Zeitler, P. | bioRxiv Science

bioRxiv2019

R Functions for Analysis of Continuous Glucose Monitor Data

Continuous glucose monitoring (CGM) is an essential part of diabetes care. Real-time CGM data are beneficial to patients for daily glucose management, and aggregate summary statistics of CGM measures are valuable to direct insulin dosing and as a tool for researchers in clinical trials. Yet, the various commercial systems still report CGM data in disparate, non-standard ways. Accordingly, there is a need for a standardized, free, open-source approach to CGM data management and analysis. Functions were developed in the free programming language R to provide a rapid, easy, and consistent methodology for CGM data management and analysis. Summary variables calculated by our package compare well to those generated by various CGM software, and our functions provide a more comprehensive list of summary measures available to clinicians and researchers. Consistent handling of CGM data using our R package may facilitate collaboration between research groups and contribute to a better understanding of free-living glucose patterns.

bioinformatics↗

bioRxiv2019

Body composition and markers of cardiometabolic health in transgender youth compared to cisgender youth: a cross-sectional study

ContextUp to 1.8% of adolescents identify as transgender and many more seek care, yet the impact of gender affirming hormone therapy (GAHT) on cardiometabolic health is unknown.\n\nObjectiveTo determine insulin sensitivity and body composition among transgender females (TF) and males (TM) on estradiol or testosterone, compared to cisgender females (CF) and males (CM).\n\nDesignPilot, cross-sectional study conducted from 2016-2018.\n\nSetting. Academic regional transgender referral center.\n\nParticipantsTransgender adolescents on either testosterone or estradiol for at least 3 months were recruited. Nineteen TM were matched to 19 CM and 42 CF on pubertal stage and body mass index (BMI). Eleven TF were matched to 23 CF and 13 TF to 24 CM on age and BMI.\n\nMain Outcome Measure(s)1/[fasting insulin] and body composition (dual-energy absorptiometry, DXA).\n\nResultsTotal body fat was lower in TM than CF (29{+/-}7 vs. 33{+/-}7%, p=0.002) and higher than CM (28{+/-}7 vs. 24{+/-}9%, p=0.047). TM had higher lean mass than CF (68{+/-}7 vs. 64{+/-}7%, p=0.002) and lower than CM (69{+/-} vs. 73{+/-}8%, p=0.029). Insulin sensitivity was not different between the groups.\n\nTF had lower body fat than CF (31{+/-}7 vs. 35{+/-}8%, p=0.033) and higher than CM (28{+/-}6 vs. 20{+/-}10, p=0.001). TF had higher lean mass than CF (66{+/-}6 vs. 62{+/-}7%, p=0.032) and lower than CM (69{+/-}5 vs. 77{+/-}9%, p=0.001). TF were more insulin resistant than CM (0.078{+/-}0.025 vs. 0.142{+/-}0.064, p=0.011).\n\nConclusionsTransgender adolescents on GAHT have significant differences in body composition compared to cisgender controls, with a body composition intermediate between BMI-matched cisgender males and females. These changes in body composition may have consequences for the cardiometabolic health of transgender adolescents.\n\nPrecisTransgender youth on gender affirming hormone therapy have differences in their percent fat and lean mass compared to cisgender (non-transgender) youth.

physiology↗