Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

Luelia Teles Jaques-Albuquerque; Elzi Dos Anjos-Martins; Luiza Torres-Nunes; Ana Gabriellie Valério-Penha; Ana Carolina Coelho-Oliveira; Viviani Lopes da Silva Sarandy; Aline Reis-Silva; Adérito Seixas; Mario Bernardo-Filho; Redha Taiar; Danúbia Cunha de Sá-Caputo

doi:10.3390/diagnostics13081499

Effectiveness of Using the FreeStyle Libre^® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

Diagnostics (Basel). 2023 Apr 21;13(8):1499. doi: 10.3390/diagnostics13081499.

Authors

Luelia Teles Jaques-Albuquerque¹, Elzi Dos Anjos-Martins^{1

2}, Luiza Torres-Nunes^{1

3}, Ana Gabriellie Valério-Penha¹, Ana Carolina Coelho-Oliveira^{1

2}, Viviani Lopes da Silva Sarandy¹, Aline Reis-Silva^{1

4}, Adérito Seixas⁵, Mario Bernardo-Filho¹, Redha Taiar⁶, Danúbia Cunha de Sá-Caputo^{1

2}

Affiliations

¹ Laboratório de Vibrações Mecânicas e Práticas Integrativas, Departamento de Biofísica e Biometria, Instituto de Biologia Roberto Alcântara Gomes, Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro 20950-003, Brazil.
² Mestrado Profissional em Saúde, Medicina Laboratorial e Tecnologia Forense, Universidade do Estado do Rio de Janeiro, Rio de Janeiro 20950-003, Brazil.
³ Programa de Pós-Graduação em Fisiopatologia Clínica e Experimental, Universidade do Estado do Rio de Janeiro, Rio de Janeiro 20950-003, Brazil.
⁴ Programa de Pós-Graduação em Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro 20950-003, Brazil.
⁵ Escola Superior de Saúde Fernando Pessoa, 4200-256 Porto, Portugal.
⁶ MATériaux et Ingénierie Mécanique (MATIM), Université de Reims Champagne Ardenne, 51100 Reims, France.

Abstract

Background: Artificial Intelligence (AI) is an area of computer science/engineering that is aiming to spread technological systems. The COVID-19 pandemic caused economic and public health turbulence around the world. Among the many possibilities for using AI in the medical field is FreeStyle Libre^® (FSL), which uses a disposable sensor inserted into the user's arm, and a touchscreen device/reader is used to scan and retrieve other continuous monitoring of glucose (CMG) readings. The aim of this systematic review is to summarize the effectiveness of FSL blood glucose monitoring during the COVID-19 pandemic.

Methods: This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and was registered in the international prospective register of systematic reviews (PROSPERO: CRD42022340562). The inclusion criteria considered studies involving the use of the FSL device during the COVID-19 pandemic and published in English. No publication date restrictions were set. The exclusion criteria were abstracts, systematic reviews, studies with patients with other diseases, monitoring with other equipment, patients with COVID-19, and bariatrics patients. Seven databases were searched (PubMed, Scopus, Embase, Web of Science, Scielo, PEDro and Cochrane Library). The ACROBAT-NRSI tool (A Cochrane Risk of Bias Assessment Tool for Non-Randomized Studies) was used to evaluate the risk of bias in the selected articles.

Results: A total of 113 articles were found. Sixty-four were excluded because they were duplicates, 39 were excluded after reading the titles and abstracts, and twenty articles were considered for full reading. Of the 10 articles analyzed, four articles were excluded because they did not meet the inclusion criteria. Thus, six articles were included in the current systematic review. It was observed that among the selected articles, only two were classified as having serious risk of bias. It was shown that FSL had a positive impact on glycemic control and on reducing the number of individuals with hypoglycemia.

Conclusion: The findings suggest that the implementation of FSL during COVID-19 confinement in this population can be confidently stated to have been effective in diabetes mellitus patients.

Keywords: COVID-19; artificial intelligence; pandemic; social isolation; type 2 diabetes mellitus.

Publication types

Review

Grants and funding

This research was funded by Conselho Nacional de Pesquisa e Desenvolvimento (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001 and Universidade do Estado do Rio de Janeiro (UERJ).