Cardiometabolic Devices Accuracy Study

Diabetes Mellitus Clinical Trial

Official title: Performance and Usability Evaluation of Cardiometabolic Point-of-care Devices in a Target Use Setting

Status Completed

Clinical Trial Summary

With the rise of cardiovascular diseases (CVD) and diabetes, the global disease burden is shifting towards non-communicable diseases (NCDs). An increasing number of low- and middle-income countries (LMICs) are currently experiencing the double burden of infectious and non-communicable diseases. In order to facilitate a patient-centred approach to healthcare, there is an urgent need to ensure that primary healthcare (PHC) facilities in LMICs are capable of addressing diagnosis and monitoring of non-communicable diseases at the point-of-care (POC). Important minimum parameters for PHC POC diagnosis and monitoring of cardiometabolic diseases are lipids/lipoproteins, glucose, glycated haemoglobin (HbA1c) and serum creatinine, to address cardiovascular disease, diabetes and chronic kidney disease. While several technologies of multi-parameter POC devices capable of supporting diagnosis and monitoring of cardiometabolic diseases exist, their quantitative accuracy is often not well evaluated outside of the manufacturer's laboratories and published independent evaluations can be rare, particularly in the settings of intended use. These settings are PHC facilities in varying climatic environments and with staff without specialist laboratory training. Our study aims to evaluate the quantitative accuracy of 2 cardiometabolic POC devices in a setting of intended use and performed by the intended user. (Evaluating the quantitative measurements of glucose, HbA1c, total cholesterol and creatinine as measured in a healthcare setting with point-of-care multiparameter devices compared to a laboratory reference method).

Clinical Trial Description

Independent performance evaluation of POC devices have shown that many devices, regardless of their intended use, do not perform as well as the manufacturers' claims may suggest. There are a variety of reasons for this, including difference in skills levels of personnel who were involved in generating the data for the manufacturer's claims and who actually perform the test in a clinic, limited evaluation of samples from different geographical locations and thus potential interfering substances or less controlled environmental conditions (e.g. dust, heat and humidity). Independent performance evaluations to assess clinical accuracy, as well as system usability are important to drive adoption of any technology, and even more so, if the technology is intended to move testing outside of the traditional setting, i.e. away from the central laboratory to the point-of-care. Many devices appear ideally suited for certain settings, however when it comes to actual implementation, the users often discover that the device and workflow do not meet their needs. The choice of a suboptimal device means badly invested resources and may lead to inappropriate use, resulting in fewer reliable tests for patients in the absence of alternatives. Data from real-world evaluations in settings of the intended use can support decision makers to select the right device. The setting for this study will be a primary healthcare facility and a health post in Nepal, where study participants attend the facility in the context of the "Early detection and management of Chronic Kidney Diseases, Hypertension, Diabetes and Cardiovascular disease in Community in Nepal (KHDC-Nepal) program", conducted by the University Hospital of Geneva and the BP Koirala Institute of Health Science in Nepal. ;

Related Conditions & MeSH terms

• Chronic Kidney Diseases
• Diabetes Mellitus
• Hyperlipidemias
• Kidney Diseases
• Renal Insufficiency, Chronic

• NCT number: NCT05257564
• Study type: Interventional
• Source: Foundation for Innovative New Diagnostics, Switzerland
• Status: Completed
• Phase: N/A
• Start date: February 14, 2022
• Completion date: June 30, 2022