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Insulin Resistance Probability Scores for Apparently Healthy Individuals
Fahim Abbasi1, Dov Shiffman2, Carmen H Tong2
1Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California.
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.
Results:
In a study of 535 participants, insulin, C-peptide, creatinine, body mass index (BMI), and triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) were independently associated with IR (all P < 0.05) in a model that included age, sex, ethnicity, BMI, blood pressure, insulin, C-peptide, fasting glucose, low-density lipoprotein cholesterol, TG/HDL-C, alanine aminotransferase, and creatinine. 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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