Pharmacokinetics and Pharmacodynamics of Human Regular U-500 Insulin Administered via Continuous Subcutaneous Insulin Infusion Versus Subcutaneous Injection in Adults With Type 2 Diabetes and High-Dose Insulin Requirements.

INTRODUCTION: Human regular U-500 insulin (U-500R) is approved for subcutaneous (SC) injection in patients with diabetes requiring >200 units/day of insulin. Here, pharmacokinetic and pharmacodynamic (PK/PD) profiles following U-500R administered by continuous subcutaneous insulin infusion (CSII) and SC injection in adults with type 2 diabetes (T2D) on high-dose insulin were studied. METHODS: In this randomized, crossover, euglycemic clamp study, patients received a 100-unit bolus of U-500R via SC injection or CSII with basal infusion using a U-500R specific pump. PK parameters were estimated using non-compartmental methods. PD estimates were derived from the glucose infusion rate during the euglycemic clamp procedure. RESULTS: When corrected for the basal infusion, the PK profiles for the 100-unit bolus of U-500R were similar for CSII and SC injection. Without correction for basal infusion, PK and PD profiles showed a greater insulin concentration and effect when U-500R was administered via CSII compared to SC injection, primarily due to basal insulin infusion for CSII. The ratio of geometric least squares AUC0-tlast means SC:CSII (90% CI) is 0.857 (0.729, 1.01) with correction (mean AUC0-tlast: 5230 pmol*L/h [SC injection] and 6070 pmol*L/h [CSII, with correction]) and 0.424 (0.361, 0.499) without correction (mean AUC0-tlast: 12300 pmol*L/h [CSII, without correction]). Median time-to-peak insulin concentration was six hours (range 0.5-8 hours) via SC injection and five hours (0.5-12 hours) via CSII. CONCLUSIONS: In adults with T2D on high-dose insulin, U-500R PK/PD parameters were similar for a 100-unit bolus when given by SC injection or CSII via a U-500R pump.

Identifying prediabetes using fasting insulin levels.

OBJECTIVE: To determine whether patients with prediabetes can be accurately and easily identified in clinical settings using a predictive clinical and laboratory model. METHODS: This retrospective study examined demographic and laboratory data from patients who had undergone 2-hour glucose testing for suspected prediabetes or diabetes between 2000 and 2004. Patients who met the diagnostic criteria for diabetes mellitus were excluded. Prediabetes was defined as a fasting glucose concentration > or = 100 mg/dL and < or = 125 mg/dL or a 2-hour postprandial glucose concentration > or = 140 mg/dL and < 200 mg/dL. Multivariate logistic regression was conducted to identify calculated or measured clinical and laboratory attributes that predict the presence of prediabetes, including fasting insulin quartiles, homeostasis model assessment of insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index. RESULTS: Of 965 patients, 287 (29.7%) had prediabetes. The study population primarily consisted of white, obese, female patients. A multivariate model revealed that compared with the referent lowest quartile of fasting insulin (mu = 4.9 [+/-SD] +/-1.2 microIU/mL), subsequent insulin quartiles increased the likelihood of identifying prediabetes (quartile 2: mu = 8.0 +/-0.8 microIU/mL, odds ratio [OR] = 2.076, confidence interval [CI] = 1.241-3.273; quartile 3: mu = 12.2 +/-1.7 microIU/mL, OR = 3.151, CI = 1.981-5.015; quartile 4: mu = 25.9 +/-12.4 microIU/mL, OR = 5.035, CI = 3.122-8.122). Older age and increased diastolic blood pressure also contributed modestly to this model. Further analysis using the area under the curve revealed that at a fasting insulin level > 9.0 microIU/mL, prediabetes would be correctly identified in 80% of affected patients. A second model revealed that increased HOMA-IR index (OR = 1.303, CI = 1.205-1.410) and older age (OR = 1.037, CI = 1.024-1.05) predicted prediabetes. CONCLUSIONS: The most robust model, which used fasting insulin levels, may provide the most utility as a clinical tool because the highest quartiles suggest significantly greater likelihood of identifying prediabetes.