,874,938 COVID-19 patients. STUDY SELECTION: Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity. DATA EXTRACTION: Study information, COVID-19 disease stages, and diabetes prevalence were extracted. DATA SYNTHESIS: The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death. LIMITATIONS: Most studies had a high risk of bias.

conclusionsThe prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.

Indexed as

COVID-19Diabetes MellitusCOVID-19 TestingHumansPrevalenceRisk Assessment

Identifiers

PMID36826982
PMCPMC10090902
OpenAlexW4321748994

What Socratic 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 Socratic graph.