Precision and accuracy of hyperglycemic clamps in a multicenter study

Abstract

Application of glucose clamp methodologies in multicenter studies brings challenges for standardization. The Restoring Insulin Secretion (RISE) Consortium implemented a hyperglycemic clamp protocol across seven centers using a combination of technical and management approaches to achieve standardization. Two-stage hyperglycemic clamps with glucose targets of 200 mg/dL and >450 mg/dL were performed utilizing a centralized spreadsheet-based algorithm that guided dextrose infusion rates using bedside plasma glucose measurements. Clamp operators received initial and repeated training with ongoing feedback based on surveillance of clamp performance. The precision and accuracy of the achieved stage-specific glucose targets were evaluated, including differences by study center. We also evaluated robustness of the method to baseline physiologic differences and on-study treatment effects. The RISE approach produced high overall precision (3%–9% variance in achieved plasma glucose from target at various times across the procedure) and accuracy (SD < 10% overall). Statistically significant but numerically small differences in achieved target glucose concentrations were observed across study centers, within the magnitude of the observed technical variability. Variation of the achieved target glucose over time in placebo-treated individuals was low (<3% variation), and the method was robust to differences in baseline physiology (youth vs. adult, IGT vs. diabetes status) and differences in physiology induced by study treatments. The RISE approach to standardization of the hyperglycemic clamp methodology across multiple study centers produced technically excellent standardization of achieved glucose concentrations. This approach provides a reliable method for implementing glucose clamp methodology across multiple study centers.

NEW & NOTEWORTHY: The Restoring Insulin Secretion (RISE) study centers undertook hyperglycemic clamps using a simplified methodology and a decision guidance algorithm implemented in an easy-to-use spreadsheet. This approach, combined with active management including ongoing central data surveillance and routine feedback to study centers, produced technically excellent standardization of achieved glucose concentrations on repeat studies within and across study centers.