The Myth of MARD (Mean Absolute Relative Difference): Limitations of MARD in the Clinical Assessment of Continuous Glucose Monitoring Data
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.The mean absolute relative difference (MARD) for glucose sensors is widely used but may not reflect clinical relevance. Alternative assessments offer more meaningful insights into sensor safety and effectiveness for people with diabetes.
Area Of Science
- Diabetes technology
- Biomedical engineering
- Clinical research
Background
- Mean Absolute Relative Difference (MARD) is the primary metric for glucose sensor accuracy.
- Its clinical relevance is debated due to limited evidence in current sensor technology.
- MARD calculation is simple but evaluation is complex, influenced by study design and participant factors.
Approach
- This review critically examines the widespread adoption of MARD.
- It highlights the impact of study design, demographics, and glycemic ranges on MARD values.
- The limitations of MARD in assessing safety and effectiveness are discussed.
Key Points
- MARD is only one of several statistical metrics (e.g., bias, precision) for sensor accuracy.
- Analytic metrics like MARD offer limited insight into real-world safety and effectiveness.
- No clinical studies prove MARD differentiates safe/unsafe or effective/less effective sensors.
Conclusions
- Alternative methods like error grid analyses and clinical studies in people with diabetes (PWD) provide clinically meaningful assessments.
- The focus should shift from MARD to clinically relevant evaluations for diabetes technology.
- Demystifying MARD's status is crucial for the diabetes community.
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
Related Concept Videos
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
When assessing blood pressure (BP), healthcare professionals must consider various factors and potential unexpected outcomes to ensure accurate readings and provide proper patient care. Adhering to these guidelines is essential to achieving the most reliable results.
Monitoring Both Arms:
Monitoring BP in both arms during the initial assessment is advisable, as the systolic value may differ by five to ten mm Hg between arms. For subsequent BP assessments, use the arm with the higher reading.
A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...