HOMA-IR Calculator — Insulin Resistance
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Metabolic measurements can look deceptively simple on a report. HOMA-IR Calculator — Insulin Resistance shows the arithmetic behind one specific interpretation without pretending to replace clinical context.
What this calculator does
HOMA-IR is a research and clinical estimate of insulin resistance derived from fasting glucose and fasting insulin. This calculator also shows QUICKI so the same two laboratory values can be viewed through two commonly used surrogate indices. Metabolic calculations can add context to measurements, but laboratory timing, assay methods, medications, and the clinical situation can change what the result means.
How to use it
Enter or select Fasting glucose and Fasting insulin. Use the units offered by the calculator and keep measurements consistent when you plan to compare results over time.
How the calculation works
With glucose entered in mg/dL, HOMA-IR = fasting glucose × fasting insulin ÷ 405. QUICKI is calculated as 1 ÷ [log10(fasting insulin) + log10(fasting glucose)]. The calculator converts supported glucose units as needed.
Example
For the sample values prefilled in this calculator, the primary result is 1.877 (HOMA-IR) and QUICKI is 0.3471. This example is there to show how the inputs flow through the implemented equation; replace the sample values with your own measurements before using the result.
How to interpret the result
Higher HOMA-IR generally corresponds to greater insulin resistance within a given population, while QUICKI moves in the opposite direction. There is no single universal cutoff that applies to every laboratory, age group, ethnicity, or clinical purpose.
Limitations and notes
Both indices depend on a true fasting sample and stable insulin/glucose physiology. Assay methods, medications, acute illness, diabetes severity, and population differences can affect interpretation. They are surrogate measures and do not replace a clinician’s diagnostic evaluation or reference methods such as clamp studies. When laboratory values are involved, use results from the same units and note whether the sample was fasting or taken under other specified conditions. A mathematically correct result can still be clinically misleading when the underlying test or timing is inappropriate.
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