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An empirical index of insulin sensitivity from short IVGTT: validation against the minimal model and glucose clamp indices in patients with different clinical characteristics

Tura, A. ; Sbrignadello, S. ; Succurro, E. ; Groop, Leif LU ; Sesti, G. and Pacini, G. (2010) In Diabetologia 53(1). p.144-152
Abstract
Aims/hypothesis Minimal model analysis for insulin sensitivity has been validated against the glucose clamp and is an accepted method for estimating insulin sensitivity from IVGTT. However minimal model analysis requires a 3 h test and relevant expertise to run the mathematical model. The aim of this study was to suggest a simple predictor of minimal model analysis index using only 1 h IVGTT. Methods We studied participants with different clinical characteristics who underwent 3 h regular (n=336) or insulin-modified (n=160) IVGTT, or 1 h IVGTT and euglycaemic-hyperinsulinaemic clamp (n=247). Measures of insulin sensitivity were insulin sensitivity index estimated by minimal model analysis ( SI) and the mean glucose infusion rate (clamp)... (More)
Aims/hypothesis Minimal model analysis for insulin sensitivity has been validated against the glucose clamp and is an accepted method for estimating insulin sensitivity from IVGTT. However minimal model analysis requires a 3 h test and relevant expertise to run the mathematical model. The aim of this study was to suggest a simple predictor of minimal model analysis index using only 1 h IVGTT. Methods We studied participants with different clinical characteristics who underwent 3 h regular (n=336) or insulin-modified (n=160) IVGTT, or 1 h IVGTT and euglycaemic-hyperinsulinaemic clamp (n=247). Measures of insulin sensitivity were insulin sensitivity index estimated by minimal model analysis ( SI) and the mean glucose infusion rate (clamp) (M). A calculated S-I (CSI) predictor, CSI alpha x K-G/(Delta AUC(INS)/T), was suggested, based on the calculation of the rate of glucose disappearance K-G and the suprabasal AUC of insulin concentration Delta AUC(INS) over T=40 min. For all the participants, a was assumed equal to the regression line slope between K-G/(Delta AUC(INS)/T) and S-I in control participants. Results CSI and S-I showed high correlation (R-2=0.68-0.96) and regression line slopes of approximately one in the majority of groups. CSI tended to overestimate S-I in type 2 diabetic participants, but results were more reliable when CSI was computed with insulin-modified rather than regular IVGTT. CSI showed behaviours similar to S-I as regards relationships with BMI, acute insulin response and sex. CSI showed good correlation with M (R-2=0.82). Conclusions/interpretation A short test can achieve a good approximation of minimal model analysis and clamp insulin sensitivity. The importance of a method such as CSI is that it allows analysis of IVGTT datasets with samples limited to 1 h. (Less)
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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Insulin resistance, Glucose tolerance, Insulin action, intravenous glucose tolerance test, One hour
in
Diabetologia
volume
53
issue
1
pages
144 - 152
publisher
Springer
external identifiers
  • wos:000272530600021
  • scopus:72449142600
  • pmid:19876614
ISSN
1432-0428
DOI
10.1007/s00125-009-1547-9
language
English
LU publication?
yes
id
a6004c92-5440-4989-9707-85a6fe513da8 (old id 1535639)
date added to LUP
2016-04-01 11:13:50
date last changed
2024-04-08 02:48:12
@article{a6004c92-5440-4989-9707-85a6fe513da8,
  abstract     = {{Aims/hypothesis Minimal model analysis for insulin sensitivity has been validated against the glucose clamp and is an accepted method for estimating insulin sensitivity from IVGTT. However minimal model analysis requires a 3 h test and relevant expertise to run the mathematical model. The aim of this study was to suggest a simple predictor of minimal model analysis index using only 1 h IVGTT. Methods We studied participants with different clinical characteristics who underwent 3 h regular (n=336) or insulin-modified (n=160) IVGTT, or 1 h IVGTT and euglycaemic-hyperinsulinaemic clamp (n=247). Measures of insulin sensitivity were insulin sensitivity index estimated by minimal model analysis ( SI) and the mean glucose infusion rate (clamp) (M). A calculated S-I (CSI) predictor, CSI alpha x K-G/(Delta AUC(INS)/T), was suggested, based on the calculation of the rate of glucose disappearance K-G and the suprabasal AUC of insulin concentration Delta AUC(INS) over T=40 min. For all the participants, a was assumed equal to the regression line slope between K-G/(Delta AUC(INS)/T) and S-I in control participants. Results CSI and S-I showed high correlation (R-2=0.68-0.96) and regression line slopes of approximately one in the majority of groups. CSI tended to overestimate S-I in type 2 diabetic participants, but results were more reliable when CSI was computed with insulin-modified rather than regular IVGTT. CSI showed behaviours similar to S-I as regards relationships with BMI, acute insulin response and sex. CSI showed good correlation with M (R-2=0.82). Conclusions/interpretation A short test can achieve a good approximation of minimal model analysis and clamp insulin sensitivity. The importance of a method such as CSI is that it allows analysis of IVGTT datasets with samples limited to 1 h.}},
  author       = {{Tura, A. and Sbrignadello, S. and Succurro, E. and Groop, Leif and Sesti, G. and Pacini, G.}},
  issn         = {{1432-0428}},
  keywords     = {{Insulin resistance; Glucose tolerance; Insulin action; intravenous glucose tolerance test; One hour}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{144--152}},
  publisher    = {{Springer}},
  series       = {{Diabetologia}},
  title        = {{An empirical index of insulin sensitivity from short IVGTT: validation against the minimal model and glucose clamp indices in patients with different clinical characteristics}},
  url          = {{http://dx.doi.org/10.1007/s00125-009-1547-9}},
  doi          = {{10.1007/s00125-009-1547-9}},
  volume       = {{53}},
  year         = {{2010}},
}