PMID- 20144339
OWN - NLM
STAT- MEDLINE
DCOM- 20100602
LR  - 20211020
IS  - 1932-2968 (Electronic)
IS  - 1932-2968 (Linking)
VI  - 3
IP  - 4
DP  - 2009 Jul 1
TI  - Computing the risk of postprandial hypo- and hyperglycemia in type 1 diabetes 
      mellitus considering intrapatient variability and other sources of uncertainty.
PG  - 895-902
AB  - OBJECTIVE: The objective of this article was to develop a methodology to quantify 
      the risk of suffering different grades of hypo- and hyperglycemia episodes in the 
      postprandial state. METHODS: Interval predictions of patient postprandial glucose 
      were performed during a 5-hour period after a meal for a set of 3315 scenarios. 
      Uncertainty in the patient's insulin sensitivities and carbohydrate (CHO) 
      contents of the planned meal was considered. A normalized area under the curve of 
      the worst-case predicted glucose excursion for severe and mild hypo- and 
      hyperglycemia glucose ranges was obtained and weighted accordingly to their 
      importance. As a result, a comprehensive risk measure was obtained. A reference 
      model of preprandial glucose values representing the behavior in different ranges 
      was chosen by a xi(2) test. The relationship between the computed risk index and 
      the probability of occurrence of events was analyzed for these reference models 
      through 19,500 Monte Carlo simulations. RESULTS: The obtained reference models 
      for each preprandial glucose range were 100, 160, and 220 mg/dl. A relationship 
      between the risk index ranges <10, 10-60, 60-120, and >120 and the probability of 
      occurrence of mild and severe postprandial hyper- and hypoglycemia can be 
      derived. CONCLUSIONS: When intrapatient variability and uncertainty in the CHO 
      content of the meal are considered, a safer prediction of possible hyper- and 
      hypoglycemia episodes induced by the tested insulin therapy can be calculated.
CI  - Copyright 2009 Diabetes Technology Society.
FAU - Garcia-Jaramillo, Maira
AU  - Garcia-Jaramillo M
AD  - Institut d'Informatica i Aplicacions, Universitat de Girona, Campus de Montilivi, 
      Girona, Spain. magarcia@eia.udg.edu
FAU - Calm, Remei
AU  - Calm R
FAU - Bondia, Jorge
AU  - Bondia J
FAU - Tarin, Cristina
AU  - Tarin C
FAU - Vehi, Josep
AU  - Vehi J
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20090701
PL  - United States
TA  - J Diabetes Sci Technol
JT  - Journal of diabetes science and technology
JID - 101306166
RN  - 0 (Blood Glucose)
SB  - IM
MH  - Blood Glucose/*metabolism
MH  - Chi-Square Distribution
MH  - Computer Simulation
MH  - Diabetes Mellitus, Type 1/*blood
MH  - Humans
MH  - Hyperglycemia/*blood
MH  - Hypoglycemia/*blood
MH  - Individuality
MH  - Monte Carlo Method
MH  - *Postprandial Period
MH  - Reference Values
MH  - Risk
PMC - PMC2769964
EDAT- 2010/02/11 06:00
MHDA- 2010/06/03 06:00
PMCR- 2010/07/01
CRDT- 2010/02/11 06:00
PHST- 2010/02/11 06:00 [entrez]
PHST- 2010/02/11 06:00 [pubmed]
PHST- 2010/06/03 06:00 [medline]
PHST- 2010/07/01 00:00 [pmc-release]
AID - dst.3.4.0895 [pii]
AID - 10.1177/193229680900300437 [doi]
PST - epublish
SO  - J Diabetes Sci Technol. 2009 Jul 1;3(4):895-902. doi: 10.1177/193229680900300437.