INTRODUCTION: Acute severe ulcerative colitis (ASUC) is a severe complication of ulcerative colitis (UC) that is associated with significant morbidity, treatment refractoriness and need for colectomy. Patients who do not adequately respond to the initial intravenous steroid therapy receive medical rescue therapy with infliximab or cyclosporine or undergo surgery for their refractory disease. However, there is limited guidance on management of steroid responders in this setting. While it is well established that Crohn’s disease (CD) is progressive and benefits from early institution of immunosuppressive therapy, such a paradigm is less well established in UC and thresholds for therapy escalation remain poorly defined. In immunosuppression-naïve patients, whether a single hospitalization for ASUC is a sufficient threshold to escalate to immunomodulator or biologic therapy is unknown. METHODS: From a single tertiary referral center, we identified all patients with ASUC hospitalized for intravenous steroids who were immunosuppression naïve (new UC diagnosis, no therapy, or 5-aminosalicylate (5-ASA) therapy) at their index hospitalization. We excluded patients who were refractory to steroids and initiated medical rescue therapy or required surgery during the index hospitalization. Our primary exposure of interest was initiation of biologic therapy within 1 month of hospital discharge or immunomodulator therapy (thiopurine, methotrexate) within 3 months. Our primary outcomes were need for colectomy within 12 months following hospitalization. Secondary outcomes include re-hospitalization rate within 12 months and late colectomy ( between 91-365 days). RESULTS: Our study included a total of 133 immunosuppressive-naïve ASUC patients among whom 56 (42%) escalated therapy to thiopurine (93%) or biologic (7%) post-hospitalization. The median age of the cohort was 29 years (range 16 – 88 years) and 46% were male. 82 patients (62%) had pancolitis on disease distribution. 38% and 58% were noted to have moderate to severe disease on sigmoidoscopic evaluation. Thirteen patients (10%) underwent surgery by 1 year. At 12 months, there was no difference in the rate of colectomy among those with therapy escalation (13%) compared to those who did not undergo such escalation (8%, unadjusted OR= 1.69 p=0.53). This lack of difference remained robust on multivariable regression analysis and propensity score adjusted models (OR 0.90, 95% confidence interval (CI) 0.18 – 4.45). There was no difference in the rates of hospitalization within 1 year (OR 2.24 95% CI 0.16 – 4.22) or in the time to colectomy between the two groups (log-rank p=0.27). CONCLUSION: Immunosuppression-naïve ASUC patients who respond to intravenous steroids remain at high risk for colectomy with 10% (13/133) receiving such surgery within 1 year. Therapy escalation was not associated with a reduction in this risk. There is an important need for larger prospective studies defining the benefit of early therapy escalation in UC, and appropriate thresholds for the same.

Le secteur des télécommunications mobiles a connu une croissance très rapide dans un passé récent avec pour résultat d'importantes évolutions technologiques et architecturales des réseaux sans fil. L'expansion et l'hétérogénéité de ces réseaux ont engendré des coûts de fonctionnement de plus en plus importants. Les dysfonctionnements typiques de ces réseaux ont souvent pour origines des pannes d'équipements ainsi que de mauvaises planifications et/ou configurations. Dans ce contexte, le dépannage automatisé des réseaux sans fil peut s'avérer d'une importance particulière visant à réduire les coûts opérationnels et à fournir une bonne qualité de service aux utilisateurs. Le dépannage automatisé des pannes survenant sur les réseaux sans fil peuvent ainsi conduire à une réduction du temps d'interruption de service pour les clients, permettant ainsi d'éviter l'orientation de ces derniers vers les opérateurs concurrents. Le RAN (Radio Access Network) d'un réseau sans fil constitue sa plus grande partie. Par conséquent, le dépannage automatisé des réseaux d'accès radio des réseaux sans fil est très important. Ce dépannage comprend la détection des dysfonctionnements, l'identification des causes des pannes (diagnostic) et la proposition d'actions correctives (déploiement de la solution). Tout d'abord, dans cette thèse, les travaux antérieurs liés au dépannage automatisé des réseaux sans-fil ont été explorés. Il s'avère que la détection et le diagnostic des incidents impactant les réseaux sans-fil ont déjà bien été étudiés dans les productions scientifiques traitant de ces sujets. Mais étonnamment, aucune référence significative sur des travaux de recherche liés aux résolutions automatisées des pannes des réseaux sans fil n'a été rapportée. Ainsi, l'objectif de cette thèse est de présenter mes travaux de recherche sur la " résolution automatisée des dysfonctionnements des réseaux sans fil LTE (Long Term Evolution) à partir d'une approche statistique ". Les dysfonctionnements liés aux paramètres RRM (Radio Resource Management) seront particulièrement étudiés. Cette thèse décrit l'utilisation des données statistiques pour l'automatisation du processus de résolution des problèmes survenant sur les réseaux sans fil. Dans ce but, l'efficacité de l'approche statistique destinée à l'automatisation de la résolution des incidents liés aux paramètres RRM a été étudiée. Ce résultat est obtenu par la modélisation des relations fonctionnelles existantes entre les paramètres RRM et les indicateurs de performance ou KPI (Key Performance Indicator). Une architecture générique automatisée pour RRM 8 a été proposée. Cette dernière a été utilisée afin d'étudier l'utilisation de l'approche statistique dans le paramétrage automatique et le suivi des performances des réseaux sans fil. L'utilisation de l'approche statistique dans la résolution automatique des dysfonctionnements des réseaux sans fil présente deux contraintes majeures. Premièrement, les mesures de KPI obtenues à partir du réseau peuvent contenir des erreurs qui peuvent partiellement masquer le comportement réel des indicateurs de performance. Deuxièmement, ces algorithmes automatisés sont itératifs. Ainsi, après chaque itération, la performance du réseau est généralement évaluée sur la durée d'une journée avec les nouveaux paramètres réseau implémentés. Les algorithmes itératifs devraient donc atteindre leurs objectifs de qualité de service dans un nombre minimum d'itérations. La méthodologie automatisée de diagnostic et de résolution développée dans cette thèse, basée sur la modélisation statistique, prend en compte ces deux difficultés. Ces algorithmes de la résolution automatisé nécessitent peu de calculs et convergent vers un petit nombre d'itérations ce qui permet leur implémentation à l'OMC (Operation and Maintenace Center). La méthodologie a été appliquée à des cas pratiques sur réseau LTE dans le but de résoudre des problématiques liées à la mobilité et aux interférences. Il est ainsi apparu que l'objectif de correction de ces dysfonctionnements a été atteint au bout d'un petit nombre d'itérations. Un processus de résolution automatisé utilisant l'optimisation séquentielle des paramètres d'atténuation des interférences et de packet scheduling a également été étudié. L'incorporation de la "connaissance a priori" dans le processus de résolution automatisé réduit d'avantage le nombre d'itérations nécessaires à l'automatisation du processus. En outre, le processus automatisé de résolution devient plus robuste, et donc, plus simple et plus pratique à mettre en œuvre dans les réseaux sans fil. / The mobile telecommunication industry has experienced a very rapid growth in the recent past. This has resulted in significant technological and architectural evolution in the wireless networks. The expansion and the heterogenity of these networks have made their operational cost more and more important. Typical faults in these networks may be related to equipment breakdown and inappropriate planning and configuration. In this context, automated troubleshooting in wireless networks receives a growing importance, aiming at reducing the operational cost and providing high-quality services for the end-users. Automated troubleshooting can reduce service breakdown time for the clients, resulting in the decrease in client switchover to competing network operators. The Radio Access Network (RAN) of a wireless network constitutes its biggest part. Hence, the automated troubleshooting of RAN of the wireless networks is very important. The troubleshooting comprises the isolation of the faulty cells (fault detection), identifying the causes of the fault (fault diagnosis) and the proposal and deployement of the healing action (solution deployement). First of all, in this thesis, the previous work related to the troubleshooting of the wireless networks has been explored. It turns out that the fault detection and the diagnosis of wireless networks have been well studied in the scientific literature. Surprisingly, no significant references for the research work related to the automated healing of wireless networks have been reported. Thus, the aim of this thesis is to describe my research advances on "Automated healing of LTE wireless networks using statistical learning". We focus on the faults related to Radio Resource Management (RRM) parameters. This thesis explores the use of statistical learning for the automated healing process. In this context, the effectiveness of statistical learning for automated RRM has been investigated. This is achieved by modeling the functional relationships between the RRM parameters and Key Performance Indicators (KPIs). A generic automated RRM architecture has been proposed. This generic architecture has been used to study the application of statistical learning approach to auto-tuning and performance monitoring of the wireless networks. The use of statistical learning in the automated healing of wireless networks introduces two important diculties: Firstly, the KPI measurements obtained from the network are noisy, hence this noise can partially mask the actual behaviour of KPIs. Secondly, these automated healing algorithms are iterative. After each iteration the network performance is typically evaluated over the duration of a day with new network parameter settings. Hence, the iterative algorithms should achieve their QoS objective in a minimum number of iterations. Automated healing methodology developped in this thesis, based on statistical modeling, addresses these two issues. The automated healing algorithms developped are computationaly light and converge in a few number of iterations. This enables the implemenation of these algorithms in the Operation and Maintenance Center (OMC) in the off-line mode. The automated healing methodolgy has been applied to 3G Long Term Evolution (LTE) use cases for healing the mobility and intereference mitigation parameter settings. It has been observed that our healing objective is achieved in a few number of iterations. An automated healing process using the sequential optimization of interference mitigation and packet scheduling parameters has also been investigated. The incorporation of the a priori knowledge into the automated healing process, further reduces the number of iterations required for automated healing. Furthermore, the automated healing process becomes more robust, hence, more feasible and practical for the implementation in the wireless networks.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第19243号 / 農博第2140号 / 新制||農||1036(附属図書館) / 学位論文||H27||N4947(農学部図書室) / 32242 / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 今井 裕, 教授 祝前 博明, 教授 松井 徹 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

No description available.

Thesis advisor: Karen S. Lyons / OBJECTIVES: Individuals with severe persistent mental illness (SPMI), also referred to as serious mental illness (SMI), experience significant inequities in health care access and outcomes. These inequities may span the lifetime of an individual living with SPMI, and include poorer cancer outcomes, shorter lifespans, barriers to having their needs met in long-term care, and a decreased likelihood of receiving hospice care when indicated. The purpose of this dissertation was to explore the causes of the disproportionately poor health outcomes for individuals living with SPMI and describe current facilitators and barriers to providing care to this vulnerable population. METHODS: A qualitative descriptive study was carried out to explore health care professionals’ perception of the needs of long-term care residents with SPMI and chronic medical conditions. and barriers and facilitators to meeting the needs of this population. A narrative review was performed to identify what is currently known about cancer symptom clusters in individuals with schizophrenia. Lastly, an integrated review was conducted to identity factors associated with hospice use by individuals with SPMI and potential barriers to use of hospice services. RESULTS: Ten health care professionals were interviewed for the qualitative study. The themes that emerged were: coming to know the individual and their unique needs takes time; being flexible and adapting approaches facilitates trust; respecting the inherent worth of each person contributes to caring. Participants described the importance of a person-centered approach when caring for long-term care residents with SPMI and chronic medical conditions. The narrative review of current literature pertaining to cancer symptom clusters in individuals with schizophrenia revealed that this phenomenon has been sparsely represented in research. No data directly pertaining to cancer symptom clusters in this population were identified. Data describing the related phenomena of health conditions that may influence cancer risk and outcomes, physical experiences of cancer, and emotional and behavioral symptoms which may impact ability to tolerate cancer treatments were identified. The integrated review of literature describing factors associated with hospice use among individuals with SPMI found that hospice and palliative care services may not be utilized by individuals with SPMI due to system-level barriers such as inadequate patient-provider communication, fragmented care, and absence of discussions around end-of-life care. CONCLUSIONS: Systemic problems such as miscommunication, fragmentation of care, and stigma contribute to the health inequities experienced by individuals living with SPMI. Nurses and other health care providers can work to ameliorate these systemic problems by promoting and participating in collaborative care models and utilizing assessment techniques appropriate to individuals who may have difficulty communicating about their health-related symptoms. Individuals with SPMI should be offered opportunities to participate in research when appropriate so that they may benefit from newer treatments for disease, and health care providers may improve their understanding of how to address the medical needs of this population. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Connell School of Nursing. / Discipline: Nursing.

<p>The project explores decision making in the context of end-of-life (EOL) care choices among adults with few social and economic resources. Although most American adults believe that planning for EOL is important, only about 30% report making formal EOL plans such as Advance Directives, wills, trusts, or any other formal documentation. Using qualitative methodology, 25, participants who were all living at the same long term care facility, were interviewed during two different waves of data collection. The transcribed interviews were analyzed using thematic analysis and guided by Normative Rhetorical Theory framework. Remarkable conclusions were that without social and economic resources, participants reported they did not make choices about EOL and care, but rather their decisions were made by default.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Anatomy Academy (AA) is a service-learning program in which pre- and current health professional students (Mentors) work in pairs to teach anatomy, physiology, and nutrition to children in the community. The purpose of this study was to investigate the short- and long-term Mentor outcomes in personal, social, civic, academic, and professional domains. Former Mentors were invited to complete a survey of Likert-style and free response questions evaluating the perceived impact of their AA experience on: teaching skills, personal and interpersonal development, civic engagement, and academic and professional development. Follow-up interviews with a subset of survey respondents were performed. The survey was completed by 219 Mentors and 17 survey respondents were interviewed. Over 50% of former Mentors reported moderate or major impact of AA participation on elements of personal and interpersonal development (e.g., selfesteem [57.6%], altruism [67.9%], communication skills [60.1%], and ability to work with others [72.6%]) and community service participation (54.2%) that endures in the years after the program. Mentors who worked with low-income or Special needs populations reported unique impacts in personal, interpersonal, and civic domains. A majority of former Mentors agreed that AA participation helped them learn practical skills (76.3%) and factual knowledge (65.4%) relevant to the their careers, with several current health professionals reported that they regularly employ teaching and interpersonal skills learned while Mentors in their roles as physicians, nurses, or physician’s assistants. A majority of former Mentors reported that AA validated their choice to either pursue a healthcare career or not (59.7%), increased their confidence in performing professional tasks (64.7%), and helped shape their professional identity (58.9%). These results indicate that a health education-based service-learning program offers undergraduate, graduate, and professional students interested in or actively pursuing a healthcare career benefits across personal, interpersonal, civic, and professional domains that support their academic progress and preparation for professional practice. This study contributes much-needed evidence of the long-term student outcomes of service-learning to the literature, with a particular focus on how the pedagogy can supplement the education and professional development of pre- and current health professional students.

The population of elderly people in the United States is predicted to increase in large numbers within the next few decades. Many of them will be admitted to long-term-care centers in the waning years of their lives. Health care professionals will need to be prepared for this influx of the elderly into these institutions and for their demands of improved quality of life in these centers. Unplanned weight loss has become one of the major predictors of mortality in long-term-care residents. The purpose of the study was to compare the use of liberalized diets with the traditional therapeutic diets long advocated in long-term-care facilities in the United States. The objectives were to conduct a randomized clinical trial with a treatment group (subjects who consumed liberalized diets) and a control group (subjects who continued with their usual therapeutic diets), and to compare outcomes between the two groups. The randomized clinical trial was conducted for 18 weeks from April to August 2009 at a long-term-care facility in rural North Mississippi. Twenty-two persons ranging in age from 54 to 100 years were approved by their physicians for participation in the trial. All of these persons participated and completed the trial. Eleven of the participants received their prescribed therapeutic diet and 11 participants received a liberalized diet for the length of the trial study. At the end of the study, there were no significant differences (p>0.05) in mean body weights and laboratory values between the two groups. However, there was a trend of weight loss in the therapeutic diet group (mean weight loss of 2% (1.4 kg) during the 18-week trial), and although it was not significant (p>0.05), this supports the growing belief of those who advocate liberalized geriatric diets to improve quality of life and prevent unintentional weight loss. Participants in the liberalized diet group did not experience weight loss and gained 0.5 kg by the end of the study.

No description available.

This paper examines the funding procedure in Ontario long-term care facilities and seeks to identify whether current resources for protecting the elderly from mistreatment is allocated fairly and effectively. The research also observes how the political economy may influence the needs-based allocation built to protect seniors from mistreatment in institutional care settings and the consequences of these resources on residents’ autonomy. The topic is also viewed through the lens of the current COVID-19 pandemic. Five experts in the area of long-term care participated in this research work including academics, scholars and institutional or agency advocates. Interviews lasting up to 60 minutes interviews were conducted, transcribed and analyzed using a political economy lens. Participants described their knowledge and experience with the funding procedure for long term-care facilities, particularly in Ontario and provided their view on areas that they felt could be improved. The analysis identified four themes including whether the issue is under-resourced, poor allocation of resources; funding according to need; the struggle to define and assess the quality of care; and general work conditions in long-term care. The result of this research will help us to better understand the resource allocation of Ontario long-term care facilities which could in turn highlight improvements that could be made to create better quality of life for residents as well as frontline workers. / Thesis / Master of Arts (MA) / This paper examines the funding procedure in Ontario long-term care facilities and seeks to identify whether current resources for protecting the elderly from mistreatment is allocated fairly and effectively. The topic is viewed through the lens of the COVID-19 pandemic. The analysis of the five expert interviews identified four themes including whether the issue is under-resourced, poor allocation of resources; funding according to need; the struggle to define and assess the quality of care; and general work conditions in long-term care. The result of this research will help us to better understand the resource allocation of Ontario long-term care facilities which could in turn highlight improvements that could be made to create better quality of life for residents as well as frontline workers.