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Song ZH, Huang QM, Xu SS, Zhou JB, Zhang C. The Effect of Antihyperglycemic Medications on COVID-19: A Meta-analysis and Systematic Review from Observational Studies. Ther Innov Regul Sci 2024; 58:773-787. [PMID: 38683419 DOI: 10.1007/s43441-024-00633-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/09/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND Diabetes, a chronic disease worldwide, may be associated with a poorer prognosis in patients with coronavirus disease 2019 (COVID-19). While some antihyperglycemic medications may be beneficial, others may increase the risk of adverse clinical outcomes of COVID-19. We aimed to analyze the effect of antihyperglycemic medications on COVID-19. METHODS We searched the Web of Science, Cochrane Library, EMBASE, PubMed, and Scopus databases from December 2019 to June 2022 to identify literature related to patients with COVID-19 and type 2 diabetes mellitus (T2DM) treated with antihyperglycemic medications. RESULTS 56 studies were included in the analysis. Metformin (OR 0.66; 95% CI 0.58-0.74; p < 0.05), Glucagon-like peptide-1 receptor agonist (GLP-1ra) (OR 0.73; 95% CI 0.59-0.91; p < 0.05), and sodium-dependent glucose transporters 2 inhibitor (SGLT 2i) (OR 0.77; 95% CI 0.69-0.87; p < 0.05) were associated with lower mortality risk, while insulin was associated with increased mortality risk (OR 1.40; 95% CI 1.26-1.55; p < 0.05). Meanwhile, metformin (OR 0.65; 95% CI 0.50-0.85; p < 0.05) and GLP-1ra (OR 0.84; 95% CI 0.76-0.94; p < 0.05) were significantly associated with decreased severe manifestation risk. What's more, metformin (OR 0.77; 95% CI 0.62-0.96; p < 0.05), GLP-1ra (OR 0.86; 95% CI 0.81-0.92; p < 0.05), and SGLT 2i (OR 0.87; 95% CI 0.79-0.97; p < 0.05) were also associated with a decreased risk of hospitalization, but insulin were associated with an increased risk of hospitalization (OR 1.31; 95% CI 1.12-1.52; p < 0.05). Nevertheless, the results of the subgroup analyses showed that the effects of different glucose-lowering agents on COVID-19 may be related to in-hospital use or out-hospital use, elderly or non-elderly patients use, and different geography. CONCLUSION Metformin, GLP-1ra, and SGLT 2i have shown a positive effect on clinical outcomes in COVID-19, particularly in non-elderly individuals. However, insulin use may pose a higher risk, especially in elderly patients, so need with caution. Meanwhile, DPP-4i, TZD, α-GLUi, and sulfonylureas appeared to have a neutral effect. These results need to be validated in future clinical studies.
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Affiliation(s)
- Zhi-Hui Song
- Department of Pharmacy, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Qiao-Ming Huang
- Department of Pharmacy, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Shan-Shan Xu
- Department of Pharmacy, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jian-Bo Zhou
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
| | - Chao Zhang
- Department of Pharmacy, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
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Pilipovic Broceta N, Todorovic N, Skrbic R, Acimovic J, Strbac S, Soldatovic I. Clinical and epidemiological risk factors associated with hospitalization and mortality rate of COVID-19 patients in Banja Luka County: A retrospective observational cohort study on 40,000 patients. J Family Med Prim Care 2024; 13:2130-2137. [PMID: 38948596 PMCID: PMC11213400 DOI: 10.4103/jfmpc.jfmpc_1641_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 07/02/2024] Open
Abstract
Context Since beginning of the coronavirus disease (COVID-19) it became clear that severe forms of this infection have primarily affected patients with chronic conditions. Aims The aim of the study was to explore clinical and epidemiological characteristics associated with COVID 19 outcomes. Settings and Design The retrospective observational study included 40,692 citizens of Banja Luka County, Bosnia and Herzegovina, who were confirmed as reverse transcriptase polymerase chain reaction (RT-PCR) positive on COVID-19 at a primary healthcare centre from March 2020 to September 2022. Methods and Materials Epidemiological data were obtained from Web-Medic medical records of patients. The COVID-19 data were obtained from COVID-19 data sheets comprised of patients' RT-PCR testing forms, surveillance forms for severe acute respiratory syndrome coronavirus-2 status, and a map of their positive and isolated contacts. Statistical Analysis Used Differences regarding the distributions of patients between groups were analysed using the Pearson chi-square test and Mantel-Haenszel chi-square test for trends, while differences in mean values were compared using an independent sample t-test. Results The average age of hospitalised patients was significantly higher compared to the age of non-hospitalised patients (P < 0.001). The average age of patients with lethal outcomes was nearly twice as high in comparison to patients with non-lethal outcomes (P < 0.001). Male patients had a higher hospitalization and mortality rate (P < 0.001). The highest hospitalization rate was in patients with chronic renal failure (CRF), diabetes and cardiovascular diseases (CVDs), while the death rate was the highest among patients with CRF and hearth comorbidities. Patients with fatigue and appetite loss had a higher percentage of lethal outcomes. Vaccinated patients had a significantly lower rate of lethal outcome. Conclusions Clinical symptoms, signs and outcomes, are posing as predictive parameters for further management of COVID-19. Vaccination has an important role in the clinical outcomes of COVID-19.
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Affiliation(s)
- Natasa Pilipovic Broceta
- Department of Family Medicine, Faculty of Medicine, University of Banja Luka, Banja Luka 78000, The Republic of Srpska, Bosnia and Herzegovina
- Family Medicine Teaching Centre, Primary Health Care Centre Banja Luka, Banja Luka, The Republic of Srpska, Bosnia and Herzegovina
| | - Nevena Todorovic
- Department of Family Medicine, Faculty of Medicine, University of Banja Luka, Banja Luka 78000, The Republic of Srpska, Bosnia and Herzegovina
- Family Medicine Teaching Centre, Primary Health Care Centre Banja Luka, Banja Luka, The Republic of Srpska, Bosnia and Herzegovina
| | - Ranko Skrbic
- Department of Pharmacology, Toxicology and Clinical Pharmacology, Faculty of Medicine, University of Banja Luka, Banja Luka, The Republic of Srpska, Bosnia and Herzegovina
| | - Jela Acimovic
- Department of Epidemiology, Public Health Institute of the Republic of Srpska, Banja Luka, The Republic of Srpska, Bosnia and Herzegovina
| | - Savka Strbac
- Department of Epidemiology, Public Health Institute of the Republic of Srpska, Banja Luka, The Republic of Srpska, Bosnia and Herzegovina
| | - Ivan Soldatovic
- Institute of Medical Statistics and Informatics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
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Moon MK, Ham H, Song SM, Lee C, Goo T, Oh B, Lee S, Kim SW, Park T. The clinical course of hospitalized COVID-19 patients and aggravation risk prediction models: a retrospective, multi-center Korean cohort study. Front Med (Lausanne) 2024; 10:1239789. [PMID: 38239614 PMCID: PMC10794356 DOI: 10.3389/fmed.2023.1239789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 12/01/2023] [Indexed: 01/22/2024] Open
Abstract
Background Understanding the clinical course and pivotal time points of COVID-19 aggravation is critical for enhancing patient monitoring. This retrospective, multi-center cohort study aims to identify these significant time points and associate them with potential risk factors, leveraging data from a sizable cohort with mild-to-moderate symptoms upon admission. Methods This study included data from 1,696 COVID-19 patients with mild-to-moderate clinical severity upon admission across multiple hospitals in Daegu-Kyungpook Province (Daegu dataset) between February 18 and early March 2020 and 321 COVID-19 patients at Seoul Boramae Hospital (Boramae dataset) collected from February to July 2020. The approach involved: (1) identifying the optimal time point for aggravation using survival analyses with maximally selected rank statistics; (2) investigating the relationship between comorbidities and time to aggravation; and (3) developing prediction models through machine learning techniques. The models were validated internally among patients from the Daegu dataset and externally among patients from the Boramae dataset. Results The Daegu dataset showed a mean age of 51.0 ± 19.6 years, with 8 days for aggravation and day 5 being identified as the pivotal point for survival. Contrary to previous findings, specific comorbidities had no notable impact on aggravation patterns. Prediction models utilizing factors including age and chest X-ray infiltration demonstrated promising performance, with the top model achieving an AUC of 0.827 in external validation for 5 days aggravation prediction. Conclusion Our study highlights the crucial significance of the initial 5 days period post-admission in managing COVID-19 patients. The identification of this pivotal time frame, combined with our robust predictive models, provides valuable insights for early intervention strategies. This research underscores the potential of proactive monitoring and timely interventions in enhancing patient outcomes, particularly for those at risk of rapid aggravation. Our findings offer a meaningful contribution to understanding the COVID-19 clinical course and supporting healthcare providers in optimizing patient care and resource allocation.
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Affiliation(s)
- Min Kyong Moon
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Hyeonjung Ham
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Soo Min Song
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Chanhee Lee
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Taewan Goo
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Bumjo Oh
- Department of Family Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Seungyeoun Lee
- Department of Mathematics & Statistics, Sejong University, Seoul, Republic of Korea
| | - Shin-Woo Kim
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul, Republic of Korea
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Greco S, Monda VM, Valpiani G, Napoli N, Crespini C, Pieraccini F, Marra A, Passaro A. The Impact of GLP-1 RAs and DPP-4is on Hospitalisation and Mortality in the COVID-19 Era: A Two-Year Observational Study. Biomedicines 2023; 11:2292. [PMID: 37626788 PMCID: PMC10452157 DOI: 10.3390/biomedicines11082292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
Novel antidiabetic drugs have the ability to produce anti-inflammatory effects regardless of their glucose-lowering action. For this reason, these molecules (including GLP-1 RAs and DPP-4is) were hypothesized to be effective against COVID-19, which is characterized by cytokines hyperactivity and multiorgan inflammation. The aim of our work is to explore the potential protective role of GLP-1 RAs and DPP-4is in COVID-19 (with the disease intended to be a model of an acute stressor) and non-COVID-19 patients over a two-year observation period. Retrospective and one-versus-one analyses were conducted to assess the impact of antidiabetic drugs on the need for hospitalization (in both COVID-19- and non-COVID-19-related cases), in-hospital mortality, and two-year mortality. Logistic regression analyses were conducted to identify the variables associated with these outcomes. Additionally, log-rank tests were used to plot survival curves for each group of subjects, based on their antidiabetic treatment. The performed analyses revealed that despite similar hospitalization rates, subjects undergoing home therapy with GLP-1 RAs exhibited significantly lower mortality rates, even over a two-year period. These individuals demonstrated improved survival estimates both within hospital and non-hospital settings, even during a longer observation period.
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Affiliation(s)
- Salvatore Greco
- Department of Translational Medicine, University of Ferrara, Via Luigi Borsari, 46, I-44121 Ferrara, FE, Italy;
- Department of Internal Medicine, Ospedale del Delta, Via Valle Oppio, 2, I-44023 Lagosanto, FE, Italy
| | - Vincenzo M. Monda
- Primary Care Department, Diabetes Unit of “SS. Annunziata” Hospital, Via Giovanni Vicini 2, I-44042 Cento, FE, Italy;
| | - Giorgia Valpiani
- Research and Innovation Section, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy;
| | - Nicola Napoli
- Programming and Management Control Unit, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy;
| | - Carlo Crespini
- Pharmaceutical Department, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy; (C.C.); (A.M.)
| | - Fabio Pieraccini
- Pharmaceutical Care Department, Azienda Unità Sanitaria Locale della Romagna, Via Carlo Forlanini 34, I-47121 Forlì, FC, Italy;
| | - Anna Marra
- Pharmaceutical Department, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy; (C.C.); (A.M.)
| | - Angelina Passaro
- Department of Translational Medicine, University of Ferrara, Via Luigi Borsari, 46, I-44121 Ferrara, FE, Italy;
- Research and Innovation Section, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy;
- Department of Internal Medicine, University Hospital of Ferrara Arcispedale Sant’Anna, Via Aldo Moro 8, I-44124 Cona, FE, Italy
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Schlesinger S, Lang A, Christodoulou N, Linnerz P, Pafili K, Kuss O, Herder C, Neuenschwander M, Barbaresko J, Roden M. Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis. Diabetologia 2023; 66:1395-1412. [PMID: 37204441 PMCID: PMC10198038 DOI: 10.1007/s00125-023-05928-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 03/16/2023] [Indexed: 05/20/2023]
Abstract
AIMS/HYPOTHESIS To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death. METHODS This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach. RESULTS A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19 vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out. CONCLUSIONS/INTERPRETATION Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease. REGISTRATION PROSPERO registration no. CRD42020193692. PREVIOUS VERSION This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science 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).
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Affiliation(s)
- Sabrina Schlesinger
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany.
| | - Alexander Lang
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Nikoletta Christodoulou
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Philipp Linnerz
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kalliopi Pafili
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Oliver Kuss
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
- Centre for Health and Society, Faculty of Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Manuela Neuenschwander
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
| | - Janett Barbaresko
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Smadi M, Kaburis M, Schnapper Y, Reina G, Molero P, Molendijk ML. SARS-CoV-2 susceptibility and COVID-19 illness course and outcome in people with pre-existing neurodegenerative disorders: systematic review with frequentist and Bayesian meta-analyses. Br J Psychiatry 2023:1-14. [PMID: 37183681 DOI: 10.1192/bjp.2023.43] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND People with neurodegenerative disease and mild cognitive impairment (MCI) may have an elevated risk of acquiring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and may be disproportionally affected by coronavirus disease 2019 (COVID-19) once infected. AIMS To review all eligible studies and quantify the strength of associations between various pre-existing neurodegenerative disorders and both SARS-CoV-2 susceptibility and COVID-19 illness course and outcome. METHOD Pre-registered systematic review with frequentist and Bayesian meta-analyses. Systematic searches were executed in PubMed, Web of Science and preprint servers. The final search date was 9 January 2023. Odds ratios (ORs) were used as measures of effect. RESULTS In total, 136 primary studies (total sample size n = 97 643 494), reporting on 268 effect-size estimates, met the inclusion criteria. The odds for a positive SARS-CoV-2 test result were increased for people with pre-existing dementia (OR = 1.83, 95% CI 1.16-2.87), Alzheimer's disease (OR = 2.86, 95% CI 1.44-5.66) and Parkinson's disease (OR = 1.65, 95% CI 1.34-2.04). People with pre-existing dementia were more likely to experience a relatively severe COVID-19 course, once infected (OR = 1.43, 95% CI 1.00-2.03). People with pre-existing dementia or Alzheimer's disease were at increased risk for COVID-19-related hospital admission (pooled OR range: 1.60-3.72). Intensive care unit admission rates were relatively low for people with dementia (OR = 0.54, 95% CI 0.40-0.74). All neurodegenerative disorders, including MCI, were at higher risk for COVID-19-related mortality (pooled OR range: 1.56-2.27). CONCLUSIONS Our findings confirm that, in general, people with neurodegenerative disease and MCI are at a disproportionally high risk of contracting COVID-19 and have a poor outcome once infected.
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Affiliation(s)
- Muhannad Smadi
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Melina Kaburis
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Youval Schnapper
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands
| | - Gabriel Reina
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; and Clínica Universidad de Navarra, Department of Microbiology, Pamplona, Spain
| | - Patricio Molero
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; and Clínica Universidad de Navarra, Department of Psychiatry and Medical Psychology, Pamplona, Spain
| | - Marc L Molendijk
- Institute of Psychology, Department of Clinical Psychology, Leiden University, Leiden, The Netherlands; and Leiden Institute for Brain and Cognition, Leiden University Medical Centre, Leiden, The Netherlands
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Kania M, Koń B, Kamiński K, Hohendorff J, Witek P, Klupa T, Malecki MT. Diabetes as a risk factor of death in hospitalized COVID-19 patients - an analysis of a National Hospitalization Database from Poland, 2020. Front Endocrinol (Lausanne) 2023; 14:1161637. [PMID: 37214252 PMCID: PMC10194032 DOI: 10.3389/fendo.2023.1161637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 04/06/2023] [Indexed: 05/24/2023] Open
Abstract
Introduction Diabetes is one of the comorbidities associated with poor prognosis in hospitalized COVID-19 patients. In this nationwide retrospective study, we evaluated the risk of in-hospital death attributed to diabetes. Methods We analyzed data from discharge reports of patients hospitalized with COVID-19 in 2020 as submitted to the Polish National Health Fund. Several multivariate logistic regression models were used. In each model, in-hospital death was estimated with explanatory variables. Models were built either on the whole cohorts or cohorts matched with propensity score matching (PSM). The models examined either the main effects of diabetes itself or the interaction of diabetes with other variables. Results We included 174,621 patients with COVID-19 who were hospitalized in the year 2020. Among them, there were 40,168 diabetic patients (DPs), and the proportion of DPs in this group was higher than in the general population (23.0% vs. 9.5%, p<0.001). In this group of COVID-19 hospitalizations, 17,438 in-hospital deaths were recorded, and the mortality was higher among DPs than non-diabetics (16.3% vs. 8.1%, p<0.001). Multivariate logistic regressions showed that diabetes was a risk factor of death, regardless of sex and age. In the main effect analysis, odds of in-hospital death were higher by 28.3% for DPs than for non-diabetic patients. Similarly, PSM analysis including 101,578 patients, of whom 19,050 had diabetes, showed that the risk of death was higher in DPs regardless of sex with odds higher by 34.9%. The impact of diabetes differed among age groups and was the highest for patients aged 60-69. Conclusions This nationwide study confirmed that diabetes was an independent risk factor of in-hospital death in the course of COVID-19 infection. However, the relative risk differed across the age groups.
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Affiliation(s)
- Michal Kania
- Department of Metabolic Diseases and Diabetology, Jagiellonian University Medical College, Krakow, Poland
- Department of Metabolic Diseases and Diabetology, University Hospital, Krakow, Poland
| | - Beata Koń
- Department of Analysis and Innovation, National Health Fund, Warsaw, Poland
| | - Konrad Kamiński
- Department of Analysis and Innovation, National Health Fund, Warsaw, Poland
| | - Jerzy Hohendorff
- Department of Metabolic Diseases and Diabetology, Jagiellonian University Medical College, Krakow, Poland
- Department of Metabolic Diseases and Diabetology, University Hospital, Krakow, Poland
| | - Przemysław Witek
- Department of Metabolic Diseases and Diabetology, Jagiellonian University Medical College, Krakow, Poland
- Department of Metabolic Diseases and Diabetology, University Hospital, Krakow, Poland
| | - Tomasz Klupa
- Department of Metabolic Diseases and Diabetology, Jagiellonian University Medical College, Krakow, Poland
- Department of Metabolic Diseases and Diabetology, University Hospital, Krakow, Poland
| | - Maciej T. Malecki
- Department of Metabolic Diseases and Diabetology, Jagiellonian University Medical College, Krakow, Poland
- Department of Metabolic Diseases and Diabetology, University Hospital, Krakow, Poland
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Lopez-de-Andres A, Jimenez-Garcia R, Zamorano-Leon JJ, Omaña-Palanco R, Carabantes-Alarcon D, Hernández-Barrera V, De Miguel-Diez J, Cuadrado-Corrales N. Prevalence of Dementia among Patients Hospitalized with Type 2 Diabetes Mellitus in Spain, 2011-2020: Sex-Related Disparities and Impact of the COVID-19 Pandemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4923. [PMID: 36981830 PMCID: PMC10049429 DOI: 10.3390/ijerph20064923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/08/2023] [Accepted: 03/09/2023] [Indexed: 06/18/2023]
Abstract
(1) Background: To assess changes in the prevalence of dementia among patients hospitalized with type 2 diabetes (T2DM), to analyze the effects of dementia on in-hospital mortality (IHM) in this population, to evaluate sex differences, and to determine the impact of the COVID-19 pandemic on these parameters. (2) Methods: We used a nationwide discharge database to select all patients with T2DM aged 60 years or over admitted to Spanish hospitals from 2011 to 2020. We identified those with all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). The effect of sex, age, comorbidity, and COVID-19 on the prevalence of dementia subtypes and on IHM was assessed using multivariable logistic regression. (3) Results: We identified 5,250,810 hospitalizations with T2DM. All-cause dementia was detected in 8.31%, AD in 3.00%, and VaD in 1.55%. The prevalence of all subtypes of dementia increased significantly over time. After multivariable adjustment, higher values were observed in women for all-cause dementia (OR 1.34; 95% CI 1.33-1.35), AD (OR 1.6; 95% CI 1.58-1.62), and VaD (OR 1.12; 95% CI 1.11-1.14). However, female sex was a protective factor for IHM in patients with all-cause dementia (OR 0.90; 95% CI 0.89-0.91), AD (OR 0.89; 95% CI 0.86-0.91), and VaD (OR 0.95; 95% CI 0.91-0.99). IHM among patients with dementia remained stable over time, until 2020, when it increased significantly. Higher age, greater comorbidity, and COVID-19 were associated with IHM in all dementia subtypes. (4) Conclusions: The prevalence of dementia (all-cause, AD, and VaD) in men and women with T2DM increased over time; however, the IHM remained stable until 2020, when it increased significantly, probably because of the COVID-19 pandemic. The prevalence of dementia is higher in women than in men, although female sex is a protective factor for IHM.
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Affiliation(s)
- Ana Lopez-de-Andres
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Rodrigo Jimenez-Garcia
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Jose J. Zamorano-Leon
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Ricardo Omaña-Palanco
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - David Carabantes-Alarcon
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Valentin Hernández-Barrera
- Preventive Medicine and Public Health Teaching and Research Unit, Health Sciences Faculty, Universidad Rey Juan Carlos, 28922 Alcorcón, Spain
| | - Javier De Miguel-Diez
- Respiratory Care Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Universidad Complutense de Madrid, 28007 Madrid, Spain
| | - Natividad Cuadrado-Corrales
- Department of Public Health and Maternal & Child Health, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
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9
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Pedrosa AR, Martins DC, Rizzo M, Silva-Nunes J. Metformin in SARS-CoV-2 infection: A hidden path - from altered inflammation to reduced mortality. A review from the literature. J Diabetes Complications 2023; 37:108391. [PMID: 36621213 PMCID: PMC9807268 DOI: 10.1016/j.jdiacomp.2022.108391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 12/21/2022] [Accepted: 12/27/2022] [Indexed: 01/04/2023]
Abstract
SARS-CoV-2 infection has been a major threat to human health and a huge challenge to Medicine. In only two years, COVID-19 affected >350 million people, causing >5.6 million deaths. Chronic inflammatory states, such as diabetes or obesity, are known risk factors for COVID-19 poorest outcomes, with higher risk for disease severity and greater mortality. Metformin remains on the first line of the management of hyperglycemia in type 2 diabetes. Through its anti-inflammatory and immunomodulatory mechanisms, metformin appears as an opportunity to control the dysregulated cytokine storm secondary to SARS-CoV-2 infection. Recent studies point towards a potential protective role of metformin in the course of COVID-19, showing that current or previous treatment with metformin associates with better outcomes.
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Affiliation(s)
- Ana Realista Pedrosa
- Department of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal; Department of Internal Medicine, Hospital do Espírito Santo de Évora, Évora, Portugal
| | - Diana Cruz Martins
- Department of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal; Faculty of Medicine of the University of Coimbra, Coimbra, Portugal
| | - Manfredi Rizzo
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
| | - José Silva-Nunes
- Department of Endocrinology, Diabetes and Metabolism, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal; NOVA Medical School/Faculdade de Ciências Medicas, New University of Lisbon, Lisbon, Portugal; Health and Technology Research Center, Escola Superior de Tecnologia da Saúde de Lisboa, Lisbon, Portugal.
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10
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Tallon EM, Ebekozien O, Sanchez J, Staggs VS, Ferro D, McDonough R, Demeterco-Berggren C, Polsky S, Gomez P, Patel N, Prahalad P, Odugbesan O, Mathias P, Lee JM, Smith C, Shyu CR, Clements MA. Impact of diabetes status and related factors on COVID-19-associated hospitalization: A nationwide retrospective cohort study of 116,370 adults with SARS-CoV-2 infection. Diabetes Res Clin Pract 2022; 194:110156. [PMID: 36400172 PMCID: PMC9663407 DOI: 10.1016/j.diabres.2022.110156] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/01/2022] [Accepted: 11/09/2022] [Indexed: 11/17/2022]
Abstract
AIMS We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D. METHODS We analyzed electronic health record data from the de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection. RESULTS In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m2), increased BMI (>25.0-29.9 kg/m2), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c). CONCLUSIONS The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes.
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Affiliation(s)
- Erin M Tallon
- Institute for Data Science and Informatics, University of Missouri, 22 Heinkel Building, Columbia, MO 65211, USA.
| | - Osagie Ebekozien
- T1D Exchange, 11 Avenue de Lafayette, Boston, MA 02111, USA; School of Population Health, University of Mississippi, 2500 North State Street, Jackson, MS 39216, USA
| | - Janine Sanchez
- University of Miami, 1601 NW 12th Avenue, Miami, FL 33136, USA
| | - Vincent S Staggs
- Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA
| | - Diana Ferro
- Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA
| | - Ryan McDonough
- Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA
| | | | - Sarit Polsky
- Barbara Davis Center for Diabetes, Adult Clinic, University of Colorado Anschutz Medical Campus, 1775 Aurora Court, MS A140, Aurora, CO 80045, USA
| | - Patricia Gomez
- University of Miami, 1601 NW 12th Avenue, Miami, FL 33136, USA
| | - Neha Patel
- Penn State Health Children's Hospital, 12 Briarcrest Square, Hershey, PA 17033, USA
| | - Priya Prahalad
- Stanford University, 730 Welch Road, Palo Alto, CA 94304, USA
| | - Ori Odugbesan
- T1D Exchange, 11 Avenue de Lafayette, Boston, MA 02111, USA
| | - Priyanka Mathias
- Albert Einstein College of Medicine, Montefiore Medical Center, 1800 Morris Park Avenue, Bronx, NY 10461, USA
| | - Joyce M Lee
- University of Michigan, Pediatric Endocrinology, Susan B. Meister Child Health Evaluation and Research Center, 2800 Plymouth Rd NCRC Building 16, Ann Arbor, MI 48109-2800, USA
| | - Chelsey Smith
- Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA
| | - Chi-Ren Shyu
- Institute for Data Science and Informatics, University of Missouri, 22 Heinkel Building, Columbia, MO 65211, USA; Department of Electrical Engineering and Computer Science, University of Missouri, 201 Naka Hall, Columbia, MO 65211, USA; School of Medicine, University of Missouri, 1 Hospital Drive, Columbia, MO 65212, USA
| | - Mark A Clements
- Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA
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11
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Yeh HC, Kraschnewski JL, Kong L, Lehman EB, Heilbrunn ES, Williams P, Poger JM, Francis E, Bryce CL. Hospitalization and mortality in patients with COVID-19 with or at risk of type 2 diabetes: data from five health systems in Pennsylvania and Maryland. BMJ Open Diabetes Res Care 2022; 10:10/3/e002774. [PMID: 35680172 PMCID: PMC9184995 DOI: 10.1136/bmjdrc-2022-002774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/16/2022] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE To identify the demographic and clinical characteristics associated with adverse COVID-19 outcomes across a 12-month period in 2020 and 2021. RESEARCH DESIGN AND METHODS We conducted a retrospective cohort study using electronic health records from five academic health systems in Pennsylvania and Maryland, including patients with COVID-19 with type 2 diabetes or at risk of type 2 diabetes. Patients were classified based on 30-day outcomes: (1) no hospitalization; (2) hospitalization only; or (3) a composite measure including admission to the intensive care unit (ICU), intubation, or death. Analyses were conducted in patients with type 2 diabetes and patients at risk of type 2 diabetes separately. RESULTS We included 15 725 patients with COVID-19 diagnoses between March 2020 and February 2021. Older age and higher Charlson Comorbidity Index scores were associated with higher odds of adverse outcomes, while COVID-19 diagnoses later in the study period were associated with lower odds of severe outcomes. In patients with type 2 diabetes, individuals on insulin treatment had higher odds for ICU/intubation/death (OR=1.59, 95% CI 1.27 to 1.99), whereas those on metformin had lower odds (OR=0.56, 95% CI 0.45 to 0.71). Compared with non-Hispanic White patients, Hispanic patients had higher odds of hospitalization in patients with type 2 diabetes (OR=1.73, 95% CI 1.36 to 2.19) or at risk of type 2 diabetes (OR=1.77, 95% CI 1.43 to 2.18.) CONCLUSIONS: Adults who were older, in racial minority groups, had multiple chronic conditions or were on insulin treatment had higher risks for severe COVID-19 outcomes. This study reinforced the urgency of preventing COVID-19 and its complications in vulnerable populations. TRIAL REGISTRATION NUMBER NCT02788903.
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Affiliation(s)
- Hsin-Chieh Yeh
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jennifer L Kraschnewski
- Department of Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Lan Kong
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Erik B Lehman
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Emily S Heilbrunn
- Department of Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Pamela Williams
- Cancer and Chronic Disease Bureau, Maryland Department of Health, Baltimore, Maryland, USA
| | - Jennifer M Poger
- Department of Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Erica Francis
- Department of Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Cindy L Bryce
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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12
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Nguyen NN, Ho DS, Nguyen HS, Ho DKN, Li HY, Lin CY, Chiu HY, Chen YC. Preadmission use of antidiabetic medications and mortality among patients with COVID-19 having type 2 diabetes: A meta-analysis. Metabolism 2022; 131:155196. [PMID: 35367460 PMCID: PMC8970613 DOI: 10.1016/j.metabol.2022.155196] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/10/2022] [Accepted: 03/28/2022] [Indexed: 12/16/2022]
Abstract
BACKGROUND Diabetes is an independent predictor of poor outcomes in patients with COVID-19. We compared the effects of the preadmission use of antidiabetic medications on the in-hospital mortality of patients with COVID-19 having type 2 diabetes. METHODS A systematic search of PubMed, EMBASE, Scopus and Web of Science databases was performed to include studies (except case reports and review articles) published until November 30, 2021. We excluded papers regarding in-hospital use of antidiabetic medications. We used a random-effects meta-analysis to calculate the pooled OR (95% CI) and performed a sensitivity analysis to confirm the robustness of the meta-analyses. MAIN FINDINGS We included 61 studies (3,061,584 individuals), which were rated as having low risk of bias. The OR (95% CI) indicated some medications protective against COVID-related death, including metformin [0.54 (0.47-0.62), I2 86%], glucagon-like peptide-1 receptor agonist (GLP-1RA) [0.51 (0.37-0.69), I2 85%], and sodium-glucose transporter-2 inhibitor (SGLT-2i) [0.60 (0.40-0.88), I2 91%]. Dipeptidyl peptidase-4 inhibitor (DPP-4i) [1.23 (1.07-1.42), I2 82%] and insulin [1.70 (1.33-2.19), I2 97%] users were more likely to die during hospitalization. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitor were mortality neutral [0.92 (95% CI 0.83-1.01, I2 44%), 0.90 (95% CI 0.71-1.14, I2 46%), and 0.61 (95% CI 0.26-1.45, I2 77%), respectively]. The sensitivity analysis indicated that our findings were robust. CONCLUSIONS Metformin, GLP-1RA, and SGLT-2i were associated with lower mortality rate in patients with COVID-19 having type 2 diabetes. DPP-4i and insulin were linked to increased mortality. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitors were mortality neutral. These findings can have a large impact on the clinicians' decisions amid the COVID-19 pandemic.
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Affiliation(s)
- Nam Nhat Nguyen
- College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Dung Si Ho
- Department of Geriatric Medicine, Faculty of Medicine, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Viet Nam; Department of Pulmonology, Thong Nhat Hospital, Ho Chi Minh City, Viet Nam
| | - Hung Song Nguyen
- College of Medicine, Taipei Medical University, Taipei, Taiwan; Wellcome Trust Major Overseas Program, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Dang Khanh Ngan Ho
- School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan
| | - Hung-Yuan Li
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Chia-Yuan Lin
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan
| | - Hsiao-Yean Chiu
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan; Research Center of Sleep Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yang-Ching Chen
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan; Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
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13
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Impact of Type 2 Diabetes Mellitus on the Incidence and Outcomes of COVID-19 Needing Hospital Admission According to Sex: Retrospective Cohort Study Using Hospital Discharge Data in Spain, Year 2020. J Clin Med 2022; 11:jcm11092654. [PMID: 35566794 PMCID: PMC9104185 DOI: 10.3390/jcm11092654] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/01/2022] [Accepted: 05/08/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: To analyze incidence and in-hospital mortality (IHM) of COVID-19 needing hospital admission in Spain (2020) in patients with T2DM. (2) Methods: We conducted a retrospective cohort study. Using the Spanish Register of Specialized Care-Basic Minimum Database we estimated age-adjusted incidence rates (IR). (3) Results: We included 203,488 patients (56.77% men), of whom 45,620 (22.41%) had T2DM. Age-adjusted IRs/1000 for men with and without T2DM was 12.90 and 5.87, respectively (IRR 2.20; 95% CI 2.18−2.22; p < 0.001), and for women with and without T2DM was 9.23 and 4.27, respectively (IRR 2.16; 95% CI 2.13−2.19; p < 0.001). Crude IHM was 23.86% in people with T2DM, and 15.94% in non-T2DM people (p < 0.001). After matching, intensive-care admission (7.37% vs. 6.15%; p < 0.001) and IHM (23.37% vs. 20.41%; p < 0.001) remained higher in women with T2DM. After matching, IHM among T2DM men was 1.5% higher than among non-T2DM men (24.27% vs. 22.72%; p < 0.001). Men with T2DM had a 34% higher IHM than women with T2DM. Prevalent T2DM increased IHM among women (1.09; 95% 1.03−1.16) and men (1.05; 95% 1.01−1.10). (4) Conclusions: Incidence rates of COVID-19 needing hospital admission were higher in men vs. women, and for people with T2DM vs. non-T2DM. Men had higher IHM beside T2DM status. Prevalent T2DM was associated with higher IHM for both sexes.
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14
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Mannucci F, Vitturi G, Benacchio L, Sbrogiò LG, Bano F, Lapolla A, Piarulli F, Giron MC, Avogaro A, Fadini GP. Infection Rates and Impact of Glucose Lowering Medications on the Clinical Course of COVID-19 in People with Type 2 Diabetes: A Retrospective Observational Study. Diabetes Metab Syndr Obes 2022; 15:3093-3101. [PMID: 36237966 PMCID: PMC9553236 DOI: 10.2147/dmso.s385646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/05/2022] [Indexed: 11/06/2022] Open
Abstract
PURPOSE Diabetes is a risk factor for COVID-19 severity, but the role played by glucose lowering medications (GLM) is still unclear. The aim of this study was to assess infection rates and outcomes of COVID-19 (hospitalization and mortality) in adults with diabetes assisted by the Local Health Unit of Padua (North-East Italy) according to the ongoing GLM. PATIENTS AND METHODS People with diabetes were identified using administrative claims, while those with SARS-CoV-2 infection were detected by cross referencing with the local COVID-19 surveillance registry. A multivariate logistic regression model was used to verify the association between GLM classes and the outcome. RESULTS SARS-CoV-2 infection rates were marginally but significantly higher in individuals with diabetes as compared to those without diabetes (RR 1.04, p = 0.043), though such relative 4% increase may be irrelevant from a clinical and epidemiological perspective. 1923 individuals with GLM-treated diabetes were diagnosed with COVID-19; 456 patients were hospitalized and 167 died. Those treated with insulin had a significantly higher risk of hospitalizations for COVID-19 (OR 1.48 p < 0.01) as were those treated with sulphonylureas/glinides (OR 1.34, p = 0.02). Insulin use was also significantly associated with higher mortality (OR 1.90, p < 0.01). Use of metformin was significantly associated with lower death rates (OR 0.62, p = 0.02). The association of other GLM classes with the outcome was not significant. CONCLUSION Diabetes does not appear to modify the risk of SARS-CoV-2 infection in a clinically meaningful way, but strongly increases the rates of hospitalization and death. Insulin use was associated with worse outcomes, whereas metformin use was associated with lower mortality.
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Affiliation(s)
| | - Giacomo Vitturi
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padua, Italy
| | | | | | | | | | | | - Maria Cecilia Giron
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padua, Italy
| | - Angelo Avogaro
- Department of Medicine, University of Padova, Padua, Italy
| | - Gian Paolo Fadini
- Department of Medicine, University of Padova, Padua, Italy
- Correspondence: Gian Paolo Fadini, Department of Medicine, University of Padova, Via Giustiniani 2, Padova, 35128, Italy, Tel +39 049 8214318, Fax +39 049 8212184, Email
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15
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Fu Y, Hu L, Ren HW, Zuo Y, Chen S, Zhang QS, Shao C, Ma Y, Wu L, Hao JJ, Wang CZ, Wang Z, Yanagihara R, Deng Y. Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes. Int J Endocrinol 2022; 2022:9322332. [PMID: 35047039 PMCID: PMC8763039 DOI: 10.1155/2022/9322332] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 12/01/2021] [Accepted: 12/07/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) as a worldwide chronic disease combined with the COVID-19 pandemic prompts the need for improving the management of hospitalized COVID-19 patients with preexisting T2D to reduce complications and the risk of death. This study aimed to identify clinical factors associated with COVID-19 outcomes specifically targeted at T2D patients and build an individualized risk prediction nomogram for risk stratification and early clinical intervention to reduce mortality. METHODS In this retrospective study, the clinical characteristics of 382 confirmed COVID-19 patients, consisting of 108 with and 274 without preexisting T2D, from January 8 to March 7, 2020, in Tianyou Hospital in Wuhan, China, were collected and analyzed. Univariate and multivariate Cox regression models were performed to identify specific clinical factors associated with mortality of COVID-19 patients with T2D. An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration. RESULTS Nearly 15% (16/108) of hospitalized COVID-19 patients with T2D died. Twelve risk factors predictive of mortality were identified. Older age (HR = 1.076, 95% CI = 1.014-1.143, p=0.016), elevated glucose level (HR = 1.153, 95% CI = 1.038-1.28, p=0.0079), increased serum amyloid A (SAA) (HR = 1.007, 95% CI = 1.001-1.014, p=0.022), diabetes treatment with only oral diabetes medication (HR = 0.152, 95%CI = 0.032-0.73, p=0.0036), and oral medication plus insulin (HR = 0.095, 95%CI = 0.019-0.462, p=0.019) were independent prognostic factors. A nomogram based on these prognostic factors was built for early prediction of 7-day, 14-day, and 21-day survival of diabetes patients. High concordance index (C-index) was achieved, and the calibration curves showed the model had good prediction ability within three weeks of COVID-19 onset. CONCLUSIONS By incorporating specific prognostic factors, this study provided a user-friendly graphical risk prediction tool for clinicians to quickly identify high-risk T2D patients hospitalized for COVID-19.
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Affiliation(s)
- Yuanyuan Fu
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Ling Hu
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Hong-Wei Ren
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Yi Zuo
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Shaoqiu Chen
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Qiu-Shi Zhang
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Chen Shao
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Yao Ma
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Lin Wu
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Jun-Jie Hao
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Chuan-Zhen Wang
- Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Zhanwei Wang
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Richard Yanagihara
- Department of Pediatrics, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Youping Deng
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
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16
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Ding Y, Zhou Y, Ling P, Feng X, Luo S, Zheng X, Little PJ, Xu S, Weng J. Metformin in cardiovascular diabetology: a focused review of its impact on endothelial function. Am J Cancer Res 2021; 11:9376-9396. [PMID: 34646376 PMCID: PMC8490502 DOI: 10.7150/thno.64706] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 08/30/2021] [Indexed: 02/07/2023] Open
Abstract
As a first-line treatment for diabetes, the insulin-sensitizing biguanide, metformin, regulates glucose levels and positively affects cardiovascular function in patients with diabetes and cardiovascular complications. Endothelial dysfunction (ED) represents the primary pathological change of multiple vascular diseases, because it causes decreased arterial plasticity, increased vascular resistance, reduced tissue perfusion and atherosclerosis. Caused by “biochemical injury”, ED is also an independent predictor of cardiovascular events. Accumulating evidence shows that metformin improves ED through liver kinase B1 (LKB1)/5'-adenosine monophosphat-activated protein kinase (AMPK) and AMPK-independent targets, including nuclear factor-kappa B (NF-κB), phosphatidylinositol 3 kinase-protein kinase B (PI3K-Akt), endothelial nitric oxide synthase (eNOS), sirtuin 1 (SIRT1), forkhead box O1 (FOXO1), krüppel-like factor 4 (KLF4) and krüppel-like factor 2 (KLF2). Evaluating the effects of metformin on endothelial cell functions would facilitate our understanding of the therapeutic potential of metformin in cardiovascular diabetology (including diabetes and its cardiovascular complications). This article reviews the physiological and pathological functions of endothelial cells and the intact endothelium, reviews the latest research of metformin in the treatment of diabetes and related cardiovascular complications, and focuses on the mechanism of action of metformin in regulating endothelial cell functions.
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