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Related Experiment Videos

Variability of HOMA and QUICKI insulin sensitivity indices.

Miloš Žarković1,2, Jasmina Ćirić1,2, Biljana Beleslin1,2

  • 1a Internal Medicine, School of Medicine , University of Belgrade , Belgrade , Serbia.

Scandinavian Journal of Clinical and Laboratory Investigation
|April 1, 2017
PubMed
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Estimating insulin sensitivity with HOMA and QUICKI indices shows significant biological variability. Increasing the number of insulin and glucose samples reduces this variability, mainly caused by plasma insulin oscillations.

Area of Science:

  • Endocrinology
  • Metabolic Research
  • Clinical Biochemistry

Background:

  • Insulin sensitivity assessment is crucial for metabolic health.
  • Commonly used indices like HOMA and QUICKI rely on single insulin and glucose measurements.
  • Understanding the variability of these indices is essential for accurate clinical interpretation.

Purpose of the Study:

  • To evaluate the biological variability of insulin sensitivity estimates using HOMA and QUICKI indices.
  • To determine the impact of the number of samples on the reliability of these indices.
  • To identify the primary drivers of variability in insulin sensitivity measurements.

Main Methods:

  • Blood samples were collected from 56 subjects over 90 minutes with 2-minute intervals after a 12-hour fast.
Keywords:
Diabetes mellitusglucoseinsulininsulin resistancereference valuestype 2

Related Experiment Videos

  • Insulin and glucose levels were measured to calculate HOMA and QUICKI indices.
  • A bootstrapping procedure with 1000 resamples was used to compute the variability of point estimates based on 1 to 45 samples.

    • Main Results:

    • Using a single sample, HOMA variability was 26.18% ± 4.31% and QUICKI variability was 3.30% ± 0.54%.
    • With 10 samples, variability decreased to 11.99% ± 2.22% for HOMA and 1.62% ± 0.31% for QUICKI.
    • Plasma insulin concentration oscillations were identified as the main cause of variability.

    Conclusions:

    • Significant biological variability exists in HOMA and QUICKI insulin sensitivity indices.
    • Increasing the number of insulin and glucose samples effectively reduces this variability.
    • Accurate assessment of insulin sensitivity requires consideration of measurement variability and potential oscillations in insulin levels.