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Czaja-Mitura I.,My Health Care | Merecz-Kot D.,University of Lodz | Szymczak W.,University of Lodz | Bortkiewicz A.,University of Lodz
Medycyna Pracy | Year: 2013

Background: Several studies have shown an association between work-related stress and risk factors for cardiovascular disease. However, only a few studies concerned the police. The aim of this study was to assess the relationship between the general and work-related stress, and the functioning of the circulatory system in the police staff. Material and Methods: The study group consisted of 126 policemen (aged 37.8±7.3 years), with average employment duration of 14.4±7 years. The study comprised the assessment of health status based on the medical examination and medical history of identified diseases, cardiovascular risk factors and symptoms, dietary habits, physical activity, intake of drugs, data on the family history, determinations of serum total cholesterol, HDL and LDL fractions, triglycerides, and fasting glycemia. The stress level was assessed using the Questionnaire for the Subjective Assessment of Work and Perceived Stress Scale. Results: On medical examination hypertension was found in 36% of the people under study. Chest discomfort was reported by 60% of the subjects. Average body mass index (BMI), serum cholesterol and LDL were elevated (22.7±4.1, 222.6±41.7 mg/dl and 142.7±39.7 mg/dl, respectively). Mean triglyceride, HDL fraction and fasting glucose levels were normal in the whole group. The levels of general and occupational stress were 34.9±4.8 and 128.0±33.3, respectively, being higher than in other occupational groups. In the group with the highest level of stress, there were significantly more people with circulatory problems (81%), drinking strong alcohol at least once a week (27%), working in a 3-shift system (40.5%) and working overtime (44%). Conclusions: The results show that the police are a group at high risk of developing cardiovascular diseases due to work-related stress. © Instytut Medycyny Pracy im. prof. J. Nofera w Łodzi. Source


The application of long-term blood pressure monitoring (ABPM) in the occupational medicine practice, its advantages and disadvantages and the diagnostic and prognostic values of the parameters determined during the test were reviewed. The circumstances (e.g., social meeting, phone call) in which blood pressure value significantly differs from its resting value were identified. The methodology and reference values of systolic and diastolic blood pressure proposed by the European Society of Hypertension and the European Society of Cardiology were discussed as well as the recommended values of the blood pressure load. The use of ABPM in the assessment of circadian blood pressure rhythm and the prognostic value of insufficient nocturnal drop (in non-dippers) or excessive nocturnal drop of ABP (in extreme dippers), and inverted circadian ABP variation (in reverse-dippers) was discussed. Attention was paid to the prognostic value of BP variability over short periods of time, which is specified in terms of standard deviation or coefficient of variance. This variability is considered as a factor capable of modifying the course, complications and prognosis of the hypertensive disease. The phenomena of "white coat hypertension" and masked hypertension were also described. It was demonstrated that the use of ABPM in occupational medicine is feasible, especially for preventive purposes, in workers exposed to different adverse work-related factors (noise, electromagnetic fields, shift work). © Instytut Medycyny Pracy im. prof. J. Nofera w Łodzi. Source


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 139.07K | Year: 2010

DESCRIPTION (provided by applicant): Dramatic growth of the senior population in the U.S. is widely expected to challenge the capacity of this segment of the U.S. health system. Alternative strategies to support seniors living independently will be critical in meeting the short fall. My Health Care Manager (MHCM) has developed the Senior Care Navigation System (SCANSTM) to provide decision support to Geriatric Care Managers (GCMs), registered nurses and social workers, in the construction of consumer-side care plans for seniors and their caregivers. SCANSTM provides interventions and practical, real-world tools to extend the healthy and active years of life and assist families with critical decisions. Automatic acquisition of knowledge will help to augment MHCM's research staff in order to keep the SCANSTM knowledge base up to date for providing effective and efficient senior care plans. The overall goal for this Fast-Track SBIR research will be for MHCM in collaboration with the Indiana University's School of Informatics to develop an automated knowledge acquisition system that will acquire knowledge from health literature pertinent to senior care. This knowledge in the form of best practices will be used as part of the SCANSTM decision support system. The automatic acquisition of knowledge will greatly increase the overall productivity of the SCANS Research Team. The improvements in quality, timeliness, breadth, depth, and volume of research will be a marketable feature of the SCANSTM product. During Phase I, MHCM will validate the feasibility of automatically acquiring knowledge in literature for senior care planning. MHCM will develop knowledge extraction methodologies for geriatric care in Phase I and will implement 3 of 40 MHCM defined care categories. Phase II will expand on the algorithm(s) developed during Phase I to include an additional 30-37 care categories. MCHM will also develop geriatric care intervention discovery algorithms to be used in finding, updating, and evaluating new knowledge to be included in the SCANSTM knowledgebase. MHCM will verify and validate the feasibility of the knowledge acquisition methods by comparing the current manual research process with an automated acquisition process using literature. MHCM will then augment the knowledge discovered through text mining with an existing Bayesian Reasoning Network model to make the SCANS TM an efficient decision support system for geriatric care. With the completion of Phases I and II, commercialization of the knowledge acquisition system for SCANSTM can then proceed in Phase III of the project. PUBLIC HEALTH RELEVANCE: The goal of this Fast-Track research application is to improve the quality, depth and breadth of research reference material held in the Senior Care Navigation System, SCANS, knowledgebase used by our Geriatric Care Managers. The knowledgebase helps our GCM's to prepare comprehensive care plans for elders and their care givers covering 40 care categories. The intent is to expand the knowledge of and coordinate the services available to seniors and their families for improving their quality of life and for extending independent living.


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 1.04M | Year: 2011

DESCRIPTION (provided by applicant): Dramatic growth of the senior population in the U.S. is widely expected to challenge the capacity of this segment of the U.S. health system. Alternative strategies to support seniors living independently will be critical in meeting the short fall. My Health Care Manager (MHCM) has developed the Senior Care Navigation System (SCANSTM) to provide decision support to Geriatric Care Managers (GCMs), registered nurses and social workers, in the construction of consumer-side care plans for seniors and their caregivers. SCANSTM provides interventions and practical, real-world tools to extend the healthy and active years of life and assist families with critical decisions. Automatic acquisition of knowledge will help to augment MHCM's research staff in order to keep the SCANSTM knowledge base up to date for providing effective and efficient senior care plans. The overall goal for this Fast-Track SBIR research will be for MHCM in collaboration with the Indiana University's School of Informatics to develop an automated knowledge acquisition system that will acquire knowledge from health literature pertinent to senior care. This knowledge in the form of best practices will be used as part of the SCANSTM decision support system. Theautomatic acquisition of knowledge will greatly increase the overall productivity of the SCANS Research Team. The improvements in quality, timeliness, breadth, depth, and volume of research will be a marketable feature of the SCANSTM product. During PhaseI, MHCM will validate the feasibility of automatically acquiring knowledge in literature for senior care planning. MHCM will develop knowledge extraction methodologies for geriatric care in Phase I and will implement 3 of 40 MHCM defined care categories. Phase II will expand on the algorithm(s) developed during Phase I to include an additional 30-37 care categories. MCHM will also develop geriatric care intervention discovery algorithms to be used in finding, updating, and evaluating new knowledge to be included in the SCANSTM knowledgebase. MHCM will verify and validate the feasibility of the knowledge acquisition methods by comparing the current manual research process with an automated acquisition process using literature. MHCM will then augment the knowledge discovered through text mining with an existing Bayesian Reasoning Network model to make the SCANS TM an efficient decision support system for geriatric care. With the completion of Phases I and II, commercialization of the knowledge acquisition system for SCANSTM can then proceed in Phase III of the project. PUBLIC HEALTH RELEVANCE: The goal of this Fast-Track research application is to improve the quality, depth and breadth of research reference material held in the Senior Care Navigation System, SCANS, knowledgebase used by our Geriatric Care Managers. The knowledgebase helps our GCM's to prepare comprehensive care plans for elders and their care givers covering 40 care categories. The intent is to expand the knowledge of and coordinate the services available to seniors and their families for improving their quality of life and for extending independent living.


Raghuram S.,Indiana University - Purdue University Indianapolis | Xia Y.,Indiana University - Purdue University Indianapolis | Ge J.,Indiana University - Purdue University Indianapolis | Palakal M.,Indiana University - Purdue University Indianapolis | And 5 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Bayesian network is a widely used tool for data analysis, modeling and decision support in various domains. There is a growing need for techniques and tools which can automatically construct Bayesian networks from massive text or literature data. In practice, Bayesian networks also need be updated when new data is observed, and literature mining is a very important source of new data after the initial network is constructed. Information closely related to Bayesian network usually includes the causal associations, statistics information and experimental results. However, these associations and numerical results cannot be directly integrated with the Bayesian network. The source of the literature and the perceived quality of research needs to be factored into the process of integration. In this demo, we will present a general methodology and toolkit called AutoBayesian that we developed to automatically build and update a Bayesian network based on the casual relationships derived from text mining. © 2011 Springer-Verlag. Source

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