CBmeter study: protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseases
Related Experiment Video For health informatics
Updated: Oct 22, 2025

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
Published on: August 17, 2022
Marlene Lages1, Lucinda Carvalho2,3, Salvato Feijó1,4
1ciTechCare - Center for Innovative Care and Health Technology, Polytechnic Institute of Leiria, Leiria, Portugal.
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.
More Related Videos
14:28Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care
Published on: May 10, 2024
09:33Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise
Published on: December 19, 2024
Related Concept Videos
Diagnosing Acidosis and Alkalosis
First, the pH level is assessed to determine whether the blood pH is normal (7.35–7.45), low (acidosis), or high (alkalosis).
Next, the PCO2 and...
Chemical Factors Affecting Respiration Centers
CO2 has a potent influence on respiration and is strictly regulated....
Assessment of Diffusion and Perfusion
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies
Medical History