Whether you’re a parent, an athlete, or a clinician, this guide answers the 15 most common questions about CamAPS FX, from starting in the first two weeks to managing exercise, pizza nights, and sensor choice.
I was only able to put this together after attending the MyLife DiabetesCare Excellence exchange at EASD 2025!
The Algorithm
1. What does CamAPS FX use to run?
Only body weight + total daily insulin dose. It ignores preset basal, ISF, ICR, or AIT.
2. How does CamAPS adapt over time?
Three levels: daily (long-term insulin need), hourly (circadian rhythm), post-meal (learned over ~5 days).
3. How is CamAPS different from other systems (780G, Control-IQ)?
CamAPS: basal-heavy corrections, scaling up to 500–700% of ‘internal basal.’
780G / Control-IQ: cap basal at ~250% and rely on auto-boluses.
What about Active Insulin Time (AIT)?
AIT is not a user setting — CamAPS estimates it dynamically each loop cycle.
Getting Started (First 2 Weeks)
4. What’s the rule for the first 14 days?
Avoid Boost and Ease-off unless safety requires. Let the algorithm learn.
5. What personal glucose target (PGT) should I set?
Most common: 5.0-6.0 mmol/L 9100–120 mg/dL). Lower = higher time in range but higher risk of hypos. Night is the safest time to tighten. Young children often need higher PGT during the day due to erratic activity levels.
Advanced Features
6. When should I use Boost?
For illness or known glucose-raising events. Use sparingly — overuse blunts algorithm adaptation.
7. When should I use Ease-off?
Sporadic exercise, illness, or stress. Planned Ease-off can be scheduled (parent-friendly).
8. What about Add Meal?
For high-fat or high-protein meals. Works like an extended bolus, but only gives the extra insulin if it’s needed.
Exercise
9. How do I prevent overnight hypos after evening training?
Raise overnight Personal Glucose Target. Only snack if trending down with insulin on board. Adjust if the pattern repeats. See the AID and exercise guide for more.
Meals & Bolus Strategies
10. Do I need exact carb counting?
Not always. Simplified meal announcement is non-inferior to exact carb counting in trials.
11. How do I handle pizza and high-fat meals?
60% normal carb entry, 40% ‘slowly absorbed meal.’ Use Add Meal if a late rise appears. Boost only if necessary.
12. Do apps like Snaq help?
RCT (n=44, 3 weeks): +6.6% TIR, mean glucose ↓0.54 mmol/L. Lower error vs patients/CalorieMama. Consistency not significantly better. Low uptake: ~1.6 uses/day, 19% advice followed.
Sensor Considerations
12. Dexcom or Libre?
Dexcom G6/G7: factory-calibrated, optional calibration if drift, but 10 days and bigger.
Libre 3: factory-calibrated, no calibration option, but smaller and 15 days
13. Should I insert sensors early?
If significant inaccuracies occur, consider inserting the sensor 24–36h before activation for smoother performance (let the inflammation settle).
Connectivity & Troubleshooting
14. Why does Auto mode turn off?
Families sometimes toggle off thinking insulin ‘stops when low.’ Technical: phone >6m, Bluetooth cache, set issue.
15. What’s the best troubleshooting routine?
Restart phone at set change. Clear Bluetooth cache. Keep the phone within 6 m.
GNL Resources
- Tips & Tricks for CamAPS FX
- Podcast Episode: Exercise & CamAPS FX
- CGM Series
- AID Series
- Bolus strategies for challenging meals
References
Alwan H, Wilinska ME, Ruan Y, Da Silva J, Hovorka R. Real-World Evidence Analysis of a Hybrid Closed-Loop System. J Diabetes Sci Technol. 2025 Mar;19(2):385-389. doi: 10.1177/19322968231185348. Epub 2023 Jul 8. PMID: 37421250
Baumgartner M, Kuhn C, Nakas CT, Herzig D, Bally L. Carbohydrate Estimation Accuracy of Two Commercially Available Smartphone Applications vs Estimation by Individuals With Type 1 Diabetes: A Comparative Study. J Diabetes Sci Technol. 2024 Jul 26:19322968241264744. doi: 10.1177/19322968241264744. Epub ahead of print. PMID: 39058316
Moser O et al. Exercise and CGM in type 1 diabetes (position statement). Diabetologia. 2020. PMID: 33047169
Moser O, Zaharieva DP, Adolfsson P, Battelino T, Bracken RM, Buckingham BA, Danne T, Davis EA, Dovč K, Forlenza GP, Gillard P, Hofer SE, Hovorka R, Jacobs PG, Mader JK, Mathieu C, Nørgaard K, Oliver NS, O’Neal DN, Pemberton J, Rabasa-Lhoret R, Sherr JL, Sourij H, Tauschmann M, Yardley JE, Riddell MC. The use of automated insulin delivery around physical activity and exercise in type 1 diabetes: a position statement of the European Association for the Study of Diabetes (EASD) and the International Society for Pediatric and Adolescent Diabetes (ISPAD). Diabetologia. 2025 Feb;68(2):255-280. doi: 10.1007/s00125-024-06308-z. PMID: 39653802
Tecce N, Vetrani C, Pelosi AL, Alfiore M, Mayol D, Maddaloni MG, Amodio M, Colao A. AI-Powered Carbohydrate Counting for Type 1 Diabetes: Accuracy and Real-World Performance. Diabetes Care. 2025 Aug 1;48(8):e97-e98. doi: 10.2337/dc25-0303. PMID: 40397829.
Questions Still Unanswered
- Transparency of algorithms: CamAPS ignores presets, but clinicians lack clear guidance on its internal caps vs 780G/Control-IQ.
- Boost/Ease-off overuse: How often does this blunt learning in real-world use?
- Meal handling: Should AID systems auto-detect fat/protein effect rather than relying on a manual ‘slowly absorbed meal’?
- App integration: Snaq showed +6.6% TIR, but uptake was low. Will embedding AI tools inside AID workflows improve adherence?