Evidence map›Paper›PMID 32779091›Full record

ReviewEndocrine2020

Hypothesized mechanisms explaining poor prognosis in type 2 diabetes patients with COVID-19: a review.

Giuseppe Lisco, Anna De Tullio, Vito Angelo Giagulli, Edoardo Guastamacchia, Giovanni De Pergola, Vincenzo Triggiani

Open access · bronzeAbstract readReview
In one paragraph

Review in Endocrine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 17% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  8. Glucose variability is a marker for COVID-19 severity and mortality.Archives of endocrinology and metabolism · 2022
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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

6 authors at 2 institutions in 1 country.

Giuseppe LiscoUnit of Endocrinology, Metabolic Disease & Clinical Nutrition, Hospital "A. Perrino", Strada 7 per Mesagne, 72100, Brindisi, Puglia, Italy. g.lisco84@gmail.com.ORCID http://orcid.org/0000-0001-6521-8578
Anna De TullioInterdisciplinary Department of Medicine-Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, University of Bari "Aldo Moro", School of Medicine, Policlinico, Piazza Giulio Cesare 11, 70124, Bari, Puglia, Italy.ORCID http://orcid.org/0000-0001-6341-6140
Vito Angelo GiagulliInterdisciplinary Department of Medicine-Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, University of Bari "Aldo Moro", School of Medicine, Policlinico, Piazza Giulio Cesare 11, 70124, Bari, Puglia, Italy.ORCID http://orcid.org/0000-0002-7073-1795
Edoardo GuastamacchiaInterdisciplinary Department of Medicine-Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, University of Bari "Aldo Moro", School of Medicine, Policlinico, Piazza Giulio Cesare 11, 70124, Bari, Puglia, Italy.ORCID http://orcid.org/0000-0001-8666-8658
Giovanni De PergolaDepartment of Biomedical Sciences and Human Oncology, Section of Internal Medicine and Clinical Oncology, University of Bari Aldo Moro, Piazza Giulio Cesare 11, 70124, Bari, Puglia, Italy.ORCID http://orcid.org/0000-0003-0020-3273
Vincenzo TriggianiInterdisciplinary Department of Medicine-Section of Internal Medicine, Geriatrics, Endocrinology and Rare Diseases, University of Bari "Aldo Moro", School of Medicine, Policlinico, Piazza Giulio Cesare 11, 70124, Bari, Puglia, Italy.ORCID http://orcid.org/0000-0001-6308-0528
University of Bari Aldo Moro · ITOspedale A. Perrino · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEpidemiological data suggest that comorbid patients, mostly those with type 2 diabetes (T2D), are predisposed to poor prognosis in Coronavirus disease 2019 (COVID-19), leading to serious healthcare concerns. The aim of the present manuscript is to review the main relevant mechanisms possibly contributing to worsen the clinical course of COVID-19 in T2D.

resultsPoor glucose control, high glycaemic variability and diabetes-related comorbidities at baseline, particularly cardiovascular diseases and obesity, contribute in worsening the prognosis in the above-mentioned cluster of patients. Moreover, both a lower efficient innate immune system response and cytokine dysregulation predispose patients with T2D to impaired viral clearance and more serious pulmonary and systemic inflammation once the SARS-CoV-2 infection occurred. Inconclusive data are currently available for specifically indicate or contraindicate concurrent medications for managing T2D and its comorbidities in infected patients.

conclusionsT2D individuals should be considered as more vulnerable to COVID-19 than general population, and thus require adequate advices about hygienic tips to protect themselves during the pandemic. A careful management of glucose levels and diabetes-related comorbidities remains essential for avoiding further complications, and patient monitoring during the pandemic should be performed also at distance by means of telemedicine. Further studies are needed to clarify whether medications normally used for managing T2D and its associated comorbidities could have a protective or detrimental effect on COVID-19 clinical course.

Indexed as

BetacoronavirusCardiovascular DiseasesComorbidityCoronavirus InfectionsCOVID-19Diabetes Mellitus, Type 2Disease ProgressionHumansMortalityObesityPandemicsPneumonia, ViralPrognosisRisk FactorsSARS-CoV-2Signal TransductionCardiovascular diseaseCOVID-19Diabetes mellitusGLP-1RAsImmune responseObesity

Identifiers

PMID32779091
PMCPMC7417102
OpenAlexW3048198647

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.