Diabetes primary prevention program: new insights from data analysis of recruitment period

Primary Prevention of Diabetes Program in Buenos Aires Province evaluates the effectiveness of adopting healthy lifestyle to prevent type 2 diabetes (T2D) in people at high risk of developing it. We aimed to present preliminary data analysis of FINDRISC and laboratory measurements taken during recruitment of people for the Primary Prevention of Diabetes Program in Buenos Aires Province in the cities of La Plata, Berisso, and Ensenada, Argentina.Fil: Gagliardino, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Elgart, Jorge Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Bourgeois, Marcelo Javier. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro Interdisc.universitario Para la Salud; ArgentinaFil: Etchegoyen, Graciela Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Fantuzzi, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ré, Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ricart, Juan P.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: García, Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Giampieri, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Gonzalez, Lorena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Suárez Crivaro, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Kronsbein, Peter. Niederrhein University of Applied Sciences Mönchengladbach; AlemaniaFil: Angelini, Julieta M.. Universidad Nacional de La Plata; ArgentinaFil: Martinez, Camilo. Universidad Nacional de La Plata; ArgentinaFil: Martinez, Jorge. Universidad Nacional de La Plata; ArgentinaFil: Ricart, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Humanidades y Ciencias Sociales. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales; ArgentinaFil: Spinedi, Eduardo Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; Argentin

Inventory drivers in a pharmaceutical supply chain

In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

Optimizing the assessment of suicidal behavior: the application of curtailment techniques

Background: Given their length, commonly used scales to assess suicide risk, such as the Beck Scale for Suicide Ideation (SSI) are of limited use as screening tools. In the current study we tested whether deterministic and stochastic curtailment can be applied to shorten the 19-item SSI, without compromising its accuracy. Methods: Data from 366 patients, who were seen by a liaison psychiatry service in a general hospital in Scotland after a suicide attempt, were used. Within 24 h of admission, the SSI was administered; 15 months later, it was determined whether a patient was re-admitted to a hospital as the result of another suicide attempt. We fitted a Receiver Operating Characteristic curve to derive the best cut-off value of the SSI for predicting future suicidal behavior. Using this cut-off, both deterministic and stochastic curtailment were simulated on the item score patterns of the SSI. Results: A cut-off value of SSI≥6 provided the best classification accuracy for future suicidal behavior. Using this cut-off, we found that both deterministic and stochastic curtailment reduce the length of the SSI, without reducing the accuracy of the final classification decision. With stochastic curtailment, on average, less than 8 items are needed to assess whether administration of the full-length test will result in an SSI score below or above the cut-off value of 6. Limitations: New studies using other datasets should re-validate the optimal cut-off for risk of repeated suicidal behavior after being treated in a hospital following an attempt. Conclusions: Curtailment can be used to simplify the assessment of suicidal behavior, and should be considered as an alternative to the full scale

Stakeholders' perceptions of rehabilitation services for individuals living with disability:A survey study

Background: The World Health Organization (WHO) was tasked with developing health system guidelines for the implementation of rehabilitation services. Stakeholders' perceptions are an essential factor to take into account in the guideline development process. The aim of this study was to assess stakeholders' perceived feasibility and acceptability of eighteen rehabilitation services and the values they attach to ten rehabilitation outcomes.   Methods: We disseminated an online self-administered questionnaire through a number of international and regional organizations from the different WHO regions. Eligible individuals included persons with disability, caregivers of persons with disability, health professionals, administrators and policy makers. The answer options consisted of a 9-point Likert scale.   Results: Two hundred fifty three stakeholders participated. The majority of participants were health professional (64 %). In terms of outcomes, 'Increasing access' and 'Optimizing utilization' were the top service outcomes rated as critical (i.e., 7, 8 or 9 on the Likert scale) by >70 % of respondents. 'Fewer hospital admissions', 'Decreased burden of care' and 'Increasing longevity' were the services rated as least critical (57 %, 63 % and 58 % respectively). In terms of services, 'Community based rehabilitation' and 'Home based rehabilitation' were found to be both definitely feasible and acceptable (75 % and 74 % respectively). 'Integrated and decentralized rehabilitation services' was found to be less feasible than acceptable according to stakeholders (61 % and 71 % respectively). As for 'Task shifting', most stakeholders did not appear to find task shifting as either definitely feasible or definitely acceptable (63 % and 64 % respectively).   Conclusion: The majority of stakeholder's perceived 'Increasing access' and 'Optimizing utilization' as most critical amongst rehabilitation outcomes. The feasibility of the 'Integrated and decentralized rehabilitation services' was perceived to be less than their acceptability. The majority of stakeholders found 'Task shifting' as neither feasible nor acceptable

Observer-biased bearing condition monitoring: from fault detection to multi-fault classification

Bearings are simultaneously a fundamental component and one of the principal causes of failure in rotary machinery. The work focuses on the employment of fuzzy clustering for bearing condition monitoring, i.e., fault detection and classification. The output of a clustering algorithm is a data partition (a set of clusters) which is merely a hypothesis on the structure of the data. This hypothesis requires validation by domain experts. In general, clustering algorithms allow a limited usage of domain knowledge on the cluster formation process. In this study, a novel method allowing for interactive clustering in bearing fault diagnosis is proposed. The method resorts to shrinkage to generalize an otherwise unbiased clustering algorithm into a biased one. In this way, the method provides a natural and intuitive way to control the cluster formation process, allowing for the employment of domain knowledge to guiding it. The domain expert can select a desirable level of granularity ranging from fault detection to classification of a variable number of faults and can select a specific region of the feature space for detailed analysis. Moreover, experimental results under realistic conditions show that the adopted algorithm outperforms the corresponding unbiased algorithm (fuzzy c-means) which is being widely used in this type of problems. (C) 2016 Elsevier Ltd. All rights reserved.Grant number: 145602