Ventilator-associated pneumonia in neurocritically ill patients: insights from the ENIO international prospective observational study.

BACKGROUND: Acute brain injured (ABI) patients are at high risk of developing ventilator-associated pneumonia (VAP). However, incidence, risk factors and effects on outcome of VAP are not completely elucidated in this population. The primary aim of this study was to determine the incidence of VAP in a cohort of ABI patients. The secondary objectives included the identification of risk factors for development of VAP, and the impact of VAP on clinical outcomes. Clinical outcomes were defined as intensive care unit length of stay (ICU-LOS), duration of invasive mechanical ventilation (IMV), and ICU mortality. METHODS: Pre-planned sub-analysis of the Extubation strategies in Neuro-Intensive care unit (ICU) patients and associations with Outcomes (ENIO) international multi-center prospective observational study. Patients with available data on VAP, who received at least 48 h of IMV and ICU-LOS ≥ 72 h were included. RESULTS: Out of 1512 patients included in the ENIO study, 1285 were eligible for this analysis. The prevalence of VAP was 39.5% (33.7 cases /1000 ventilator-days), with a high heterogeneity across countries and according to the type of brain injury. VAP was significantly more frequent in male patients, in those with smoke habits and when intraparenchymal probe (IP), external ventricular drain (EVD) or hypothermia (p < 0.001) were used. Independent risk factors for VAP occurrence were male gender, the use of IP, hypothermia, and the occurrence of tracheobronchitis during ICU stay. VAP was not an independent risk factor for ICU mortality (Hazard Ratio, HR = 0.71 95%CI 0.43-1.16, p = 0.168), but was independently associated with longer ICU stay (OR = 2.55 95%CI 2.01-3.23, p < 0.001). CONCLUSIONS: VAP is common in ABI patients. Male gender, IP and EVD insertion, tracheobronchitis, and the use of therapeutic hypothermia were significantly associated with VAP occurrence. VAP did not affect mortality but increased ICU-LOS.

An algorithm for the optimal collection of wet waste.

This work refers to the development of an approach for planning wet waste (food waste and other) collection at a metropolitan scale. Some specific modeling features distinguish this specific waste collection problem from the other ones. For instance, there may be significant differences as regards the values of the parameters (such as weight and volume) characterizing the various collection points. As it happens for classical waste collection planning, even in the case of wet waste, one has to deal with difficult combinatorial problems, where the determination of an optimal solution may require a very large computational effort, in the case of problem instances having a noticeable dimensionality. For this reason, in this work, a heuristic procedure for the optimal planning of wet waste is developed and applied to problem instances drawn from a real case study. The performances that can be obtained by applying such a procedure are evaluated by a comparison with those obtainable via a general-purpose mathematical programming software package, as well as those obtained by applying very simple decision rules commonly used in practice. The considered case study consists in an area corresponding to the historical center of the Municipality of Genoa.

A dynamic optimization model for solid waste recycling.

Recycling is an important part of waste management (that includes different kinds of issues: environmental, technological, economic, legislative, social, etc.). Differently from many works in literature, this paper is focused on recycling management and on the dynamic optimization of materials collection. The developed dynamic decision model is characterized by state variables, corresponding to the quantity of waste in each bin per each day, and control variables determining the quantity of material that is collected in the area each day and the routes for collecting vehicles. The objective function minimizes the sum of costs minus benefits. The developed decision model is integrated in a GIS-based Decision Support System (DSS). A case study related to the Cogoleto municipality is presented to show the effectiveness of the proposed model. From optimal results, it has been found that the net benefits of the optimized collection are about 2.5 times greater than the estimated current policy.

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).