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Serum glycosylated proteins as a measure of carbohydrate metabolism in users of oral contraceptives

  • H. J. Kloosterboer
  • G. J. Bruining
  • P. Liukko
  • S. Nummi
  • L. Lund

Summary

Women using oral contraceptives may display minor alterations in carbohydrate metabolism. Using the oral glucose tolerance test (oGTT) it has been demonstrated that currently used low-dose combination pills induce an increase in the insulin response. In addition it has been suggested that during long-term use of low-dose combination pills glucose tolerances deteriorate. The oGTT is not performed under physiological conditions, and so it is questionable as to whether such a test truly reflects the glucose metabolic state. Moreover, the results are often influenced by factors such as stress and diet. The amount of glycosylated protein in serum is at present considered a good index of glucose homeostasis during the fourteen days preceding blood sampling.

A reliable method for the determination of serum glycosylated proteins, which allows assessment of carbohydrate metabolism under more physiological conditions than those found in the oGTT, has been developed in our laboratory.

This method was applied for the estimation of the effect of a new progestational compound, desogestrel, on carbohydrate metabolism. Glycosylated serum proteins, measured as the amount of hydroxy-methylfurfural released per gram of protein, was estimated in (a) women receiving 0.125 mg desogestrel per day for 2 months and (b) women receiving the new oral contraceptive combination 0.150 mg desogestrel + 0.030 mg ethinyloestradiol (EE) for 3, 18 or 24 months.

It can be concluded from these studies that neither desogestrel alone nor the 150/30 combination of desogestrel and EE have any effect on carbohydrate metabolism.

Keywords

Glucose Tolerance Oral Contraceptive Oral Glucose Tolerance Test Carbohydrate Metabolism Glucose Homeostasis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1984

Authors and Affiliations

  • H. J. Kloosterboer
  • G. J. Bruining
  • P. Liukko
  • S. Nummi
  • L. Lund

There are no affiliations available

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