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the claim

Insulin resistance can be accurately measured clinically

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Insulin resistance can be effectively and accurately assessed in clinical practice using established surrogate markers and indices derived from routine measurements, such as HOMA-IR and QUICKI.

The analysis

The retrieved literature consistently supports the claim that insulin resistance can be accurately evaluated using validated clinical surrogate markers (such as QUICKI, HOMA-IR, and the TyG index) which correlate well with gold-standard clamp techniques.

Evidence for · 4
Recorded source metadata

Arie Katz, Sridhar Nambi, Kieren J. Mather, Alain Baron, Dean Follmann, Gail W. Sullivan, Michael J. Quon. Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity In Humans. 2000. https://doi.org/10.1210/jcem.85.7.6661

The study validates the Quantitative Insulin Sensitivity Check Index (QUICKI) as a simple and accurate clinical method derived from fasting blood samples.

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More for · 3
Recorded source metadata

Bhawna Singh. Surrogate markers of insulin resistance: A review. 2010. https://doi.org/10.4239/wjd.v1.i2.36

The review outlines multiple surrogate markers and indices successfully employed to simplify and assess insulin resistance in clinical settings.

Recorded source metadata

Steven Stern, Ken Williams, Eleuterio Ferrannini, Ralph A. DeFronzo, Clifton Bogardus, Michael P. Stern. Identification of Individuals With Insulin Resistance Using Routine Clinical Measurements. 2005. https://doi.org/10.2337/diabetes.54.2.333

Research demonstrates that routine clinical measurements and decision rules can accurately identify insulin-resistant individuals.

Recorded source metadata

B. Adams-Huet, R. Zubirán, A. Remaley, I. Jialal. The triglyceride-glucose index is superior to homeostasis model assessment of insulin resistance in predicting metabolic syndrome in an adult population in the United States.. 2024. https://doi.org/10.1016/j.jacl.2024.04.130

The study highlights valid surrogate measures like the triglyceride-glucose index and HOMA-IR for predicting metabolic syndrome in adults.

The paper trail · every fact has a biography
first checked02 Aug 2026
judged → SUPPORTED · 9802 Aug 2026
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