External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study

OBJECTIVE To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. DESIGN External validation of all published prognostic models in large scale, prospective, multicentre cohort study. SETTING 31 independent midwifery practices and six hospitals in the Netherlands. PARTICIPANTS Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded. MAIN OUTCOME MEASURES Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots. RESULTS 3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit. CONCLUSIONS In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact

Potential of DIVA vaccines for Fish

The expanding aquaculture industry continues to encounter major challenges from highly contagious viruses. Control and eradication measures for lethal and economically damaging notifiable viral diseases involve &lsquo;stamping out&rsquo; policies and surveillance strategies. Mass-culling of stock and restricted movement of fish and fish products, used to control the spread of notifiable diseases, has considerable impacts on the trade of fish products. Although effective, these measures are expensive and ethically complex and could possibly be reduced by emulating innovative vaccination strategies used by the terrestrial livestock industry. DIVA (differentiating infected from vaccinated animal) strategies provide a basis to vaccinate and contain disease outbreaks without compromising &lsquo;disease-free&rsquo; status, as antibodies induced during infection can be used to distinguish from those induced by vaccination. The potential and feasibility of DIVA vaccination in aquaculture is explored here with reference to DIVA strategies applied in higher vertebrates. Three economically important notifiable viruses, causing major problems in three different cultured fish industries, are considered. The increased availability and application of sophisticated biotechnology tools has enabled improved prophylaxis and serological diagnosis for control of viral haemorrhagic septicaemia in rainbow trout, infectious salmon anaemia in Atlantic salmon and koi herpesvirus disease in carp. Improving the specificity of serological diagnostics in aquaculture in conjunction with suitable vaccines could enable the application of DIVA strategies, but the immunological variation between different fish species and contrasting pathobiological characteristics of different viruses determines the feasibility and potential of such DIVA approaches for aquaculture industries