BackgroundTreatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated with improved maternal and neonatal outcomes and requires intensive clinical input. This is currently achieved by hospital clinic attendance every 2 to 4 weeks with limited opportunity for intervention between these visits.ObjectiveWe conducted a randomized controlled trial to determine whether the use of a mobile phone-based real-time blood glucose management system to manage women with GDM remotely was as effective in controlling blood glucose as standard care through clinic attendance.MethodsWomen with an abnormal oral glucose tolerance test before 34 completed weeks of gestation were individually randomized to a mobile phone-based blood glucose management solution (GDm-health, the intervention) or routine clinic care. The primary outcome was change in mean blood glucose in each group from recruitment to delivery, calculated with adjustments made for number of blood glucose measurements, proportion of preprandial and postprandial readings, baseline characteristics, and length of time in the study.ResultsA total of 203 women were randomized. Blood glucose data were available for 98 intervention and 85 control women. There was no significant difference in rate of change of blood glucose (–0.16 mmol/L in the intervention and –0.14 mmol/L in the control group per 28 days, P=.78). Women using the intervention had higher satisfaction with care (P=.049). Preterm birth was less common in the intervention group (5/101, 5.0% vs 13/102, 12.7%; OR 0.36, 95% CI 0.12-1.01). There were fewer cesarean deliveries compared with vaginal deliveries in the intervention group (27/101, 26.7% vs 47/102, 46.1%, P=.005). Other glycemic, maternal, and neonatal outcomes were similar in both groups. The median time from recruitment to delivery was similar (intervention: 54 days; control: 49 days; P=.23). However, there were significantly more blood glucose readings in the intervention group (mean 3.80 [SD 1.80] and mean 2.63 [SD 1.71] readings per day in the intervention and control groups, respectively; P<.001). There was no significant difference in direct health care costs between the two groups, with a mean cost difference of the intervention group compared to control of –£1044 (95% CI –£2186 to £99). There were no unexpected adverse outcomes.ConclusionsRemote blood glucocse monitoring in women with GDM is safe. We demonstrated superior data capture using GDm-health. Although glycemic control and maternal and neonatal outcomes were similar, women preferred this model of care. Further studies are required to explore whether digital health solutions can promote desired self-management lifestyle behaviors and dietetic adherence, and influence maternal and neonatal outcomes. Digital blood glucose monitoring may provide a scalable, practical method to address the growing burden of GDM around the world.Trial RegistrationClinicalTrials.gov NCT01916694; https://clinicaltrials.gov/ct2/show/NCT01916694 (Archived by WebCite at http://www.webcitat...

Prevalence estimates for fragile X syndrome vary considerably. This systematic review and meta-analysis was conducted to provide an accurate prevalence estimate for this disorder using primary publications in PubMed, Embase, and the Cochrane library. Data were pooled using Bayesian fixed-effects and random-effects models. Primary analyses assessed the frequency of the full mutation and premutation in males and females in the total population (no bias against individuals with intellectual disability) and in female carriers of the premutation in normal populations (biased against individuals with intellectual disability), based on diagnosis by polymerase chain reaction or Southern blotting. A sensitivity analysis included studies using any diagnostic testing method and conference abstracts. Sixty-eight recorded observations provided data for the primary (56 observations) and sensitivity (12 observations) analysis. Using the random-effects model, frequency of the full mutation was 1.4 (95% CI: 0.1-3.1) per 10,000 males and 0.9 (95% CI: 0.0-2.9) per 10,000 females (1:7,143 and 1:11,111, respectively) in the total population. The premutation frequency was 11.7 (95% CI: 6.0-18.7) per 10,000 males and 34.4 (95% CI: 6.3-83.3) per 10,000 for females (1:855 and 1:291, respectively) in the total population. The prevalence of female carriers of the premutation in the normal population was 34.4 (95% CI: 8.9-60.3) per 10,000, or 1:291. Sensitivity analyses resulted in similar prevalence estimates but with wider heterogeneity. Prevalence estimates for the full mutation from this meta-analysis are lower than those in previous reviews of fragile X syndrome epidemiological data.

The authors' approach has higher MSE than the direct OLS approach but gives more descriptive data on domains of health effects. Further out of sample prediction work will help test the validity of these methods.

The EQ-5D-Y-3L is a generic, health-related, quality-of-life instrument for use in younger populations. Some methodological studies have explored the valuation of children's EQ-5D-Y-3L health states. There are currently no published value sets available for the EQ-5D-Y-3L that are appropriate for use in a cost-utility analysis. The aim of this article was to describe the development of the valuation protocol for the EQ-5D-Y-3L instrument. There were several research questions that needed to be answered to develop a valuation protocol for EQ-5D-Y-3L health states. Most important of these were: (1) Do we need to obtain separate values for the EQ-5D-Y-3L, or can we use the ones from the EQ-5D-3L? (2) Whose values should we elicit: children or adults? (3) Which valuation methods should be used to obtain values for child's health states that are anchored in Full health = 1 and Dead = 0? The EuroQol Research Foundation has pursued a research programme to provide insight into these questions. In this article, we summarized the results of the research programme concluding with the description of the features of the EQ-5D-Y-3L valuation protocol. The tasks included in the protocol for valuing EQ-5D-Y-3L health states are discrete choice experiments for obtaining the relative importance of dimensions/levels and composite time-tradeoff for anchoring the discrete choice experiment values on 1 = Full Health and 0 = Dead. This protocol is now available for use by research teams to generate EQ-5D-Y-3L value sets for their countries allowing the implementation of a cost-utility analysis for younger populations.

This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.