sweston4 · HackerTrans

4 tahun yang laludiscuss

I don't have any of these issues at all? I've a folder called 'main blogs' which is just every feed I follow. Any link I have to Feedly is a link to my 'main blogs' folder which provides a pretty clean interface. I have 0 adds on my 'main blogs' page currently. Perhaps a similar setup would work for others.

sweston4

4 tahun yang laludiscuss

Hey Jeremy, I was hoping to send you an email based on the email in your profile ([email protected]) and received an "address not found". Would there be a better way to reach you?

sweston4

4 tahun yang laludiscuss

Oh, I am very happy to answer this to the extent I can. Whey protein impacts my blood glucose in confusing ways! Most days, I'll have a whey protein shake that consists of one scoop whey protein, a little bit of coffee for taste, and some almond milk. This will typically be my first meal after ~12-16 hours without eating. The correct dose of insulin for this shake can vary from 2 units of insulin to 4.

First, I believe you're correct that gluconeogenesis happens rarely. More specifically, I believe it happens in the absence of carbohydrates in the food you consume. Since I eat a low carb diet, it would make sense that I experience gluconeogenesis.

Second, have I noticed a spike in glucose? Yes! I have to take some amount of insulin if I have a protein shake. The coffee has no effect, so any effect comes from the almond milk and whey. There's maybe half a cup of almond milk in my shakes which is close to negligible. We can probably assume that whey drives most of the glucose effects from my shake.

Third, why is there so much variance in my blood glucose response and insulin requirements? Here, I do not have a defined answer. One aspect may be that whey is quickly digested. The quick digestion may accelerate the effect of gluconeogenesis. Another factor may be the state of the glucose reserves in my liver before I consume the whey. If I'm in a state of ketosis, it may be that my body accelerates gluconeogenesis because it believes it's in a carbohydrate shortage. In this situation, the glucose spike may exceed what would otherwise be expected. There's a few other things such as exercise I'd include here, but I don't have a single definitive answer to this.

A final note: In some sense, I can feel/anticipate my insulin sensitivity during the day. I cannot explain this in writing in any coherent way, but I have decent intuition on what insulin dose between 2 and 4 units I should pick each day. Or, before bed, even if my blood sugar appears constant and in-range, I may anticipate that it'll go up and down as I sleep and eat/inject insulin accordingly. One part of this intuition is "knowing" rather a protein heavy meal will kick into gluconeogenesis while I sleep. Anyways, I can answer more, but as you can perhaps tell, most of my explanations are of the waves hands variety.

sweston4

4 tahun yang laludiscuss

I 100% agree with what you're saying.

Assume a 1:10 insulin to carb ratio (though I don't think insulin dosages have a strictly linear effect) and a meal of 100 carbs. If the meal, in reality, has 80 carbs, you've injected two extra units of insulin. We might expect a unit of insulin to reduce blood glucose by 30-50 mg/dl, so we've reduced our expected blood glucose by 60-80 mg/dl. If you target a blood glucose of 80 mg/dl, this would mean your expected future glucose is 0-20 mg/dl. In that case, you would die.

Now, the problem with this example is that I would 100% take action to avoid dying, so my actual risk of death is still minute despite having a lethal dose of insulin in my body at the time I inject myself. However, it's still a bit strange to know that, conditional on me taking no independent action, I'm hours away from death in certain situations.

sweston4

4 tahun yang laludiscuss

Thanks for this! Bernstein's book is the source of my "variance reduction" strategy too! The one thing I haven't adopted is the slower acting insulin. It's one of those things that I know I should try but just haven't gotten around to yet, so thanks for the extra incentive to try it.

sweston4

4 tahun yang laludiscuss

I'm a type 1 diabetic and data scientist. Estimating the causal effect of a unit of insulin or food on blood sugar is an absolute crap shoot. Consider that there's a +/-20% margin of error on the reported carbohydrates on nutrition facts. We might consider this irreducible error that just cannot be modelled (Maybe you could get a calorimeter, estimate the distribution of errors, and reduce that error somewhat). Therefore, even if we created a model that explained all explainable variance, we still have a 20% margin of error. If a meal has enough carbohydrates, a 20% overestimate of insulin requirements would lead to an insulin overdose that would kill you if the resulting low blood sugar is not dealt with. In other words, the irreducible variance is so large that a "perfect" model would regularly suggest lethal insulin doses.

My "solution" is to eat low-carb/keto as a "variance reduction" strategy. Still, removing carbs also introduces gluconeogenesis (the production of glucose from protein) as a factor to consider. The synthesis of protein to glucose also occurs on a much time different time horizon than the consumption of carbs themselves which has implications for insulin dosing and insulin type.

I could go on! But long story short, modelling blood glucose is bloody hard.

sweston4

6 tahun yang laludiscuss

Oh my god, I just finished this book, and I had the exact same thought. Serendipitous

sweston4

7 tahun yang laludiscuss

Location: Tennessee

Remote: OK

Willing to relocate: Yes

Technologies: Python, R, SQL, ggplot/matplotlib, GIS

Résumé: https://drive.google.com/open?id=1uWBKgzZ5j89f2jye1NQuDs85hn...

Side Project:https: github.com/Spencer-Weston/NBA_bet

Personal Website: crockpotthoughts.wordpress.com

Email: [email protected]

Data Scientist with a specialty in spatial statistics. After graduation (2017), I worked at Oak Ridge National Laboratory on population estimation for a year. Since then, I've spent my time travelling the United States and Canada to see where I should live next. Conclusion: I'll be happy most places. I'm now looking for a new opportunity and would appreciate the opportunity to learn about your company.

If you'd like to learn more about me, I'd recommend visiting my personal website. Or even better, feel free to email me with any questions.

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