Strengths and Limitations
This analysis has several strengths and limitations. Strengths include
the use of a rich set of covariates from the prenatal and early
postpartum period, including glucose metabolism values at 2 days
postpartum, robust methods including the use of a predictive modelling
algorithm to identify important predictors in the presence of a small
number of events and several collinear variables, internal validation
with k-fold cross validation, and calibration assessment of the final
model.22 In addition, we used multiple imputation to
address missing covariate data, which is often ubiquitous in routinely
collected clinical data.36 Limitations include the
fact that only 68% of women from the parent study (n=300) had glucose
metabolism assessed at 1 year postpartum and were included in the
present analysis, raising the possibility of selection bias. However, a
previous analysis of these data indicated that on average, women who
returned at 1 year postpartum were similar to women who did not across
measured covariates, with the exception of being more likely to be
privately insured.14 Women in the study were followed
for only 1 year postpartum, which is too short to evaluate type 2
diabetes as an outcome. Our analysis also included information on
race/ethnicity as a potential predictor of impaired glucose tolerance.
Type 2 diabetes is well known to have a genetic component37,38. However, race and ethnicity are not reliable
indicators of genetic differences.39 In this context,
race/ethnicity likely represent social rather than genetic differences.
We note the lack of additional covariates related to social
stratification (socioeconomic status, healthcare access, etc.) as a
limitation. Finally, in our calibration analysis we observed some
evidence of model overfitting in women in the highest two quartiles of
predicted risk, which may reflect the small sample size in our cohort
and indicates the need to validate these findings in larger cohorts of
women with GDM.