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Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis
INTRODUCTION: and aims: To prevent the spread of coronavirus disease (COVID19) total lockdown is in place in India from March 24, 2020 for 21 days. In this study, we aim to assess the impact of the duration of the lockdown on glycaemic control and diabetes-related complications. MATERIALS AND METHOD...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd on behalf of Diabetes India.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146694/ https://www.ncbi.nlm.nih.gov/pubmed/32298984 http://dx.doi.org/10.1016/j.dsx.2020.03.014 |
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author | Ghosal, Samit Sinha, Binayak Majumder, Milan Misra, Anoop |
author_facet | Ghosal, Samit Sinha, Binayak Majumder, Milan Misra, Anoop |
author_sort | Ghosal, Samit |
collection | PubMed |
description | INTRODUCTION: and aims: To prevent the spread of coronavirus disease (COVID19) total lockdown is in place in India from March 24, 2020 for 21 days. In this study, we aim to assess the impact of the duration of the lockdown on glycaemic control and diabetes-related complications. MATERIALS AND METHODS: A systematic search was conducted using Cochrane library. A simulation model was created using glycemic data from previous disasters (taken as similar in impact to current lockdown) taking baseline HBA1c and diabetes-related complications data from India-specific database. A multivariate regression analysis was conducted to analyse the relationship between the duration of lockdown and glycaemic targets & diabetes-related complications. RESULTS: The predictive model was extremely robust (R2 = 0.99) and predicted outcomes for period of lockdown up to 90 days. The predicted increment in HBA1c from baseline at the end of 30 days and 45 days lockdown was projected as 2.26% & 3.68% respectively. Similarly, the annual predicted percentage increase in complication rates at the end of 30-day lockdown was 2.8% for non-proliferative diabetic retinopathy, 2.9% for proliferative diabetic retinopathy, 1.5% for retinal photocoagulation, 9.3% for microalbuminuria, 14.2% for proteinuria, 2.9% for peripheral neuropathy, 10.5% for lower extremity amputation, 0.9% for myocardial infarction, 0.5% for stroke and 0.5% for infections. CONCLUSION: The duration of lockdown is directly proportional to the worsening of glycaemic control and diabetes-related complications. Such increase in diabetes-related complications will put additional load on overburdened healthcare system, and also increase COVID19 infections in patients with such uncontrolled glycemia. |
format | Online Article Text |
id | pubmed-7146694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Published by Elsevier Ltd on behalf of Diabetes India. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71466942020-04-10 Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis Ghosal, Samit Sinha, Binayak Majumder, Milan Misra, Anoop Diabetes Metab Syndr Article INTRODUCTION: and aims: To prevent the spread of coronavirus disease (COVID19) total lockdown is in place in India from March 24, 2020 for 21 days. In this study, we aim to assess the impact of the duration of the lockdown on glycaemic control and diabetes-related complications. MATERIALS AND METHODS: A systematic search was conducted using Cochrane library. A simulation model was created using glycemic data from previous disasters (taken as similar in impact to current lockdown) taking baseline HBA1c and diabetes-related complications data from India-specific database. A multivariate regression analysis was conducted to analyse the relationship between the duration of lockdown and glycaemic targets & diabetes-related complications. RESULTS: The predictive model was extremely robust (R2 = 0.99) and predicted outcomes for period of lockdown up to 90 days. The predicted increment in HBA1c from baseline at the end of 30 days and 45 days lockdown was projected as 2.26% & 3.68% respectively. Similarly, the annual predicted percentage increase in complication rates at the end of 30-day lockdown was 2.8% for non-proliferative diabetic retinopathy, 2.9% for proliferative diabetic retinopathy, 1.5% for retinal photocoagulation, 9.3% for microalbuminuria, 14.2% for proteinuria, 2.9% for peripheral neuropathy, 10.5% for lower extremity amputation, 0.9% for myocardial infarction, 0.5% for stroke and 0.5% for infections. CONCLUSION: The duration of lockdown is directly proportional to the worsening of glycaemic control and diabetes-related complications. Such increase in diabetes-related complications will put additional load on overburdened healthcare system, and also increase COVID19 infections in patients with such uncontrolled glycemia. Published by Elsevier Ltd on behalf of Diabetes India. 2020 2020-04-10 /pmc/articles/PMC7146694/ /pubmed/32298984 http://dx.doi.org/10.1016/j.dsx.2020.03.014 Text en © 2020 Published by Elsevier Ltd on behalf of Diabetes India. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ghosal, Samit Sinha, Binayak Majumder, Milan Misra, Anoop Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title | Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title_full | Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title_fullStr | Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title_full_unstemmed | Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title_short | Estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: A simulation model using multivariate regression analysis |
title_sort | estimation of effects of nationwide lockdown for containing coronavirus infection on worsening of glycosylated haemoglobin and increase in diabetes-related complications: a simulation model using multivariate regression analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146694/ https://www.ncbi.nlm.nih.gov/pubmed/32298984 http://dx.doi.org/10.1016/j.dsx.2020.03.014 |
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