A novel validated model for the prediction of insulin therapy initiation and adverse perinatal outcomes in women with gestational diabetes mellitus

Abstract

Aims/hypothesis Identifying women with gestational diabetes mellitus who are more likely to require insulin therapy vs medical nutrition therapy (MNT) alone would allow risk stratification and early triage to be incorporated into risk-based models of care. The aim of this study was to develop and validate a model to predict therapy type (MNT or MNT plus insulin [MNT+I]) for women with gestational diabetes mellitus (GDM). Methods Analysis was performed of de-identified prospectively collected data from women diagnosed with GDM by criteria in place since 1991 and formally adopted and promulgated as part of the more detailed 1998 Australasian Diabetes in Pregnancy Society management guidelines. Clinically relevant variables predictive of insulin therapy by univariate analysis were dichotomised and included in a multivariable regression model. The model was tested in a separate clinic population. Results In 3317 women, seven dichotomised significant independent predictors of insulin therapy were maternal age >30 years, family history of diabetes, pre-pregnancy obesity (BMI ≥30 kg/m 2 ), prior GDM, early diagnosis of GDM (<24 weeks gestation), fasting venous blood glucose level (≥5.3 mmol/l) and HbA 1c at GDM diagnosis ≥5.5% (≥37 mmol/mol). The requirement for MNT+I could be estimated according to the number of predictors present: 85.7-93.1% of women with 6-7 predictors required MNT+I compared with 9.3-14.7% of women with 0-1 predictors. This model predicted the likelihood of several adverse outcomes, including Caesarean delivery, early delivery, large for gestational age and an abnormal postpartum OGTT. The model was validated in a separate clinic population. Conclusions/interpretation This validated model has been shown to predict therapy type and the likelihood of several adverse perinatal outcomes in women with GDM.

Predictive factors of subsequent insulin requirement for glycemic control during pregnancy at diagnosis of gestational diabetes mellitus

“…Several studies have analyzed maternal characteristics (age, pre‐pregnancy BMI, ethnicity, or previous GDM) or biological parameters (FPG, HbA1c >5.4%, and elevated OGTT values) that should be associated with AIT . A large retrospective study analyzed outcomes according to pre‐pregnancy BMI categories (normal weight, overweight, and obese), and by diet or AIT and glycemic control .…”

“…In obese women with GDM, achievement of targeted levels of glycemia was associated with enhanced outcome only in women treated with insulin . Another large retrospective study in Australia with an ethnically diverse origin reported a model that correctly predicts AIT using seven dichotomized significant independent variables at diagnosis of GDM (age, pre‐pregnancy BMI, gestational age at diagnosis, FPG, HbA1c, family history of type 2 diabetes, and previous GDM) . The greater the number of predictors presented, the increased likelihood there was of requiring AIT …”

“…This allowed for standardized protocols to be followed, thus mitigating differences in outcomes due to variations in clinical practice. A retrospective observational study design is a limitation often observed in published studies about predictors of AIT at diagnosis of GDM . Our study was also important because it attempted to combine maternal characteristics and biological predictors of AIT for glycemic control to improve planning and resource utilization, and to identify high‐risk women with severe hyperglycemia requiring AIT.…”

“…Several studies have successfully identified one or more maternal characteristics or biochemical parameters at diagnosis of GDM that are associated with AIT . In a large retrospective study, Barnes et al .…”

“…Several studies have successfully identified one or more maternal characteristics or biochemical parameters at diagnosis of GDM that are associated with AIT. [5][6][7][8][9][10][11][12][13][14][15][16] In a large retrospective study, Barnes et al 15 successfully validated a model that predicts AIT using seven dichotomized independent variables at diagnosis of GDM (age, prepregnancy body mass index [BMI], gestational age at diagnosis, fasting plasma glucose [FPG], glycated hemoglobin [HbA1c] at diagnosis , family history of type 2 diabetes, and previous GDM). Early screening of these predictors may be important to identify high-risk women who require high priority in our perinatal center.…”