Prolactin-related adverse events and change in prolactin levels in pediatric patients given antipsychotics for schizophrenia and schizophrenia spectrum disorders: A systematic review

Abstract Background Second-generation antipsychotics are commonly prescribed for pediatric patients with schizophrenia and schizophrenia spectrum disorders despite their lack of approval for use in children. Although considered a safer alternative to first-generation antipsychotics, there is evidence to suggest that second-generation antipsychotics may be associated with some adverse events as well as an increase in prolactin levels. The purpose of this review is to examine the risk of prolactin-related adverse events in pediatric patients using antipsychotics and to quantify changes in prolactin for this population. Methods Literature searches were conducted in Medline, Embase, the Cochrane Central Register of Controlled Trials, and PsycINFO databases, supplemented with review of select gray literature to identify both randomized controlled trials and observational studies on pediatric patients prescribed antipsychotic medications for schizophrenia or schizophrenia spectrum disorders. Using a narrative approach, data on adverse events were recorded and changes from baseline in prolactin were pooled, where possible, from the randomized trials. Change from baseline in prolactin was evaluated for each treatment, as well as in comparison to placebo and to other treatments. Where data was available, these changes were evaluated separately for male and female patients. Results Six randomized controlled trials and five observational studies, all examining the effects of second-generation antipsychotics, were selected. Literature reporting the effects of risperidone, quetiapine, aripiprazole, olanzapine, and paliperidone was identified, with varying doses. Prolactin-related adverse events were sparsely reported across studies. In evidence gathered from randomized controlled trials, risperidone, olanzapine, and two doses of paliperidone (3–5 mg/day and 6–12 mg/day) were associated with increased prolactin levels compared to baseline. With the exception of paliperidone, similar trends were observed in males and females, separately. The findings of the observational evidence served to both complement and run contrary to the randomized trials, with discrepancies attributed to differences in patient and treatment characteristics. Conclusions No definitive conclusions between second-generation antipsychotic use and prolactin-related adverse events can be made based on the available literature. While some trends in prolactin level changes emerged, this was based on few trials with small sample sizes. Future investigations should emphasize reporting on treatment safety. Trial registration PROSPERO CRD42014009506

Additional file 1: of Prolactin-related adverse events and change in prolactin levels in pediatric patients given antipsychotics for schizophrenia and schizophrenia spectrum disorders: A systematic review

Figure S1. Evaluation of RCTs with the Cochrane risk of bias assessment. (PDF 267 kb

Cardiovascular events and all-cause mortality associated with sulphonylureas compared with other antihyperglycaemic drugs: a Bayesian meta-analysis of survival data

Aim: To conduct a systematic review and meta-analysis to determine the risk of cardiovascular events and all-cause mortality associated with sulphonylureas (SUs) vs other glucose lowering drugs in patients with T2DM (T2DM. Materials and methods: A systematic review of Medline, Embase, Cochrane and clinicaltrials.gov was conducted for studies comparing SUs with placebo or other antihyperglycaemic drugs in patients with T2DM. A cloglog model was used in the Bayesian framework to obtain comparative hazard ratios (HRs) for the different interventions. For the analysis of observational data, conventional fixed-effect pairwise meta-analyses were used. Results: The systematic review identified 82 randomized controlled trials (RCTs) and 26 observational studies. Meta-analyses of RCT data showed an increased risk of all-cause mortality and cardiovascular-related mortality for SUs compared with all other treatments combined (HR 1.26, 95% confidence interval [CI] 1.10-1.44 and HR 1.46, 95% CI 1.21-1.77, respectively). The risk of myocardial infarction was significantly higher for SUs compared with dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium-glucose co-transporter-2 inhibitors (HR 2.54, 95% CI 1.14-6.57 and HR 41.80, 95% CI 1.64-360.4, respectively). The risk of stroke was significantly higher for SUs than for DPP-4 inhibitors, glucagon-like peptide-1 agonists, thiazolidinediones and insulin. Conclusions: The present meta-analysis showed an association between SU therapy and a higher risk of major cardiovascular disease-related events compared with other glucose lowering drugs. Results of ongoing RCTs, which should be available in 2018, will provide definitive results on the risk of cardiovascular events and all-cause mortality associated with SUs vs other antihyperglycaemic drugs

D4.1 – AI-BASED DATA OPERATIONS V1

<p>This is the first of the series of deliverables related to the activities of WP4 ("AI-based Data Management for Green Data Operations"). Following the MobiSpaces Reference Architecture defined under the scope of T2.1 ("Design of Reference Architecture") and its current release reported in D2.1 ("Conceptual Model & Reference Architecture v1"), this document gives more details about one of the major architectural pillars, the AI-based Data Operations Toolbox. </p><p>The overall activities conducted under the scope of WP4 ("AI-based Data Management for Green Data Operations") that are being reported in this document, mostly focus on this particular pillar, with the exception of the T4.4 ("Privacy-driven Data Aggregation"). The latter is considered as part of the Trustworthy Data Governance Services, however, the progress of this task is reported in these series of deliverables that summarize the activities of the whole WP4. In this document, we present the individual software components that are part of the AI-based Data Operations Toolbox, we give details of their interactions, the background technologies that these components are currently being built upon, along with more detailed description of their internal building blocks. </p><p>WP4 focuses on both the data management aspects of MobiSpaces and the data operations of the platform in terms of automating the definition of AI workflows in a declarative manner and their corresponding runtime deployment and orchestration of their entire data lifecycle. The first category of components consists of the Data Management Toolset of the integrated solution that offers a variety of different but complementary data management systems to be exploited by the data users and application developers. For the second category of components, we provide the tools and algorithms for automating the definition and execution of complex AI workflows, consuming data from the aforementioned Data Management Toolset in a transparent manner. The target objective is to execute these workflows in an energy efficient manner, using our novel resource allocator to reduce the carbon emission. </p><p>The duration of WP4 spans from M04 to M34. This deliverable reports the work that has been conducted until M10, which accomplishes the milestone MS04 ("Software prototypes - Iteration I"). At this phase of the project, we have identified the internal building blocks of the AI-based Data Operations Toolbox, the details of their interactions and we have delivered the first release of the corresponding prototypes. In this report our primary focus is on the individual evaluation of the components, while D2.7 ("AI-based Data Operations Toolbox v1") will later focus on the integrated solution based on our prototypes described here, to be evaluated by the project's use cases. Given the different maturity levels of the different components in WP4 at this moment, in this document we either provide some initial evaluation results or a concrete plan for evaluation that will be followed during the next period. Two additional versions are planned to be submitted in M22 and M34, where the second and third release of the prototypes will be available, giving more details of the implementation and final evaluation, implementing all target objectives of the WP4. </p&gt