Optimal management of elderly patients with glioblastoma.

Median age at diagnosis in patients with glioblastoma (GB) is slowly increasing with an aging population in Western countries, and was 64years in 2006. The number of patients age 65 and older with GB will double in 2030 compared with 2000. Survival in this older cohort of patients is significantly less than seen in younger patients. This may in part be related to more aggressive biology of tumor, reduced use of standard management approaches, increased toxicity of available therapies, and increased presence of comorbidities in this older patient population. Limited data do support the use of more extensive resection in these patients. Randomized data support the use of post-operative radiotherapy (RT) versus supportive care, but do not demonstrate a benefit for the use of the standard 6weeks course of RT over hypofractionated RT given over 3weeks. Preliminary data of randomized studies raise the possibility of temozolomide alone as an option for these patients. The use of 6weeks of RT with concurrent and adjuvant temozolomide has been associated with reasonably good survival in several uncontrolled small series of selected older patients; however, this better outcome may be related to the selection of better prognosis patients rather than the specific therapy utilized. The current National Cancer Institute of Canada (NCIC) and European Organization for Research and Treatment of Cancer (EORTC) CE.6/26062/22061 randomized study of short course RT with or without concurrent and adjuvant temozolomide will help determine the optimal therapy for this older cohort with currently available therapies.

Optimal management of microgrids

Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.. Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.

Réhabilitation améliorée après chirurgie--L'ere de la prise en charge optimale du patient chirurgical [Enhanced Recovery After Surgery--optimal management of the surgical patient].

Enhanced Recovery After Surgery (ERAS) is a multimodal, standardized and evidence-based perioperative care pathway. With ERAS, postoperative complications are significantly lowered, and, as a secondary effect, length of hospital stay and health cost are reduced. The patient recovers better and faster allowing to reduce in addition the workload of healthcare providers. Despite the hospital discharge occurs sooner, there is no increased charge of the outpatient care. ERAS can be safely applied to any patient by a tailored approach. The general practitioner plays an essential role in ERAS by assuring the continuity of the information and the follow-up of the patient.

Optimal management of natural resources. Accounting for heterogeneity

Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.

The Future REvascularization Evaluation in patients with Diabetes mellitus: Optimal management of Multivessel disease (FREEDOM) trial: Clinical and angiographic profile at study entry

Background The optimal revascularization strategy for diabetic patients with multivessel coronary artery disease (MVD) remains uncertain for lack of an adequately powered, randomized trial. The FREEDOM trial was designed to compare contemporary coronary artery bypass grafting (CABG) to percutaneous coronary intervention (PCI) with drug-eluting stents in diabetic patients with MVD against a background of optimal medical therapy. Methods A total of 1,900 diabetic participants with MVD were randomized to PCI or CABG worldwide from April 2005 to March 2010. FREEDOM is a superiority trial with a mean follow-up of 4.37 years (minimum 2 years) and 80% power to detect a 27.0% relative reduction. We present the baseline characteristics of patients screened and randomized, and provide a comparison with other MVD trials involving diabetic patients. Results The randomized cohort was 63.1 +/- 9.1 years old and 29% female, with a median diabetes duration of 10.2 +/- 8.9 years. Most (83%) had 3-vessel disease and on average took 5.5 +/- 1.7 vascular medications, with 32% on insulin therapy. Nearly all had hypertension and/or dyslipidemia, and 26% had a prior myocardial infarction. Mean hemoglobin A1c was 7.8 +/- 1.7 mg/dL, 29% had low-density lipoprotein <70 mg/dL, and mean systolic blood pressure was 134 +/- 20 mm Hg. The mean SYNTAX score was 26.2 with a symmetric distribution. FREEDOM trial participants have baseline characteristics similar to those of contemporary multivessel and diabetes trial cohorts. Conclusions The FREEDOM trial has successfully recruited a high-risk diabetic MVD cohort. Follow-up efforts include aggressive monitoring to optimize background risk factor control. FREEDOM will contribute significantly to the PCI versus CABG debate in diabetic patients with MVD. (Am Heart J 2012;164:591-9.)

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Hemiplegic shoulder pain: defining the problem and its management

Purpose: Hemiplegic shoulder pain can affect up to 70% of stroke patients and can have an adverse impact on rehabilitation outcomes. This article aims to review the literature on the suggested causes of hemiplegic shoulder pain and the therapeutic techniques that can be used to prevent or treat it. On the basis of this review, the components of an optimal management programme for hemiplegic shoulder pain are explored. Method: English language articles in the CINAHL and MEDLINE databases between 1990 and 2000 were reviewed. These were supplemented by citation tracking and manual searches. Results: A management programme for hemiplegic shoulder pain could comprise the following components: provision of an external support for the affected upper limb when the patient is seated, careful positioning in bed, daily static positional stretches, motor retraining and strapping of the scapula to maintain postural tone and symmetry. Conclusions: Research is required to evaluate the effectiveness of the components of the proposed management programme for the prevention and treatment of hemiplegic shoulder pain and to determine in what combination they achieve the best outcomes.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Prise en charge par le praticien des infections après transplantation d'organes solides [Management of infection after organ transplantation by the primary care physician]

The primary care physician is frequently consulted in first line for infectious complications in organ transplant recipients. Many infections without signs of severity can nowadays be managed on an outpatient basis. However, a number of clinical situations specific to transplant recipients may require special attention and knowledge. In particular, the general practitioner must be aware of the potential interactions between immunosuppressive and antimicrobial therapies, the risk of renal dysfunction as a consequence of diarrhea or urinary tract infection, and the diagnostic of CMV disease as a cause of fever without obvious source occurring several months after transplantation. Collaboration with the transplantation specialists is recommended in order to assure an optimal management of these patients.

European expert opinion on the management of invasive candidiasis in adults.

This report discusses the present status of antifungal therapy and treatment options for candidaemia, considered by experts in the field in Europe. A conference of 26 experts from 13 European countries was held to discuss strategies for the treatment and prevention of invasive candidiasis, with the aim of providing a review on optimal management strategies. Published and unpublished comparative trials on antifungal therapy were analysed and discussed. Commonly asked questions about the management of candidaemia were selected, and possible responses to these questions were discussed. Panellists were then asked to respond to each question by using a touchpad answering system. After the initial conference, the viewpoint document has been reviewed and edited to include new insights and developments since the initial meeting. For many situations, consensus on treatment could not be reached, and the responses indicate that treatment is likely to be modified on a patient-to-patient basis, depending on factors such as degree of illness, prior exposure to azole antifungals, and the presence of potentially antifungal drug-resistant Candida species.

Centralized IT management using SCCM in a large multinational company

Microsoft System Center Configuration Manager is a systems management product for managing large groups of computers and/or mobile devices. It provides operating system deployment, software distribution, patch management, hardware & software inventory, remote control and many other features for the managed clients. This thesis focuses on researching whether this product is suitable for large, international organization with no previous, centralized solution for managing all such networked devices and detecting areas, where the system can be altered to achieve a more optimal management product from the company’s perspective. The results showed that the system is suitable for such organization if properly configured and clear and transparent line of communication between key IT personnel exists.

Bridging Knowledge Gaps in the Management of Acute Coronary Syndromes

Contexte L’occlusion d’une artère du cœur cause un syndrome coronarien aigu (SCA) soit avec une élévation du segment ST (IAMEST) ou sans élévation du segment ST (1). Le traitement des patients avec un IAMEST requiert soit une intervention coronarienne d’urgence (ICP primaire) ou une thérapie fibrinolytique (FL). La thérapie FL peut être administrée soit dans un contexte pré-hospitalier (PHL) ou à l’hôpital. Une prise en charge précoce des patients avec SCA peut être améliorée par un simple indice de risque. Objectifs Les objectifs de cette thèse étaient de : 1) comparer l’ICP primaire et la thérapie FL (2); décrire plusieurs systèmes internationaux de PHL; (3) développer et valider un indice de risque simplifié pour une stratification précoce des patients avec SCA. Méthodes Nous complétons des méta-analyses, de type hiérarchique Bayésiennes portant sur l’effet de la randomisation, d’études randomisées et observationnelles; complétons également un sondage sur des systèmes internationaux de PHL; développons et validons un nouvel indice de risque pour ACS (le C-ACS). Résultats Dans les études observationnelles, l’ICP primaire, comparée à la thérapie FL, est associée à une plus grande réduction de la mortalité à court-terme; mais ce sans bénéfices concluants à long terme. La FL pré-hospitalière peut être administrée par des professionnels de la santé possédant diverses expertises. Le C-ACS a des bonnes propriétés discriminatoires et pourrait être utilisé dans la stratification des patients avec SCA. Conclusion Nous avons comblé plusieurs lacunes importantes au niveau de la connaissance actuelle. Cette thèse de doctorat contribuera à améliorer l’accès à des soins de qualité élevée pour les patients ayant un SCA.

Spatial-temporal aspects of cost-benefit analysis for park management: an example from Khao Yai National Park, Thailand

Using a model calibrated to Khao Yai National Park in Thailand, this paper highlights the importance of generating explicitly spatial and temporal data for developing management plans for tropical protected forests. Spatial and temporal cost-benefit analysis should account for the interactions between different land uses – such as the benefits of contiguous areas of preserved land and edge effects – and the realities of villagers living near forests who rely on extracted resources. By taking a temporal perspective, this paper provides a rare empirical assessment of the importance of quasi-option values when determining optimal management plans.

On Real-Time Monitoring And Control For Efficient Management Of Drinking Water Networks: Barcelona Case Study

Drinking water utilities in urban areas are focused on finding smart solutions facing new challenges in their real-time operation because of limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. Such challenges force water managers to monitor and control not only water supply and distribution, but also consumer demand. This paper presents and discusses novel methodologies and procedures towards an integrated water resource management system based on advanced ICT technologies of automation and telecommunications for largely improving the efficiency of drinking water networks (DWN) in terms of water use, energy consumption, water loss minimization, and water quality guarantees. In particular, the paper addresses the first results of the European project EFFINET (FP7-ICT2011-8-318556) devoted to the monitoring and control of the DWN in Barcelona (Spain). Results are split in two levels according to different management objectives: (i) the monitoring level is concerned with all the aspects involved in the observation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; (ii) the control level is concerned with computing the best suitable and admissible control strategies for network actuators as to optimize a given set of operational goals related to the performance of the overall system. This level covers the network control (optimal management of water and energy) and the demand management (smart metering, efficient supply). The consideration of the Barcelona DWN as the case study will allow to prove the general applicability of the proposed integrated ICT solutions and their effectiveness in the management of DWN, with considerable savings of electricity costs and reduced water loss while ensuring the high European standards of water quality to citizens.