Key result
Simultaneously optimized IVGTT designs were 1.9 and 7.1 times more efficient than standard rich and sparse designs, respectively, allowing for fewer samples and lower glucose/insulin input.
Why the study?
The insulin-modified intravenous glucose tolerance test for assessing insulin sensitivity and glucose effectiveness is laborious with an intense sampling schedule of up to 32 samples.
Effect estimate: 1.9 and 7.1 times more efficient
Optimized IVGTT designs can significantly reduce the number of blood samples and required sample size while maintaining efficiency in assessing insulin sensitivity and glucose effectiveness.
May ease IVGTT burden for SI/SG assessment; leaves open prospective validation before wider use.
The integrated minimal model allows assessment of clinical diagnosis indices, for example, insulin sensitivity (SI) and glucose effectiveness (SG), from data of the insulin‐modified intravenous glucose tolerance test (IVGTT), which is laborious with an intense sampling schedule, up to 32 samples. The aim of this study was to propose a more informative, although less laborious, IVGTT design to be used for model‐based assessment of SI and SG. The IVGTT design was optimized simultaneously for all design variables: glucose and insulin infusion doses, time of glucose dose and start of insulin infusion, insulin infusion duration, sampling times, and number of samples. Design efficiency was used to compare among different designs. The simultaneously optimized designs showed a profound higher efficiency than both standard rich (32 samples) and sparse (10 samples) designs. The optimized designs, after removing replicate sample times, were 1.9 and 7.1 times more efficient than the standard rich and sparse designs, respectively. After including practical aspects of the designs, for example, sufficient duration between samples and avoidance of prolonged hypoglycemia, we propose 2 practical designs with fewer sampling times and lower input of glucose and insulin than standard designs, constrained to prevent hypoglycemia. The optimized practical rich design is equally efficient in assessing SI and SG as the rich standard design, but with half the number of the samples, while the optimized practical sparse design has 1 less sample and requires 4.6 times fewer individuals for equal certainty when assessing SI and SG than the sparse standard design.
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Ibrahim et al. (2020) studied this question. Optimized IVGTT designs vs. Standard rich (32 samples) and sparse (10 samples) designs was evaluated on Design efficiency for assessing insulin sensitivity (SI) and glucose effectiveness (SG) (1.9 and 7.1 times more efficient). Simultaneously optimized IVGTT designs were 1.9 and 7.1 times more efficient than standard rich and sparse designs, respectively, allowing for fewer samples and lower glucose/insulin input.
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