title: Estimating insulin sensitivity from glucose levels only: Use of a non-linear mixed effects approach and maximum a posteriori (MAP) estimation.
abstract: Insulin Sensitivity is an important parameter for the management of Diabetes. It can be derived for a particular patient using data derived from some glucose challenge tests using measured glucose and insulin levels at various times. Whilst a useful approach, deriving insulin sensitivities to inform insulin dosing in other settings such as Intensive Care Units can be more challenging - especially as insulin levels have to be assayed in a laboratory, not at the bedside. This paper investigates an approach to measure insulin sensitivity from glucose levels only. Estimates of mean and between individual parameter variances are used to derive conditional estimates of insulin sensitivity. The method is demonstrated to perform reasonably well, with conditional estimates comparing well with estimates derived from insulin data as well.
authors.affiliation: AstraZeneca R&D, Alderley Park, UK. james.yates@astrazeneca.com
authors.forename: James W T
authors.initials: JW
authors.lastname: Yates
authors.forename: Edmund M
authors.initials: EM
authors.lastname: Watson
mesh_terms: D000465:Algorithms; D000818:Animals; D001786:Blood Glucose / Q000032:analysis*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy / Q000378:metabolism*; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D007328:Insulin / Q000627:therapeutic use; D007333:Insulin Resistance; D008297:Male; D008954:Models, Biological; D051381:Rats; D017208:Rats, Wistar
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin