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CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases

INTRODUCTION: Early screening of metabolic diseases is crucial since continued undiagnostic places an ever-increasing burden on healthcare systems. Recent studies suggest a link between overactivated carotid bodies (CB) and the genesis of type 2 diabetes mellitus. The non-invasive assessment of CB a...

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Autores principales: Lages, Marlene, Carvalho, Lucinda, Feijó, Salvato, Vieira, Alexandra, Fonseca-Pinto, Rui, Guarino, Maria Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395299/
https://www.ncbi.nlm.nih.gov/pubmed/34446475
http://dx.doi.org/10.1136/bmjopen-2020-042825
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author Lages, Marlene
Carvalho, Lucinda
Feijó, Salvato
Vieira, Alexandra
Fonseca-Pinto, Rui
Guarino, Maria Pedro
author_facet Lages, Marlene
Carvalho, Lucinda
Feijó, Salvato
Vieira, Alexandra
Fonseca-Pinto, Rui
Guarino, Maria Pedro
author_sort Lages, Marlene
collection PubMed
description INTRODUCTION: Early screening of metabolic diseases is crucial since continued undiagnostic places an ever-increasing burden on healthcare systems. Recent studies suggest a link between overactivated carotid bodies (CB) and the genesis of type 2 diabetes mellitus. The non-invasive assessment of CB activity by measuring ventilatory, cardiac and metabolic responses to challenge tests may have predictive value for metabolic diseases; however, there are no commercially available devices that assess CB activity. The findings of the CBmeter study will clarify the role of the CBs in the genesis of—metabolic diseases and guide the development of new therapeutic approaches for early intervention in metabolic disturbances. Results may also contribute to patient classification and stratification for future CB modulatory interventions. METHODS: This is a non-randomised, multicentric, controlled clinical study. Forty participants (20 control and 20 diabetics) will be recruited from secondary and primary healthcare settings. The primary objective is to establish a new model of early diagnosis of metabolic diseases based on the respiratory and metabolic responses to transient 100% oxygen administration and ingestion of a standardised mixed meal. ANALYSIS: Raw data acquired with the CBmeter will be endorsed against gold standard techniques for heart rate, respiratory rate, oxygen saturation and interstitial glucose quantification and analysed a multivariate analysis software developed specifically for the CBmeter study (CBview). Data will be analysed using clustering analysis and artificial intelligence methods based on unsupervised learning algorithms, to establish the predictive value of diabetes diagnosis. ETHICS: The study was approved by the Ethics Committee of the Leiria Hospital Centre. Patients will be asked for written informed consent and data will be coded to ensure the anonymity of data. DISSEMINATION: Results will be disseminated through publication in peer-reviewed journals and relevant medical and health conferences.
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spelling pubmed-83952992021-09-14 CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases Lages, Marlene Carvalho, Lucinda Feijó, Salvato Vieira, Alexandra Fonseca-Pinto, Rui Guarino, Maria Pedro BMJ Open Diabetes and Endocrinology INTRODUCTION: Early screening of metabolic diseases is crucial since continued undiagnostic places an ever-increasing burden on healthcare systems. Recent studies suggest a link between overactivated carotid bodies (CB) and the genesis of type 2 diabetes mellitus. The non-invasive assessment of CB activity by measuring ventilatory, cardiac and metabolic responses to challenge tests may have predictive value for metabolic diseases; however, there are no commercially available devices that assess CB activity. The findings of the CBmeter study will clarify the role of the CBs in the genesis of—metabolic diseases and guide the development of new therapeutic approaches for early intervention in metabolic disturbances. Results may also contribute to patient classification and stratification for future CB modulatory interventions. METHODS: This is a non-randomised, multicentric, controlled clinical study. Forty participants (20 control and 20 diabetics) will be recruited from secondary and primary healthcare settings. The primary objective is to establish a new model of early diagnosis of metabolic diseases based on the respiratory and metabolic responses to transient 100% oxygen administration and ingestion of a standardised mixed meal. ANALYSIS: Raw data acquired with the CBmeter will be endorsed against gold standard techniques for heart rate, respiratory rate, oxygen saturation and interstitial glucose quantification and analysed a multivariate analysis software developed specifically for the CBmeter study (CBview). Data will be analysed using clustering analysis and artificial intelligence methods based on unsupervised learning algorithms, to establish the predictive value of diabetes diagnosis. ETHICS: The study was approved by the Ethics Committee of the Leiria Hospital Centre. Patients will be asked for written informed consent and data will be coded to ensure the anonymity of data. DISSEMINATION: Results will be disseminated through publication in peer-reviewed journals and relevant medical and health conferences. BMJ Publishing Group 2021-08-26 /pmc/articles/PMC8395299/ /pubmed/34446475 http://dx.doi.org/10.1136/bmjopen-2020-042825 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Diabetes and Endocrinology
Lages, Marlene
Carvalho, Lucinda
Feijó, Salvato
Vieira, Alexandra
Fonseca-Pinto, Rui
Guarino, Maria Pedro
CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title_full CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title_fullStr CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title_full_unstemmed CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title_short CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
title_sort cbmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
topic Diabetes and Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395299/
https://www.ncbi.nlm.nih.gov/pubmed/34446475
http://dx.doi.org/10.1136/bmjopen-2020-042825
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