Evidence map›Paper›PMID 33907860›Full record

SynthesisDiabetologia2021

Risk phenotypes of diabetes and association with COVID-19 severity and death: a living systematic review and meta-analysis.

Sabrina Schlesinger, Manuela Neuenschwander, Alexander Lang, Kalliopi Pafili, Oliver Kuss, Christian Herder, Michael Roden

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Diabetologia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 8 pooled it
6.6field-weighted citation impact, top 3% 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

48 citing papers in PubMed, 8 syntheses or guidelines pooled it, 100 citations in OpenAlex.

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  19. Acupoint stimulation for long COVID: A promising intervention:.World journal of acupuncture-moxibustion · 2023
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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

7 authors at 2 institutions in 1 country.

Sabrina SchlesingerInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. sabrina.schlesinger@ddz.de.ORCID https://orcid.org/0000-0003-4244-0832
Manuela NeuenschwanderInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0001-5761-2225
Alexander LangInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Kalliopi PafiliGerman Center for Diabetes Research (DZD), Partner Düsseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0003-4293-3514
Oliver KussInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0003-3301-5869
Christian HerderGerman Center for Diabetes Research (DZD), Partner Düsseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0002-2050-093X
Michael RodenGerman Center for Diabetes Research (DZD), Partner Düsseldorf, Düsseldorf, Germany.ORCID https://orcid.org/0000-0001-8200-6382
Deutsches Diabetes-Zentrum e.V. · DEDüsseldorf University Hospital · DE

Funding

The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Science and Culture of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD). The funders had no role in study design or data collection, analysis and interpretation. NA
6 · The paper itself

Abstract

aims/hypothesisDiabetes has been identified as a risk factor for poor prognosis of coronavirus disease-2019 (COVID-19). The aim of this study is to identify high-risk phenotypes of diabetes associated with COVID-19 severity and death.

methodsThis is the first edition of a living systematic review and meta-analysis on observational studies investigating phenotypes in individuals with diabetes and COVID-19-related death and severity. Four different databases were searched up to 10 October 2020. We used a random effects meta-analysis to calculate summary relative risks (SRR) with 95% CI. The certainty of evidence was evaluated by the GRADE tool.

resultsA total of 22 articles, including 17,687 individuals, met our inclusion criteria. For COVID-19-related death among individuals with diabetes and COVID-19, there was high to moderate certainty of evidence for associations (SRR [95% CI]) between male sex (1.28 [1.02, 1.61], n = 10 studies), older age (>65 years: 3.49 [1.82, 6.69], n = 6 studies), pre-existing comorbidities (cardiovascular disease: 1.56 [1.09, 2.24], n = 8 studies; chronic kidney disease: 1.93 [1.28, 2.90], n = 6 studies; chronic obstructive pulmonary disease: 1.40 [1.21, 1.62], n = 5 studies), diabetes treatment (insulin use: 1.75 [1.01, 3.03], n = 5 studies; metformin use: 0.50 [0.28, 0.90], n = 4 studies) and blood glucose at admission (≥11 mmol/l: 8.60 [2.25, 32.83], n = 2 studies). Similar, but generally weaker and less precise associations were observed between risk phenotypes of diabetes and severity of COVID-19. CONCLUSIONS/

interpretationIndividuals with a more severe course of diabetes have a poorer prognosis of COVID-19 compared with individuals with a milder course of disease. To further strengthen the evidence, more studies on this topic that account for potential confounders are warranted. REGISTRATION: PROSPERO registration ID CRD42020193692.

Indexed as

Diabetes MellitusAgedAged, 80 and overComorbidityCOVID-19Diabetes ComplicationsFemaleHumansMaleMiddle AgedMortalityPhenotypePrognosisRespiration, ArtificialRisk FactorsSARS-CoV-2COVID-19DiabetesMeta-analysisSARS-CoV-2Systematic review

Identifiers

PMID33907860
PMCPMC8079163
OpenAlexW3106671214

What Socratic holds

Textmetadata
LicenceCC BY
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.