PMID- 32746043
OWN - NLM
STAT- MEDLINE
DCOM- 20210625
LR  - 20210625
IS  - 1558-2531 (Electronic)
IS  - 0018-9294 (Linking)
VI  - 68
IP  - 2
DP  - 2021 Feb
TI  - Using Iterative Learning for Insulin Dosage Optimization in 
      Multiple-Daily-Injections Therapy for People With Type 1 Diabetes.
PG  - 482-491
LID - 10.1109/TBME.2020.3005622 [doi]
AB  - OBJECTIVE: In this work, we design iterative algorithms for the delivery of 
      long-acting (basal) and rapid-acting (bolus) insulin, respectively, for people 
      with type 1 diabetes (T1D) on multiple-daily-injections (MDIs) therapy using 
      feedback from self-monitoring of blood glucose (SMBG) measurements. METHODS: 
      Iterative learning control (ILC) updates basal therapy consisting of one 
      long-acting insulin injection per day, while run-to-run (R2R) adapts meal bolus 
      therapy via the update of the mealtime-specific insulin-to-carbohydrate ratio 
      (CR). Updates are due weekly and are based upon sparse SMBG measurements. 
      RESULTS: Upon termination of the 20 weeks long in-silico trial, in a scenario 
      characterized by meal carbohydrate (CHO) normally distributed with mean mu = [50, 
      75, 75] grams and standard deviation sigma = [5, 7, 7] grams, our strategy produced 
      statistically significant improvements in time in range (70--180) [mg/dl], from 
      66.9(33.1) % to 93.6(6.7) %, p = 0.02. CONCLUSIONS: Iterative learning shows 
      potential to improve glycemic regulation over time by driving blood glucose 
      closer to the recommended glycemic targets. SIGNIFICANCE: Decision support 
      systems (DSSs) and automated therapy advisors such as the one proposed here are 
      expected to improve glycemic outcomes reducing the burden on patients on MDI 
      therapy.
FAU - Cescon, Marzia
AU  - Cescon M
FAU - Deshpande, Sunil
AU  - Deshpande S
FAU - Nimri, Revital
AU  - Nimri R
FAU - Doyle Iii, Francis J
AU  - Doyle Iii FJ
FAU - Dassau, Eyal
AU  - Dassau E
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20210120
PL  - United States
TA  - IEEE Trans Biomed Eng
JT  - IEEE transactions on bio-medical engineering
JID - 0012737
RN  - 0 (Blood Glucose)
RN  - 0 (Hypoglycemic Agents)
RN  - 0 (Insulin)
SB  - IM
MH  - Blood Glucose
MH  - Blood Glucose Self-Monitoring
MH  - *Diabetes Mellitus, Type 1/drug therapy
MH  - Humans
MH  - Hypoglycemic Agents/therapeutic use
MH  - Insulin/therapeutic use
MH  - Insulin Infusion Systems
EDAT- 2020/08/04 06:00
MHDA- 2021/06/29 06:00
CRDT- 2020/08/04 06:00
PHST- 2020/08/04 06:00 [pubmed]
PHST- 2021/06/29 06:00 [medline]
PHST- 2020/08/04 06:00 [entrez]
AID - 10.1109/TBME.2020.3005622 [doi]
PST - ppublish
SO  - IEEE Trans Biomed Eng. 2021 Feb;68(2):482-491. doi: 10.1109/TBME.2020.3005622. 
      Epub 2021 Jan 20.