Me

Measuring the "Mom-induced" insulin resistance this Christmas

Hacker News

Measuring the "Mom-induced" insulin resistance this Christmas

Does your mom show you love by the amount of cakes she bakes for you? If yes, please note that transient insulin resistance can develop within a week if you are pushing it. I’m a precision health consultant for longevity clinics, focused on spotting metabolic risk early and I built this comprehensive Glucose Metabolism Interpreter: - All labs are optional — plug in whatever you have - Uses HOMA2 instead of classic HOMA (which isn’t great because it’s linear). It also provide estimated beta-cell function - Includes insulin-independent markers, so it works even with basic annual labs - Gives you meaningful interpretation, not just numbers Don’t blame your mom :) I need to figure out where to secretly donate half of the cakes, because if I ate them all, my mom’s secret gift would be type 2 diabetes :) Merry Christmas to you and your pancreas!

Visit product View on Hacker NewsDec 25, 2025

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71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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