UNLABELLED: In clinical studies insulin resistance, the main factor of the Metabolic Syndrome (MS), is determined directly by metabolic clamp technique, while in epidemiological studies is estimated on the basis of indices calculated from oral glucose tolerance test glycemia and insulinemia. The aim of the study was to find out which insulin resistance indicator best predicts the risk of the MS. MATERIAL AND METHODS: The study population consisted of 2673 inhabitants of Kraków, aged 35-75 years, who participated in the "Polish Multicenter Study on Diabetes Epidemiology". Fasting insulin, HOMA-IR, QUICKI and Matsuda's index were determined for all subjects. Insulin resistance was defined as the cutoff values for the population with normal glucose tolerance and with BMI < 25 kg/m2. RESULTS: All insulin resistance indices were closely correlated (r=0.78-0.98), and the frequency of insulin resistance in the general population was similar (47%-54%), however the highest prevalence of insulin resistance was observed when Matsuda index was used. The risk of insulin resistance, increased with the category of glucose tolerance, and was the highest when Matsuda index was used. The MSWHO was observed in 42% to 45% of the studied population and the predictive value of insulin resistance indices were similar when using WHO criteria. The highest sensitivity in the MSNCEP identification was observed when Matsuda index was used. Matsuda index had also the highest sensitivity to diagnose MSNCEP as compared with the remaining insulin resistance indices. CONCLUSIONS: The study insulin resistance indices have a similar value in predicting the MSWHO while Matsuda index predicts best the MSNCEP. Matsuda index as well predicts best the risk of insulin resistance. This argues in favor of using oral glucose tolerance test to estimate risk for diabetes mellitus and cardiovascular disease.
UNLABELLED: In clinical studies insulin resistance, the main factor of the Metabolic Syndrome (MS), is determined directly by metabolic clamp technique, while in epidemiological studies is estimated on the basis of indices calculated from oral glucose tolerance test glycemia and insulinemia. The aim of the study was to find out which insulin resistance indicator best predicts the risk of the MS. MATERIAL AND METHODS: The study population consisted of 2673 inhabitants of Kraków, aged 35-75 years, who participated in the "Polish Multicenter Study on Diabetes Epidemiology". Fasting insulin, HOMA-IR, QUICKI and Matsuda's index were determined for all subjects. Insulin resistance was defined as the cutoff values for the population with normal glucose tolerance and with BMI < 25 kg/m2. RESULTS: All insulin resistance indices were closely correlated (r=0.78-0.98), and the frequency of insulin resistance in the general population was similar (47%-54%), however the highest prevalence of insulin resistance was observed when Matsuda index was used. The risk of insulin resistance, increased with the category of glucose tolerance, and was the highest when Matsuda index was used. The MSWHO was observed in 42% to 45% of the studied population and the predictive value of insulin resistance indices were similar when using WHO criteria. The highest sensitivity in the MSNCEP identification was observed when Matsuda index was used. Matsuda index had also the highest sensitivity to diagnose MSNCEP as compared with the remaining insulin resistance indices. CONCLUSIONS: The study insulin resistance indices have a similar value in predicting the MSWHO while Matsuda index predicts best the MSNCEP. Matsuda index as well predicts best the risk of insulin resistance. This argues in favor of using oral glucose tolerance test to estimate risk for diabetes mellitus and cardiovascular disease.
Authors: Krzysztof C Lewandowski; Justyna Płusajska; Wojciech Horzelski; Ewa Bieniek; Andrzej Lewiński Journal: Endocr Connect Date: 2018-02-07 Impact factor: 3.335
Authors: Krzysztof C Lewandowski; Elżbieta Skowrońska-Jóźwiak; Katarzyna Łukasiak; Katarzyna Gałuszko; Aleksandra Dukowicz; Magdalena Cedro; Andrzej Lewiński Journal: Arch Med Sci Date: 2019-01-30 Impact factor: 3.318
Authors: Marta Siomkajło; Jacek Rybka; Magdalena Mierzchała-Pasierb; Andrzej Gamian; Joanna Stankiewicz-Olczyk; Marek Bolanowski; Jacek Daroszewski Journal: Endocrine Date: 2017-10-26 Impact factor: 3.633