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Cross-sectional study develops a probability score to assess insulin resistance in healthy individuals, suggesting potential for disease prevention.
CONTEXT: Insulin resistance (IR) can progress to type 2 diabetes. Therefore, timely identification of IR could facilitate disease prevention efforts. However, direct measurement of IR is not feasible in a clinical setting. OBJECTIVE: Develop a clinically practical probability score to assess IR in apparently healthy individuals based on levels of insulin, C-peptide, and other risk factors. DESIGN: Cross-sectional study. PARTICIPANTS: Apparently healthy individuals who volunteered to participate in studies of IR. MAIN OUTCOME MEASURE: IR, defined as the top tertile of steady-state plasma glucose during an insulin-suppression test. For an IR probability score based on a model that included insulin, C-peptide, creatinine, TG/HDL-C, and BMI, the odds ratio was 26.7 (95% CI 14.0 to 50.8) for those with scores >66% compared with those with scores <33%. When only insulin and C-peptide were included in the model, the odds ratio was 15.6 (95% CI 7.5 to 32.4) for those with scores >66% compared with those with scores <33%. CONCLUSIONS: An IR probability score based on insulin, C-peptide, creatinine, TG/HDL-C, and BMI or a score based on only insulin and C-peptide may help assess IR in apparently healthy individuals.
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Abbasi et al. (2018) studied this question.
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