Evidence map›Paper›PMID 32298981›Full record

ReviewDiabetes & metabolic syndrome

Diabetes in COVID-19: Prevalence, pathophysiology, prognosis and practical considerations.

Awadhesh Kumar Singh, Ritesh Gupta, Amerta Ghosh, Anoop Misra

Abstract readReview
In one paragraph

Review in Diabetes & metabolic syndrome. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 394 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
394citing papers in PubMed, 7 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

394 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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334 more citing papers are in PubMed but not listed here.

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

4 authors.

Awadhesh Kumar SinghG.D Hospital and Diabetes Institute, Kolkata, India. Electronic address: draksingh_2001@yahoo.com.
Ritesh GuptaFortis CDOC Hospital, Chirag Enclave, New Delhi, India.
Amerta GhoshFortis CDOC Hospital, Chirag Enclave, New Delhi, India.
Anoop MisraFortis CDOC Hospital, Chirag Enclave, New Delhi, India; National Diabetes, Obesity and Cholesterol Foundation, New Delhi, India; Diabetes Foundation, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsHigh prevalence of diabetes makes it an important comorbidity in patients with COVID-19. We sought to review and analyze the data regarding the association between diabetes and COVID-19, pathophysiology of the disease in diabetes and management of patients with diabetes who develop COVID-19 infection.

methodsPubMed database and Google Scholar were searched using the key terms 'COVID-19', 'SARS-CoV-2', 'diabetes', 'antidiabetic therapy' up to April 2, 2020. Full texts of the retrieved articles were accessed.

resultsThere is evidence of increased incidence and severity of COVID-19 in patients with diabetes. COVID-19 could have effect on the pathophysiology of diabetes. Blood glucose control is important not only for patients who are infected with COVID-19, but also for those without the disease. Innovations like telemedicine are useful to treat patients with diabetes in today's times.

Indexed as

BetacoronavirusComorbidityAngiotensin-Converting Enzyme 2Angiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsAnimalsBlood GlucoseCoronavirus InfectionsCOVID-19Diabetes MellitusDipeptidyl Peptidase 4HumansHypoglycemic AgentsInterleukin-6MicePandemicsACE2 protein, humanAce2 protein, mouseAngiotensin-Converting Enzyme 2Angiotensin-Converting Enzyme InhibitorsAngiotensin Receptor AntagonistsBlood GlucoseDipeptidyl Peptidase 4DPP4 protein, humanHypoglycemic AgentsInterleukin-6Peptidyl-Dipeptidase A

Identifiers

PMID32298981
PMCPMC7195120

What OpenQuestion 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 OpenQuestion graph.