Matsuda index adjusted for sustained hyperglycemia via propensity scores outperforms homeostatic model assessment for insulin resistance in identifying insulin-requiring gestational diabetes mellitus.

Abstract

Background: Gestational diabetes mellitus, a glucose metabolism disorder during pregnancy, is linked to insulin resistance. Pregnancy elevates insulin resistance, and gestational diabetes mellitus increases fetal complication risks via excessive glucose transport. Current gestational diabetes mellitus diagnosis relies solely on blood glucose levels, which inadequately guide clinical management or insulin initiation. While homeostatic model assessment for insulin resistance and Matsuda index assess insulin resistance, their utility for insulin treatment evaluation in gestational diabetes mellitus is underexplored.

Objectives: Insulin resistance indices with enhanced discriminatory power for gestational diabetes mellitus were evaluated to predict insulin therapy during pregnancy in women suspected of gestational diabetes.

Design: This retrospective analysis utilized existing clinical data.

Methods: Clinical data from 383 pregnant women with suspected abnormal glucose metabolism at Tenshi Hospital (Jan 2018-Sep 2021) were analyzed. Gestational diabetes mellitus was diagnosed using 75-g oral glucose tolerance test criteria. Evaluations included blood glucose, insulin levels, homeostatic model assessment for insulin resistance, and Matsuda index. The primary outcome was predicting the need for insulin treatment. Statistical analyses involved receiver operating characteristic curves and propensity score adjustment.

Results: Body mass index, glycated hemoglobin, glucose/insulin levels, homeostatic model assessment for insulin resistance, quantitative insulin sensitivity check index, and Matsuda index differed between gestational diabetes mellitus and nongestational diabetes mellitus groups. Standalone Matsuda index (area under the curve = 0.714) outperformed homeostatic model assessment for insulin resistance (area under the curve = 0.618) for gestational diabetes mellitus discrimination; however, both exhibited poor model fit. Notably, the propensity score-adjusted composite Matsuda index (Matsuda index × BS₀ × BS₁₂₀) demonstrated superior performance for gestational diabetes mellitus diagnosis (area under the curve = 0.891) and for predicting insulin treatment (area under the curve = 0.785, lowest Bayesian information criterion, highest positive likelihood ratio), surpassing single indices and adjusted homeostatic model assessment for insulin resistance models.

Conclusions: The propensity score-adjusted Matsuda index for sustained hyperglycemia (Matsuda index × BS₀ × BS₁₂₀) excelled in gestational diabetes mellitus diagnosis and insulin therapy prediction. This adjusted index offers superior model fit and predictive accuracy, potentially guiding appropriate insulin treatment decisions in suspected gestational diabetes mellitus cases.

Trial registration: Tenshi Hospital Ethics Committee (approval number: 151; accepted on February 3, 2022).