| Literature DB >> 34461139 |
Timotius Ivan Hariyanto1, Denny Intan1, Joshua Edward Hananto1, Cynthia Putri1, Andree Kurniawan2.
Abstract
AIMS: GLP-1RA has many beneficial properties, including anti-inflammatory, anti-obesogenic, pulmonary protective effects as well as beneficial impact on gut microbiome. However, the evidence regarding the benefit of GLP-1RA in Covid-19 patients with diabetes is still unclear. This study sought to analyze the benefit of pre-admission use of GLP-1RA in altering the mortality outcomes of coronavirus disease 2019 (Covid-19) patients with diabetes mellitus.Entities:
Keywords: Anti-diabetic; Coronavirus disease 2019; Covid-19; Diabetes; GLP-1RA
Mesh:
Substances:
Year: 2021 PMID: 34461139 PMCID: PMC8397482 DOI: 10.1016/j.diabres.2021.109031
Source DB: PubMed Journal: Diabetes Res Clin Pract ISSN: 0168-8227 Impact factor: 5.602
Literature search strategy.
| Database | Keyword | Result |
|---|---|---|
| PubMed | (“glucagon-like peptide 1”[MeSH Terms] OR ”glucagon-like peptide 1”[All Fields] OR “glp 1”[All Fields]) OR GLP-1RA[All Fields] OR (”dulaglutide“[Supplementary Concept] OR ”dulaglutide“[All Fields]) OR (”semaglutide“[Supplementary Concept] OR ”semaglutide“[All Fields]) OR (”exenatide“[MeSH Terms] OR ”exenatide“[All Fields]) OR (”liraglutide“[MeSH Terms] OR ”liraglutide“[All Fields]) AND (”diabetes mellitus“[MeSH Terms] OR (”diabetes“[All Fields] AND ”mellitus“[All Fields]) OR ”diabetes mellitus“[All Fields] OR ”diabetes“[All Fields] OR ”diabetes insipidus“[MeSH Terms] OR (”diabetes“[All Fields] AND ”insipidus“[All Fields]) OR ”diabetes insipidus“[All Fields]) AND (”COVID-19”[All Fields] OR “COVID-19”[MeSH Terms] OR ”COVID-19 Vaccines“[All Fields] OR ”COVID-19 Vaccines“[MeSH Terms] OR ”COVID-19 serotherapy“[All Fields] OR ”COVID-19 Nucleic Acid Testing“[All Fields] OR ”covid-19 nucleic acid testing“[MeSH Terms] OR ”COVID-19 Serological Testing“[All Fields] OR ”covid-19 serological testing“[MeSH Terms] OR ”COVID-19 Testing“[All Fields] OR ”covid-19 testing“[MeSH Terms] OR ”SARS-CoV-2”[All Fields] OR “sars-cov-2”[MeSH Terms] OR ”Severe Acute Respiratory Syndrome Coronavirus 2”[All Fields] OR “NCOV”[All Fields] OR “2019 NCOV”[All Fields] OR ((“coronavirus”[MeSH Terms] OR “coronavirus”[All Fields] OR “COV”[All Fields]) AND 2019/11/01[PubDate]: 3000/12/31[PubDate])) | 25 |
| Europe PMC | “GLP-1” OR “GLP-1RA” OR “glucagon-like peptide-1” OR “dulaglutide” OR “semaglutide” OR “exenatide” OR “liraglutide” AND “diabetes” OR “diabetes mellitus” AND “SARS-CoV-2”, OR “coronavirus disease 2019” OR “COVID-19” | 156 |
| medRxiv | “GLP-1” OR “GLP-1RA” OR “glucagon-like peptide-1” OR “dulaglutide” OR “semaglutide” OR “exenatide” OR “liraglutide” AND “diabetes” OR “diabetes mellitus” AND “SARS-CoV-2”, OR “coronavirus disease 2019” OR “COVID-19” | 19 |
Fig. 1PRISMA diagram of the detailed process of selection of studies for inclusion in the systematic review and meta-analysis.
Characteristics of included studies.
| Study | Sample size | Design | Country | Overall age mean ± SD | Male n (%) | Hypertension n (%) | Cardiovascular disease n (%) | Metformin use n (%) | Insulin use | GLP-1RA use n (%) | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Death | Alive | ||||||||||
| Cariou B et al. | 1317 | Retrospective cohort | France | 69.8 ± 13 | 855 (64.9%) | 1003 (77.2%) | 621 (47.1%) | 746 (56.6%) | 504 (38.3%) | 9 (6.4%) | 114 (9.7%) |
| Israelsen SB et al. | 996 | Retrospective cohort | Denmark | 60 ± 14 | 521 (52.3%) | N/A | N/A | 645 (64.7%) | 224 (24.8%) | 14 (26.4%) | 356 (42%) |
| Izzi-Engbeaya C et al. | 337 | Retrospective cohort | England | 65.8 ± 17.5 | 202 (60%) | 238 (70.6%) | 91 (27%) | 169 (50.1%) | 108 (31%) | No data on death/alive Total = 5 (1.4%) | |
| Nyland JE et al. | 12,954 | Retrospective cohort | USA | 62.2 ± 15.2 | 6244 (48.2%) | 5881 (45.4%) | 3420 (26.4%) | 6192 (47.8%) | 7435 (57.4%) | 32 (2.9%) | 797 (6.7%) |
| Orioli L et al. | 73 | Retrospective cohort | Belgium | 69 ± 14 | 35 (48%) | 59 (80.8%) | 32 (43.8%) | 45 (61.6%) | 31 (45.6%) | 0 (0%) | 5 (8.8%) |
| Ramos-Rincon JM et al. | 790 | Retrospective cohort | Spain | 85.8 ± 4.5 | 418 (52.9%) | 666 (84.3%) | 625 (79.1%) | 420 (53.1%) | 211 (26.7%) | 11 (2.9%) | 13 (3.3%) |
| Silverii GA et al. | 159 | Retrospective cohort | Italy | 73.3 ± 12.6 | 86 (54.1%) | N/A | N/A | 76 (47.8%) | 43 (27%) | 1 (1.7%) | 6 (6%) |
| Sourij H et al. | 238 | Retrospective cohort | Austria | 71.1 ± 12.9 | 152 (63.9%) | 169 (71%) | 160 (67.2%) | 77 (32.3%) | 52 (21.9%) | 0 (0%) | 3 (1.7%) |
| Wargny M et al. | 2796 | Retrospective cohort | France | 69.7 ± 13.2 | 1782 (63.7%) | 2126 (76.8%) | 302 (11.4%) | 1553 (55.6%) | 1039 (37.2%) | 33 (5.7%) | 221 (10%) |
Newcastle-Ottawa quality assessment of observational studies.
| First author, year | Study design | Selection | Comparability | Outcome | Total score | Result |
|---|---|---|---|---|---|---|
| Cariou B et al. | Cohort | *** | ** | *** | 8 | Good |
| Israelsen SB et al. | Cohort | *** | ** | ** | 7 | Good |
| Izzi-Engbeaya C et al. | Cohort | *** | ** | *** | 8 | Good |
| Nyland JE et al. | Cohort | ** | ** | *** | 7 | Good |
| Orioli L et al. | Cohort | *** | ** | *** | 8 | Good |
| Ramos-Rincon JM et al. | Cohort | *** | ** | *** | 8 | Good |
| Silverii GA et al. | Cohort | ** | ** | *** | 7 | Good |
| Sourij H et al. | Cohort | *** | ** | *** | 8 | Good |
| Wargny M et al. | Cohort | *** | ** | *** | 8 | Good |
Fig. 2Forest plot that demonstrates the association of pre-admission GLP-1RA use with mortality outcome.
Fig. 3Bubble-plot for Meta-regression. Meta-regression analysis showed that the association between pre-admission GLP-1RA use and mortality outcome was not affected by age (A), gender (B), hypertension (C), cardiovascular disease (D), the use of metformin (E), and the use of insulin (F).
Fig. 4Funnel plot analysis for the association of pre-admission GLP-1RA use with mortality outcome.