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Many non diabetics are wearing CGMs to better understand their blood sugar patterns. Here's what I learned from wearing a continuous glucose monitor.
Diabetic-Non-diabetic-Prediction. The objective is to predict whether or not a patient has diabetes. The Dataset used in this project is originally from NIDDK. Visually explored variables using histograms. Created scatter charts between the variables to understand the relationships.
Create a dashboard in tableau by choosing appropriate chart types and metrics useful for the business. The dashboard must entail the following: a) Pie chart to describe the diabetic/non-diabetic population. b) Scatter charts between relevant variables to analyse the relationship. c) Histogram/frequency charts to analyse the distribution of the ...
- What's The Point of Wearing A Continuous Glucose Monitor?
- Insight #1: Food Pairings Have A Big Impact on Glucose Levels
- Insight #2: A Few Carbohydrates Can Cause A Giant Glucose Spike
- Insight #3: Late Night Meals May Increase Your Fasting Glucose Levels
- Insight #4: Glucose Levels Are Sensitive to Stress
- Insight #5: Seeing Your Glucose Levels Keeps Mindless Eating in Check
Being able to see how your blood glucose levels respond in real-time to your many lifestyle factors makes it easy to identify what you're doing well and where there's room for improvement. It also may offer some insight into certain symptom patterns such as post-meal fatigue. Once you have access to this data, you have more power. You can discover ...
While wearing my CGM sensor, discoveries started to pop up all over the place. In particular, I really gained insight into my meal choices. I could list 50 different food insights I learned, but one thing that really stood out was the impact of heavily processed foods. Oatmeal paired with scrambled eggs is something I commonly have as a post-workou...
I used to be scared of consuming too many carbs. I ate my oatmealin hiding, not letting anyone know of my “guilty” pleasure. I avoided bananas like the plague. If I was craving carbs, I ate sweet potatoes, thinking they were the better alternative. What I learned when I started measuring my food responses was the exact opposite of my initial thinki...
Carbohydrates affect my glucose levels more negatively as the day progresses, as insulin sensitivity naturally lowers in the evening hours. A higher glucose spike from carbohydrates consumed at night turns out to be a fairly typical response found in many people. Most of your hormones work on a circadian rhythm, and insulin is no exception. Insulin...
The most significant non-food variable that affected my glucose levels is, unsurprisingly, STRESS! While wearing the CGM, I had just started another job on top of my full-time job. I was working all the time, barely sleeping, and always stressed about finding enough time in the day to get everything done. While this was happening, I watched my fast...
Finally, and arguably most importantly, continuous glucose monitoring and receiving real-time feedback improved my relationship with food. I know I'm not alone when I admit to not always having had a healthy relationship with food. Feeling stressed? Grab the chips. Feeling bored? Open the fridge. Binged on some cookies? Guilt and self-loathing for ...
Apr 25, 2019 · Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes. Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking.
- Viral N Shah, Stephanie N DuBose, Zoey Li, Roy W Beck, Anne L Peters, Ruth S Weinstock, Davida Kruge...
- 10.1210/jc.2018-02763
- 2019
- 2019/10
CGMap, a characterization of CGM data collected from over 7,000 non-diabetic individuals. First map of reference values of CGM-derived measures, a tool for future CGM research. CGM-derived measures are associated with clinical parameters, some from fundus imaging.
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Do new-generation CGM sensors measure glycemic levels in healthy nondiabetic individuals?
What is diabetic non-diabetic prediction?
Does continuous glucose monitoring improve glycemic performance in diabetic patients?
Can a non diabetic wear a continuous glucose monitor?
Sep 1, 2021 · Control Variability Grid Analysis, a visualization tool used to determine trends in glucose control. The following sections will demonstrate how to calculate or create the relevant value or visualization, an explanation of why it’s important, and an example analysis of my own data.
