Determination of server location in emergency care systems: an index proposal using data envelopment analysis and the hypercube queuing model.

The objective of this article is to propose a new composite index (CI) that helps to determine the most effective location of servers in an Emergency Care System (ECS), using Benefit of the Doubt (BoD)/Data Envelopment Analysis (DEA) and the Hypercube queuing model. The CI proposed was developed in four stages: (1) definition of a number of possible ECS configurations through the application of mathematical partitions and permutations; (2) application of the hypercube queuing model to determine performance parameters for each ECS configuration; (3) application of DEA/BoD to build the CI and generate performance rankings, and (4) evaluation of the rankings obtained to define the best configuration for the ECS analyzed. Data from two real cases from Brazil were used to assess the CI proposal. The results obtained confirm that: (a) the hypercube model could, relatively quickly, determine the configuration parameters generated; (b) the application of an appropriate DEA/BoD model enabled the different configurations to be ranked with good discrimination; (c) a pattern in the relationship between ambulance concentration and configuration effectiveness could be identified; and (d) the CI proposed would benefit ECS managers who are making resource location decisions.

A Meta-Analytic Framework for Developing Protocols to Attend Child and Adolescent Victims of Sexual Violence.

Violence against children and adolescents is a global public health problem. In Brazil, there are challenging boundaries for professionals in the protection network in general and for health professionals in particular. Moreover, among other factors, there is the challenge of referral, due to weaknesses in decision making, given the nature of sexual violence and how it is managed by healthcare services. This study aims to propose a Meta-Analytic framework to support the referral of young victims of sexual violence, considering levels of severity, independent of factors such as how protection systems are structured and managed and the local laws in force. We propose a Meta-Analytic approach, developed using the fundamentals of Delphi and DPSIR (Drivers, Pressures, State, Impact, and Response Model of Intervention), from the perspective of Value-Focused Thinking. The Delphi method was structured in two stages: the first stage aimed to identify and classify typical cases of sexual violence; the second stage used the DPSIR model, with the aim of identifying the decision criteria for typical cases that occur in a given municipality. The main outcomes are: (i) the application of the modified Delphi participatory method within the context of local social policies; (ii) the construction of a value tree based on Value-Focused Thinking; and (iii) the identification and systematization of criteria that most interfere with the evaluation of cases of sexual violence, which can be used for multi-criteria decision making.

Vascular endothelial growth factor (VEGF) and interleukin-1 receptor antagonist (IL-1Ra) as promising biomarkers for distinguishing active from latent tuberculosis in children and adolescents.

Since distinguishing pulmonary (PTB) from latent tuberculosis (LTBI) in pediatric patients remains a challenge, we aimed to investigate the efficacy of immune mediators in diagnosing PTB and LTBI in this population. In this cross-sectional study performed with children and adolescents, serum levels of 20 biomarkers were assessed and data were analyzed according to age groups. We included 65 participants (PTB, n = 28 and LTBI, n = 37). Overall, levels of TNF-α, IL-1Ra, IL-6, IL-17A, VEGF, MMP-1, and procalcitonin were significantly higher (P < 0.05) in adolescents and children <10 years-old with PTB. Also, principal component analysis (PCA) showed that immune mediators were able to distinguish PTB from LTBI. VEGF and IL-1Ra presented the highest area under the curve (AUC) values, both separately (AUC 0.890 and 0.785) and combined (AUC 0.99). Taken together, we showed that VEGF and IL-1Ra are promising biomarkers to distinguish PTB from LTBI in pediatric patients, especially in children <5 years-old.