Glycemic signatures in the early diagnosis and personalized treatment of diabetes

Glycemic signatures in the early diagnosis and personalized treatment of diabetes

Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10\% of the population, in the United States are diagnosed with diabetes. Another 86 million are estimated to be pre-diabetic and up to 70\% of these individuals are estimated to develop diabetes without intervention. We h...

Full description

Bibliographic Details
Main Author: Hall, Heather
Corporate Author: Stanford University Department of Stem Cell Biology and Regenerative Medicine
Other Authors: Palmer, Theo (Thesis advisor, advisor), Sebastiano, Vittorio (Thesis advisor, advisor), Snyder, Michael, Ph. D (Thesis advisor, primary advisor.)
Format: Thesis Electronic Book
Language:English
Published: 2017
LEADER 02696nam a22002537i 4500
001 7998033e-5723-40ad-8c81-265272a11cf5
005 20230617000000.0
008 170901s2017 xx sm 000 0 eng d
040 |a CSt  |c CSt 
100 1 |a Hall, Heather  |? UNAUTHORIZED 
245 1 0 |a Glycemic signatures in the early diagnosis and personalized treatment of diabetes  |h [electronic resource] /  |c Heather Hall 
260 |c 2017 
300 |a 1 online resource 
500 |a Submitted to the Department of Stem Cell Biology and Regenerative Medicine 
502 |a Thesis (Ph.D.)--Stanford University, 2017 
520 3 |a Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10\% of the population, in the United States are diagnosed with diabetes. Another 86 million are estimated to be pre-diabetic and up to 70\% of these individuals are estimated to develop diabetes without intervention. We have used continuous glucose monitoring to investigate the frequency with which people have aberrant glucose control patterns, the types of patterns, and how these patterns are affected by nutrition. We developed an analytical framework for defining glucose variability that can group individuals into specific classes. We found a high incidence of glucose variability, particularly in response to certain foods, regardless of diagnosis. We find that variability is more common in the evening and post meals in pre-diabetics before becoming more continuous in diabetics. This variability appears earlier than clinical diagnosis of pre-diabetes and we find that it shows promise for predicting insulin resistance in a standardized setting. This study provides evidence that classification of glycemic signatures by variability shows promise for early intervention and personalized treatment of diabetes. Applying this metric in treatment and diagnosis will be critical in reducing the risk and prevalence of diabetes 
596 |a 21 22 
700 1 |a Palmer, Theo  |e advisor  |4 ths  |= ^A2527790 
700 1 |a Sebastiano, Vittorio,  |e advisor  |4 ths 
700 1 |a Snyder, Michael,  |c Ph. D  |e primary advisor.  |4 ths 
710 2 |a Stanford University  |b Department of Stem Cell Biology and Regenerative Medicine 
999 1 0 |i 7998033e-5723-40ad-8c81-265272a11cf5  |l a12134999  |s US-CST  |m glycemic_signatures_in_the_early_diagnosis_and_personalized_treatment_elect2017____________a________________________________________hall__heather______________________e 
999 1 1 |l a12134999  |s ISIL:US-CST  |t BKS  |a SPEC-COLL UARCH-30  |b 36105227897282  |c 3781 2017 H  |d ALPHANUM  |x NONCIRC  |y 36105227897282  |p UNLOANABLE 
999 1 1 |l a12134999  |s ISIL:US-CST  |t BKS  |a SUL INTERNET  |b 12134999-2001  |c INTERNET RESOURCE  |d ASIS  |x SUL  |y 12134999-2001  |p UNLOANABLE 

Similar Items