Baseline HbA1c to Identify High-Risk Gestational Diabetes: Utility in Early vs Standard Gestational Diabetes.

Context: The increasing prevalence of gestational diabetes mellitus (GDM) necessitates risk stratification directing limited antenatal resources to those at greatest risk. Recent evidence demonstrates that an early pregnancy glycated hemoglobin (HbA1c ≥5.9% (41 mmol/mol) predicts adverse pregnancy outcomes. Objective: To determine the optimal HbA1c threshold for adverse pregnancy outcomes in GDM in a treated multiethnic cohort and whether this differs in women diagnosed <24 vs ≥24 weeks' gestation (early vs standard GDM). Design and Setting: This was a retrospective cohort study undertaken at the Royal Prince Alfred Hospital Diabetes Antenatal Clinic, Australia, between 1991 and 2011. Patients and Interventions: Pregnant women (N = 3098) underwent an HbA1c (single-laboratory) measurement at the time of GDM diagnosis. Maternal clinical and pregnancy outcome data were collected prospectively. Main Outcome Measure: The association between baseline HbA1c and adverse pregnancy outcomes in early vs standard GDM. Results: HbA1c was measured at a median of 17.6 ± 3.3 weeks' gestation in early GDM (n = 844) and 29.4 ± 2.6 weeks' gestation in standard GDM (n = 2254). In standard GDM, HbA1c >5.9% (41 mmol/mol) was associated with the greatest risk of large-for-gestational-age (odds ratio [95% confidence interval] = 2.7 [1.5-4.9]), macrosomia (3.5 [1.4-8.6]), cesarean section (3.6 [2.1-6.2]), and hypertensive disorders (2.6 [1.1-5.8]). In early GDM, similar HbA1c associations were seen; however, lower HbA1c correlated with the greatest risk of small-for-gestational-age (P trend = 0.004) and prevalence of neonatal hypoglycemia. Conclusions: Baseline HbA1c >5.9% (41 mmol/mol) identifies an increased risk of large-for-gestational-age, macrosomia, cesarean section, and hypertensive disorders in standard GDM. Although similar associations are seen in early GDM, higher HbA1c levels do not adequately capture risk-limiting utility as a triage tool in this cohort.

HE4, CA125, the Risk of Malignancy Algorithm and the Risk of Malignancy Index and complex pelvic masses - a prospective comparison in the pre-operative evaluation of pelvic masses in an Australian population.

BACKGROUND: Human epididymis protein 4 (HE4) has been proposed as a novel biomarker for the diagnosis of epithelial ovarian cancer. Using HE4 and CA125, the risk of malignancy algorithm (ROMA) has been shown to be effective in the stratification of epithelial ovarian cancer risk. AIMS: To determine the effectiveness of HE4 and ROMA in the diagnosis of malignancy of women presenting with a complex pelvic mass in an Australian population and to compare it with CA125 and the risk of malignancy index (RMI). MATERIALS AND METHODS: Prospective recruitment of women was conducted between October 2012 and March 2014 (n = 50). CA125 and HE4 serum concentrations were collected and stored for subsequent analysis. Sensitivities, specificities, positive predictive values (PPV) and negative predictive values (NPV) were calculated for HE4, CA125, ROMA and the RMI. Receiver operating characteristic (ROC) area under the curves (AUC) were also calculated for comparison. RESULTS: There was a higher HE4 level in women with ovarian cancer compared with women with benign pathology (P = 0.008), and this observation was seen in benign versus stage 1 ovarian cancer women (P = 0.025). HE4 had a better specificity than CA125 for the diagnosis of ovarian cancer in all women (P = 0.022), and this effect was also observed in premenopausal women (P = 0.012). Furthermore, the ROC-AUC for HE4 was superior than CA125 in all women (P = 0.0451). The ROMA algorithm was not inferior to the RMI calculation in this population. CONCLUSIONS: In an Australian population, HE4 and ROMA are useful in the diagnosis of epithelial ovarian cancer.

Inhibin B levels in hypothyroid males.

BACKGROUND: The primary role of inhibin B is the regulation of gametogenesis via negative feedback on the production of follicle stimulating hormone (FSH) by the pituitary. METHODS: We studied 14 males with primary hypothyroidism due to various etiologies to determine if they exhibited hypogonadotrophic hypogonadism involving the reproductive segment of the gonadotrophic axis. Levels of inhibin B, FSH, luteinizing hormone, testosterone, free thyroxine, and thyrotropin were measured. RESULTS: The mean level of inhibin B in males with primary hypothyroidism was found to be approximately half that of normal males. The FSH level remained within the normal range and no reciprocal increase was observed as occurs in other conditions with reduced inhibin B. CONCLUSIONS: Our results indicate that primary hypothyroidism has a significant effect on inhibin B levels without reciprocal increase in FSH, which is consistent with a hypogonadotrophic hypogonadal state affecting the reproductive segment of the gonadotrophic axis.

Can common clinical parameters be used to identify patients who will need insulin treatment in gestational diabetes mellitus?

OBJECTIVE: To identify patients with gestational diabetes mellitus (GDM) who will need antenatal insulin treatment (AIT) by using a risk-prediction tool based on maternal clinical and biochemical characteristics at diagnosis. RESEARCH DESIGN AND METHODS: Data from 3,009 women attending the Royal Prince Alfred Hospital GDM Clinic, Australia, between 1995 and 2010 were studied. A risk engine was developed from significant factors identified for AIT using a logistic regression model. RESULTS: A total of 51% of GDM patients required AIT. Ethnicity, gestation at diagnosis, HbA(1c), fasting and 60-min glucose at oral glucose tolerance test, BMI, and diabetes family history were significant independent determinants of AIT. Notably, only 9% of the attributable risk for AIT can be explained by the clinical factors studied. A modeled risk-scoring system was therefore a poor predictor of AIT. CONCLUSIONS: Baseline maternal characteristics including HbA(1c) alone cannot predict the need for AIT in GDM. Lifestyle, compliance, or as yet unmeasured influences play a greater role in determining AIT.