Interprofessional Faculty Development: Integration of Oral Health into the Geriatric Diabetes Curriculum, from Theory to Practice.

Georgia Dounis,1 Marcia Ditmyer,2 Susan VanBeuge,3 Sue Schuerman,4 Mildred McClain,1 Kiki Dounis,1,5 Connie Mobley21Department of Clinical Sciences, 2Department of Biomedical Sciences, 3Department of Physiological Nursing, 4Department of Physical Therapy, University of Nevada Las Vegas School of Dental Medicine, Las Vegas, NV, USA; 5Department of Family Medicine, University of Nevada School of Medicine, Reno, NV, USABackground: Health care workforce shortages and an increase demand for health care services by an older demographic challenged by oral–systemic conditions are being recognized across health care systems. Demands are placed on health care professionals to render coordinated delivery of services. Management of oral–systemic conditions requires a trained health care workforce to render interprofessional patient-centered and coordinated delivery of health care services. The purpose of this investigation was to evaluate the effectiveness of an interprofessional health care faculty training program.Methods: A statewide comprehensive type 2 diabetes training program was developed and offered to multidisciplinary health care faculty using innovative educational methods. Video-recorded clinically simulated patient encounters concentrated on the oral–systemic interactions between type 2 diabetes and comorbidities. Post-encounter instructors facilitated debriefing focused on preconceptions, self-assessment, and peer discussions, to develop a joint interprofessional care plan. Furthermore, the health care faculty explored nonhierarchical opportunities to bridge common health care themes and concepts, as well as opportunities to translate information into classroom instruction and patient care.Results: Thirty-six health care faculty from six disciplines completed the pre-research and post-research assessment survey to evaluate attitudes, knowledge, and perceptions following the interprofessional health care faculty training program. Post-training interprofessional team building knowledge improved significantly. The health care faculty post-training attitude scores improved significantly, with heightened awareness of the unique oral–systemic care needs of older adults with type 2 diabetes, supporting an interprofessional team approach to care management. In addition, the health care faculty viewed communication across disciplines as being essential and interprofessional training as being vital to the core curriculum of each discipline. Significant improvement occurred in the perception survey items for team accountability and use of uniform terminology to bridge communication gaps.Conclusion: Attitude, knowledge, and perceptions of health care faculty regarding interprofessional team building and the team approach to management of the oral–systemic manifestations of chronic disease in older adults was improved. Uniform language to promote communication across health professionals, care settings, and caregivers/patients, was noted. Interprofessional team building/care planning should be integrated in core curricula.Keywords: team building, patient-centered care, oral–systemic, older adult

Statistical properties of microcracking in polyurethane foams under tensile test, influence of temperature and density

We report tensile failure experiments on polyurethane (PU) foams. Experiments have been performed by imposing a constant strain rate. We work on heterogeneous materials for whom the failure does not occur suddenly and can develop as a multistep process through a succession of microcracks that end at pores. The acoustic energy and the waiting times between acoustic events follow power-law distributions. This remains true while the foam density is varied. However, experiments at low temperatures (PU foams more brittle) have not yielded power-laws for the waiting times. The cumulative acoustic energy has no power law divergence at the proximity of the failure point which is qualitatively in agreement with other experiments done at imposed strain. We notice a plateau in cumulative acoustic energy that seems to occur when a single crack starts to propagate

Validation of a multifactorial risk factor model used for predicting future caries risk with nevada adolescents

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting.</p> <p>Methods</p> <p>This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model.</p> <p>Results</p> <p>Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%.</p> <p>Conclusions</p> <p>Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.</p

A case-control study of determinants for high and low dental caries prevalence in Nevada youth

<p>Abstract</p> <p>Background</p> <p>The main purpose of this study was to compare the 30% of Nevada Youth who presented with the highest Decayed Missing and Filled Teeth (DMFT) index to a cohort who were caries free and to national NHANES data. Secondly, to explore the factors associated with higher caries prevalence in those with the highest DMFT scores compared to the caries-free group.</p> <p>Methods</p> <p>Over 4000 adolescents between ages 12 and 19 (Case Group: N = 2124; Control Group: N = 2045) received oral health screenings conducted in public/private middle and high schools in Nevada in 2008/2009 academic year. Caries prevalence was computed (Untreated decay scores [D-Score] and DMFT scores) for the 30% of Nevada Youth who presented with the highest DMFT score (case group) and compared to the control group (caries-free) and to national averages. Bivariate and multivariate logistic regression was used to analyze the relationship between selected variables and caries prevalence.</p> <p>Results</p> <p>A majority of the sample was non-Hispanic (62%), non-smokers (80%), and had dental insurance (70%). With the exception of gender, significant differences in mean D-scores were found in seven of the eight variables. All variables produced significant differences between the case and control groups in mean DMFT Scores. With the exception of smoking status, there were significant differences in seven of the eight variables in the bivariate logistic regression. All of the independent variables remained in the multivariate logistic regression model contributing significantly to over 40% of the variation in the increased DMFT status. The strongest predictors for the high DMFT status were racial background, age, fluoridated community, and applied sealants respectively. Gender, second hand smoke, insurance status, and tobacco use were significant, but to a lesser extent.</p> <p>Conclusions</p> <p>Findings from this study will aid in creating educational programs and other primary and secondary interventions to help promote oral health for Nevada youth, especially focusing on the subgroup that presents with the highest mean DMFT scores.</p

Impact of Diabetes on Postinfarction Heart Failure and Left Ventricular Remodeling

Diabetes mellitus, the metabolic syndrome, and the underlying insulin resistance are increasingly associated with diastolic dysfunction and reduced stress tolerance. The poor prognosis associated with heart failure in patients with diabetes after myocardial infarction is likely attributable to many factors, important among which is the metabolic impact from insulin resistance and hyperglycemia on the regulation of microvascular perfusion and energy generation in the cardiac myocyte. This review summarizes epidemiologic, pathophysiologic, diagnostic, and therapeutic data related to diabetes and heart failure in acute myocardial infarction and discusses novel perceptions and strategies that hold promise for the future and deserve further investigation

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

Diastolic dysfunction in diabetes and the metabolic syndrome: promising potential for diagnosis and prognosis

Cardiac disease in diabetes mellitus and in the metabolic syndrome consists of both vascular and myocardial abnormalities. The latter are characterised predominantly by diastolic dysfunction, which has been difficult to evaluate in spite of its prevalence. While traditional Doppler echocardiographic parameters enable only semiquantitative assessment of diastolic function and cannot reliably distinguish perturbations in loading conditions from altered diastolic functions, new technologies enable detailed quantification of global and regional diastolic function. The most readily available technique for the quantification of subclinical diastolic dysfunction is tissue Doppler imaging, which has been integrated into routine contemporary clinical practice, whereas cine magnetic resonance imaging (CMR) remains a promising complementary research tool for investigating the molecular mechanisms of the disease. Diastolic function is reported to vary linearly with age in normal persons, decreasing by 0.16 cm/s each year. Diastolic function in diabetes and the metabolic syndrome is determined by cardiovascular risk factors that alter myocardial stiffness and myocardial energy availability/bioenergetics. The latter is corroborated by the improvement in diastolic function with improvement in metabolic control of diabetes by specific medical therapy or lifestyle modification. Accordingly, diastolic dysfunction reflects the structural and metabolic milieu in the myocardium, and may allow targeted therapeutic interventions to modulate cardiac metabolism to prevent heart failure in insulin resistance and diabetes

Comparison of Hospital Building&rsquo;s Energy Consumption Prediction Using Artificial Neural Networks, ANFIS, and LSTM Network

Since accurate load forecasting plays an important role in the improvisation of buildings and as described in EU&rsquo;s &ldquo;Green Deal&rdquo;, financial resources saved through improvisation of the efficiency of buildings with social importance such as hospitals, will be the funds to support their mission, the social impact of load forecasting is significant. In the present paper, eight different machine learning predictors will be examined for the short-term load forecasting of a hospital&rsquo;s facility building. The challenge is to qualify the most suitable predictors for the abovementioned task, which is beneficial for an in-depth study on accurate predictors&rsquo; applications in Intelligent Energy Management Systems (IEMS). Three Artificial Neural Networks using a backpropagation algorithm, three Artificial Neural Networks using metaheuristic optimization algorithms for training, an Adaptive Neuro-Fuzzy Inference System (ANFIS), and a Long-Short Term Memory (LSTM) network were tested using timeseries generated from a simulated healthcare facility. ANFIS and backpropagation-based trained models outperformed all other models since they both deal well with complex nonlinear problems. LSTM also performed adequately. The models trained with metaheuristic algorithms demonstrated poor performance

In vitro release of new quinolones from biodegradable systems: A comparative study

A new biodegradable delivery system based on low molecular weight poly(lactic acid) has been formualted, with potential application in the sustained antibiotic release against bone infection. The in vitro release of two new quinolones (ofloxacin and ciprofloxacin) from the biodegradable matrix showed that the delivery of ofloxacin from the matrix lasted fifty-six days, whereas that of ciprofloxacin lasted fifty-one days. In both cases, release is controlled by the drug diffusion and the matrix degradation, the latter being the most critical factor. The obtained concentration levels are well above the Minimum Inhibitory Concentration (MIC) against the major causative bacteria of osteomyelitis. This fact in combination with the good reproducibility of measurements indicated that the system studied could be of value for the preparation of implantable controlled release systems for treatment of diseases in the bone system