The lack of standardized reference range for the homeostasis model assessment-estimated insulin resistance HOMA-IR index has limited its clinical application. This study investigated a Hispanic population of adults, randomly selected on the basis of Census tract data in the city of Brownsville, Cameron County.
Machine learning methods, support vector machine SVM and Bayesian Logistic Regression BLRwere used to automatically identify measureable variables using standardized values that correlate with HOMA-IR; K-means clustering was then used to classify the individuals by insulin resistance.
There are Our results are dramatically different using the popular clinical cutoff of 2.
It is calculated multiplying fasting plasma insulin FPI by fasting plasma glucose FPGthen dividing by the constant This method has been applied across all ethnic groups. One study suggested that the range of normal HOMA-IR in a healthy Hispanic population may be higher than for Caucasians in central and north America and certainly this population is known to have a genetic susceptibility to type 2 diabetes, which is closely associated with insulin resistance.
Therefore, in spite of its importance, the lack of standardized reference range for HOMA-IR has hindered its clinical and population application. We used the accepted national standard values of the variables in our model e.
Simulation and Game Index
BMI, waist-to-hip ratio, triglyceride levels etc based on published recommendations that are currently and widely used in different populations.
Using this method we identified those variables associated with elevated HOMA-IR and then defined its optimal reference range in an adult Hispanic Mexican American population in south Texas. The design and collection of data for this cohort was previously described . Insulin was measured in batches using the enzyme-linked immunosorbent assay insulin kit Mercodia, Uppsala, Sweden using the standard curves supplied with the kit .
Based on the classification results, a series of cutoffs of HOMA-IR was evaluated for the sensitivity the true positive rate and specificity the true negative rate, or 1- the false positive rate.
To identify the best cutoff value, a receiver operator characteristic ROC analysis was performed based on the sensitivity and specificity values of the series of cutoffs. The best cutoff was identified using the maximum Matthews correlation coefficient.
Increased FPG is a direct result of insulin resistance because of decreased sensitivity to the glucose-lowering effect of insulin. Both serum triglycerides and total cholesterol were associated with HOMA-IR, though the effect of triglycerides is stronger than cholesterol.
ALT is mainly produced in the liver, and is elevated in serum in conditions leading to chronic hepatocellular injury.
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Elevated AST may also reflect liver injury, but less specifically. The correlation between liver function and insulin resistance may be explained by the critical role of liver in glucose-insulin metabolism liver injury caused by insulin resistance or disorders of adipose metabolism compounded by liver dysfunction and insulin resistance . Otherwise, the noise effects of uncorrelated factors interfere with the proper classification of individuals with or without insulin resistance.
After the identification of factors which best correlated with elevated HOMA-IR we used the reference ranges of these factors to classify the individuals as having insulin resistance Table S2. The reference ranges of BMI, serum triglycerides, total cholesterol, HDL cholesterol, and blood pressures, were based on the recommendations of the American Heart Association www.
Based on these categorized factors, the individuals were classified into two groups by the K-means clustering Table 1.To view the D2L. Learn how Brightspace can help you Engage young minds. Learn how Brightspace can help you Drive learner success.
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Springe direkt zu Inhalt. MA International Relations. Path Navigation Homepage Modules. Modules and Courses of International Relations Online International Relations Online IRO seeks to equip you with the capacity to apply theoretical concepts to pressing issues in world politics and to design recommendations for policy-making.Machine Learning is an international forum for research on computational approaches to learning.
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The newsletter is offered in English only at the moment. Sign up now. Sign in with Github Sign in with Google.Founded inInfraspection Institute has trained and certified over 10, thermographers worldwide. With over 35 years in business, Infraspection Institute literally pioneered the thermography training industry. During our long history, we have shaped the infrared industry through training, consulting, technical publications, research, standards developmentand software publishing.
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These exams are open book tests that are based upon the content of the subject course.
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Unlike certifications offered by other infrared training firms, Infraspection Institute certifications have no expiration date and are good for life. Infraspection Institute does not charge renewal fees nor is it conditional upon your future attendance at technical conferences. Continuing Education Credits are available for several of our infrared training courses. The Conference Center is easily reached from major highways and is approximately 50 miles from both Philadelphia International and Liberty International Airports.
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