Évaluer la sécurité des patients hospitalisés constitue un enjeu majeur de la gestion des risques pour les services de santé. Le développement d’indicateurs destinés à mesurer les événements indésirables liés aux soins (EIS) est une étape cruciale dont le défi principal repose sur la performance des données utilisées. Le développement d’indicateurs de la sécurité des patients – les Patient Safety Indicators (PSIs) – par l’Agency for Healthcare Research and Quality (AHRQ) aux Etats Unis, utilisant des codes de la 9ème révision (cliniquement modifiée) de la Classification Internationale des Maladies (CIM) présente des perspectives intéressantes. Nos travaux ont abordé cinq questions fondamentales liées au développement de ces indicateurs : la définition du cadre nosologique, la faisabilité de calcul des algorithmes et leur validité, la qualité des données pour coder les diagnostics médicaux à partir de la CIM et leur performance pour comparer plusieurs pays, et la possibilité d’établir une valeur de référence pour comparer ces indicateurs. Certaines questions demeurent cependant et nous proposons des pistes de recherche pour améliorer les PSIs : une meilleure définition des algorithmes et l’utilisation d’autres sources de données pour les valider (i.e., données de registre), ainsi que l’utilisation de modèles d’ajustement utilisant l’index de Charlson, le nombre moyen de diagnostics codés et une variable de la valeur prédictive positive, afin de contrôler les variations du case-mix et les différences de qualité du codage entre hôpitaux et pays. / Assessing safety among hospitalized patients is a major issue for health services. The development of indicators to measure adverse events related to health care (HAE) is a crucial step, for which the main challenge lies on the performance of the data used for this approach. Based on the limitations of the measurement in terms of reproducibility and on the high cost of studies conducted using medical records audit, the development of Patient Safety Indicators (PSI) by the Agency for Healthcare Research and Quality (AHRQ) in the United States, using codes from the clinically modified 9th revision of the International Classification of Diseases (ICD) shows interesting prospects. Our work addressed five key issues related to the development of these indicators: nosological definition; feasibility and validity of codes based algorithms; quality of medical diagnoses coding using ICD codes, comparability across countries; and possibility of establishing a benchmark to compare these indicators. Some questions remain, and we suggest several research pathways regarding possible improvements of PSI based on a better definition of PSI algorithms and the use of other data sources to validate PSI (i.e., registry data). Thus, the use of adjustment models including the Charlson index, the average number of diagnoses coded and a variable of the positive predictive value should be considered to control the case-mix variations and differences of quality of coding for comparisons between hospitals or countries.

The United States is one of the last countries to transition to the 10th edition of the International Classification of Diseases (ICD-10) coding system. The move from the 35-year-old system, ICD-9, to ICD-10, represents a milestone in the transformation of the 21st century healthcare industry. All covered healthcare entities were mandated to use the ICD-10 system on October 1, 2015, to justify medical necessity, an essential component in determining whether a service is payable or not. Despite the promising outcomes of this shift, more than 70% of healthcare organizations identified concerns related to education efforts, including lack of best practices for the ICD-10 transition. Lack of preparation for the implementation of ICD-10 undermines the clinical, technological, operational, and financial processes of healthcare organizations. This study was an exploration of implementation strategies used to overcome barriers to transition to ICD-10. A single case study was conducted, grounded by the conceptual framework of the technology acceptance model, to learn about ways to mitigate the barriers of this new coding system. Data were gathered from the review of documents, observations, and semistructured interviews with 9 participants of a public healthcare organization in Florida. Data were coded to identify themes. Key themes that emerged from the study included (a) in-depth ICD-10 training, (b) the prevalence of ICD-10 cheat sheets, (c) lack of system readiness, and (d) perception of usefulness of job performance. The results of the study may contribute to social change by identifying successful implementation strategies to mitigate operational disruptions that will allow providers to capture more detailed health information about the severity of patients' conditions.

Over the past several decades rates of spine surgeries in the U.S. have increased dramatically. Spinal fusion surgery rates, in particular, have grown exponentially despite being one of the most costly, invasive, and controversial methods for treating patients suffering from back conditions. Furthermore, lumbar fusion surgeries continue to be performed at increasing rates despite a lack of scientific evidence and consensus that they are cost-effective and produce better clinical outcomes than less radical treatment of lower back pain. As a result, large amounts of healthcare dollars continue to be invested in these costly procedures which are potentially dangerous and have questionable efficacy in terms of improving patient outcomes. Importantly, there is a lack of population studies in the literature on spinal fusion surgeries from a health services research perspective. Therefore, the present research is a population based study using an administrative database and includes patients of all ages and payer types. The data used in the present study come from the Florida Agency for Health Care Administration (AHCA) and include all hospitalizations in Florida in 2010. The objective of the study is to analyze the incidence of spinal fusion surgeries in Florida hospitals for patients of all ages and payer types by demographic variables to understand who gets these surgeries and for which conditions. The first null hypothesis is that there are no statistically significant predictors of the incidence of lumbar/lumbosacral, dorsal/dorsolumbar spinal fusion surgeries in Florida hospitals. Logistic regression was used to analyze the incidence of fusion surgeries. The binary dependent variable was coded as a "1" for all patients who were a case (i.e. they received one of the five procedure codes being studied in the present research) and a "0" for all patients who were controls (meaning they did not receive any of the five fusion procedure codes). Logistic regression was used to predict the probability of an observation being a "1" given the independent variables included in the model. Additionally, hospital charges were analyzed to understand the associated hospital charges with these surgeries. The second null hypothesis is that there are no statistically significant predictors of the charges of Lumbar/Lumbosacral, Dorsal/Dorsolumbar spinal fusion surgeries in Florida Hospitals. A mixed effects model was used to test this hypothesis and the fixed effects which were included in the model were gender, age, race, principal payer, and principal procedure. A mixed effects model was chosen due to the fact that cases who had surgeries performed at the same hospital are not independent and therefore the data were clustered on hospitals. A random intercept term was used to address this fact. SAS software was used to complete all of the analyses. In 2010, there were 16,236 Lumbar/Lumbosacral, Dorsal/Dorsolumbar fusion surgery cases in Florida hospitals that were included in the case population and 21,856 individuals included in the control population for a total of 38,092 included in the study population. An understanding of who is most likely to receive a fusion surgery, at what age, and for which diagnoses, as has been done here, is extremely important. This knowledge can help researchers, policy makers, and physicians alike. Comprehensive physician practice guidelines for performing fusion surgeries still do not exist in the year 2013; therefore, in order to have the greatest impact, the efforts for creating the guidelines should be focused on those individuals who are most likely to receive fusions as shown for the first time by the data analyzed here. Given the high incidence of these surgeries in Florida alone, the need for practice guidelines cannot be overstated. The total hospital charges in Florida hospitals for the 16,236 cases were $2,095,413,584. Despite having the same principal diagnoses and a similar number of additional diagnoses, patients who received a fusion surgery resulted in approximately three times the charges as those incurred by the controls. Overall, the high incidence and charges for fusion surgeries shown in this study emphasize the importance of having a better understanding of when these surgeries are justified and for which patients. Without comprehensive practice guidelines established through evidence-based research this is difficult, if not impossible, to accomplish. The diagnoses which are most prevalent and show the most inconsistencies between cases may be a good starting point for such guidelines.

Prostate cancer is the most common cancer in men, with the incidence rapidly increasing in Europe over the past two decades. Reliable biomarkers for prostate cancer are currently unavailable. Thus, there is an urgent need for improved biomarkers to diagnose prostate cancer at an early stage and to determine the best treatment options. Higher expression of transforming growth factor-β (TGFβ) has been reported in patients with aggressive cancer. TGFβ is a multifunctional cytokine that acts as a tumor suppressor during early tumor development, and as a tumor promoter at later stages of cancer. TGFβ signals through the canonical Smad or non-Smad cascade via TGFβ type II and type I receptors. The TGFβ signaling cascade is regulated by various post-translational modifications of its key components. The present investigation aimed to identify a potential function of TRAF6 in TGFβ-induced responses in prostate cancer. The first two articles of this thesis unveil the proteolytic cleavage of TGFβ type I receptor (TβRI), and the biological importance of the liberated TβRI intracellular domain (TβRI-ICD) in the nucleus. We found that tumor necrosis factor receptor-associated factor 6 (TRAF6) polyubiquitinates TβRI, which leads to cleavage of TβRI by tumor necrosis factor alpha converting enzyme (TACE) in a protein kinase C zeta (PKCζ)-dependent manner. Following ectodomain shedding, TβRI undergoes a second cleavage by presenilin 1 (PS1), which liberates TβRI-ICD. TβRI-ICD translocates to the nucleus, where it regulates its own expression as well as expression of the pro-invasive gene Snail1, thereby promoting invasion. We further found that TβRI-ICD associates with Notch intracellular domain (NICD) to drive expression of the pro-invasive gene Snail1, as well as Notch1 ligand Jag1. The third article provides evidence that TRAF6 promotes Lys63-linked polyubiquitination of TβRI at Lys178 in a TGFβ-dependent manner. TβRI polyubiquitination was found to be a prerequisite for TβRI nuclear translocation, and thus for regulation of the genes involved in cell cycle, differentiation, and invasion of prostate cancer cells. In the fourth article we investigated the role of the pro-invasive gene Snail1 in TGFβ-induced epithelial-to-mesenchymal transition (EMT) in prostate cancer cells.

Bakgrund: Hjärt-och kärlsjukdomar är den vanligaste dödsorsaken i världen. En behandlingsform som skyddar mot hjärt-och kärlsjukdomar i form av plötslig hjärtdöd och livshotande arytmier är en Implanterbar Cardioverter Defibrillator (ICD). ICD-apparaten kan bland annat avge defibrilleringar när hjärtats rytm avviker från normal sinusrytm. Hälsorelaterad livskvalitet kan mätas för att avgöra hur en viss behandling påverkar människors livskvalitet. Hälsorelaterad livskvalitet kan mätas med hjälp av olika mätskalor. Skalorna undersöker bland annat patienters hälsostatus, emotionell och psykisk funktion och hur dessa påverkar det sociala och dagliga livet. Begreppet kan även brytas ner till olika domäner i form av generell livskvalitet samt psykiska domän i form av depression och ångest. Syfte: Syftet med litteraturstudien var att undersöka hur ICD-behandlingen påverkar den hälsorelaterade livskvaliteten hos personer med en implanterbar ICD. Metod: En litteraturstudie med kvantitativ ansats tillämpades och baserades på tolv vetenskapliga artiklar. Resultat: Den hälsorelaterade livskvaliteten hos hjärtsjuka patienter inför en ICD-behandling var signifikant försämrad, i jämförelse med generell befolkning. Den rapporterade livskvaliteten hos hjärtsjuka människor uppmättes som lägst kort innan en ICD-implantation och ICD-behandlingen utgav en signifikant förbättring på livskvaliteten, sex till tolv månader efter implantionen. Ångestrelaterade tankar, depression, den emotionella, psykiska och mentala hälsan angav förbättrade resultat när patienterna fått ICD-behandling, i jämförelse med hur den hälsorelaterade livskvaliteten hos patienterna var före behandlingen. Konklusion: Den hälsorelaterade livskvaliteten tenderade att höjas hos hjärtsjuka patienter som fått en implanterad ICD. Utan ICD-behandling uppmätte hjärtsjuka patienter en signifikant försämrad livskvalitet, i jämförelse med generell befolkning. Däremot försvann den signifikanta skillnaden i hälsorelaterad livskvaliteten mellan hjärtsjuka patienter och generell befolkning efter att de hjärtsjuka erhållit en ICD-behandling. / Background: Heart-diseases are the most common cause of death in the whole world. Treatment that could possibly save patients from sudden cardiac arrest and life-threatening arrhythmias is the Implantable Cardioverter Defibrillator (ICD). The ICD can for instance give defibrillations when the heart departs from regular sinus rhythm. Health-related quality of life can be measured to assess how a certain treatment is affecting peoples’ quality of life. ICD-treatment can be measured in health-related quality of life. Health-related quality of life can be measured with help of different types of measurements and scales. It investigates the patients’ health-status and physical and emotional function and in which way it impacts the daily and social life. Health-related quality of life is a huge concept that can be divided in to smaller domains, like general quality of life and physical symptoms like depression and anxiety. Aim: The aim of this study was to investigate how ICD-treatment infects patients’ health-related quality of life.Method: A literature review with quantitative study-design, based on twelve scientific articles. Result: The health-related quality of life in patients with cardiac problems who are facing an ICD-treatment were significant worse, in comparison with the general population. However, the reported quality of life in patients with cardiac problems was measured at its lowest shortly before the ICD-implantation and the ICD-treatment had a significant improvement on the quality of life, six to twelve months after the implantation. Anxiety-related thoughts, depression, the emotional, physical and mental health indicated a better result when the patients with cardiac problems received an implantable ICD, in comparison with how the health-related quality of life were before the treatment. Conclusion: The health-related quality of life tends to increase after the patients with cardiac problems received an ICD. Without the ICD-treatment, the patients with cardiac problems measure a significantly worse quality of life, in comparison to the general population. However, the significantly worse impact on the quality of life in patients with cardiac problems in comparison with the general population, disappeared after the patients received an ICD.

No description available.

Cette thèse porte sur la préparation de nouveaux catalyseurs chiraux à partir de composés naturels issus de la biomasse, et leurs applications en organocatalyse asymétrique. La première partie décrit la synthèse de thiourées énantiomériquement pures dérivées de l'isosorbide et l’isommanide. Ces thiourées ont été évaluées comme catalyseurs organiques dans des réactions asymétriques de Friedel-Crafts, d’alkylation, d’addition de type aza-Michael, d’hydroamination et de type Morita-Baylis-Hillman (MBH). Les meilleurs résultats en termes de réactivité et d’induction asymétrique, ont été obtenus dans le cas de la réaction de Friedel-Crafts. La deuxième partie est consacrée à la conception et la synthèse de thiourée-phosphines chirales à partir de la L-proline. Ces thiourée-phosphines sont capables de promouvoir la formation de liaisons C-N et C-S, selon un processus de substitution allylique énantiosélectif d’adduits modifiés de MBH. De très bons rendements (jusqu’à 98%) et énantiosélectivités (jusqu'à 93%) ont été obtenus. Dans la troisième partie, nous avons développé le premier exemple de cyclisation [4 + 2] entre un allénoate et un alcène tétrasubstitué, catalysée par une amine tertiaire. Nous avons montré que des composés de type 4H-pyranniques peuvent être sélectivement obtenus, avec d’excellents rendements, en utilisant le DABCO comme catalyseur. Dans le cas de catalyseur organique de type alcaloïde, le β-ICD conduit sélectivement aux composés 2H-pyranniques avec des excès énantiomériques jusqu’à 71 % ee. / The thesis focused on the preparation of new chiral catalysts derived from biomass and their applications in asymmetric organocatalysis. The first part described the synthesis of chiral thioureas derived from isosorbide and isomanide, naturally renewable resource, in moderate to good overall yields. These thioureas were evaluated in asymmetric reactions such as Friedel-Crafts alkylation, aza-Michael addition, hydroamination, Morita-Baylis-Hillman reaction. Good yields and enantioselectivities were obtained. The second part of our work went on the design and synthesis of chiral thiourea-phosphines from L-Proline. These thiourea-phosphines promoted C-N and C-S bond formation via the asymmetric allylic substitution of tert-butoxycarbonyloxy adducts. Good yields (up to 98 %) and enantioselectivities (up to 93 %) were observed. In the third part, we have developed the first example [4+2] annulation of allenoate and all-carbon tetrasubstituted alkenes catalyzed by an amine. In the case of DABCO catalyst, 4H-pyrans were isolated exclusively in good to excellent yield under mild reaction conditions. While employing β-ICD as catalyst, the enantioenriched 2H-pyran derivatives were obtained with enantiomeric excess up to 71 % ee.

Identifying factors associated with appropriate and inappropriate therapies in patients with implantable cardioverter-defibrillator (ICD) could help to identify those at risk and reduce the incidence of this emergency situation which has detrimental effect on mortality and morbidity in patients with ICD. These studies were designed to find the prevalence and factors associated with appropriate and inappropriate therapies in patients with ICD.

Electronic Health Record (EHR) is an umbrella term encompassing demographics and health information of a patient from many different sources in a digital format. Deep learning has been used on EHRs in many successful studies and there is great potential in future implementations. In this study, diagnosis classification of EHRs with Multi-layer Perceptron models are studied. Two MLPs with different architectures are constructed and run on both a modified version of the EHR dataset and the raw data. A Random Forest is used as baseline for comparison. The MLPs are not successful in beating the baseline, with the best-performing MLP having a classification accuracy of 48.1%, which is 13.7 percentage points lower than that of the baseline. The results indicate that when the dataset is small, this approach should not be chosen. However, the dataset is growing over time and thus there is potential for continued research in the future. / Elektronisk patientjournal (EHR) är ett paraplybegrepp som används för att beskriva en digital samling av demografisk och medicinsk data från olika källor för en patient. Det finns stor potential i användandet av djupinlärning på dessa journaler och många framgångsrika studier har redan gjorts på området. I denna studie undersöks diagnosklassificering av elektroniska patientjournaler med Multi-layer perceptronmodeller. Två MLP-modeller av olika arkitekturer presenteras. Dessa körs på både en anpassad version av EHR-datamängden och på den råa EHR-datan. En Random Forest-modell används som baslinje för jämförelse. MLP-modellerna lyckas inte överträffa baslinjen, då den bästa MLP-modellen ger en klassifikationsnoggrannhet på 48,1%, vilket är 13,7 procentenheter mindre än baslinjens. Resultaten visar att en liten datamängd indikerar att djupinlärning bör väljas bort för denna typ av problem. Datamängden växer dock över tid, vilket gör områdetattraktivt för framtida studier.

The use of Electronic Health Records (EHR) for reporting patient data has been widely adopted by healthcare providers. This data can encompass many forms of medical information such as disease symptoms, results from laboratory tests, ICD-10 classes and other information from patients. Structured EHR data is often high-dimensional and contain many missing values, which impose a complication to many computing problems. Detecting meaningful structures in EHR data could provide meaningful insights in diagnose detection and in development of medical decision support systems. In this work, a subset of EHR data from patient questionnaires is explored through two well-known clustering algorithms: K-Means and Agglomerative Hierarchical. The algorithms were tested on different types of data, primarily raw data and data where missing values have been imputed using different imputation techniques. The primary evaluation index for the clustering algorithms was the silhouette value using euclidean and cosine distance measures. The result showed that natural groupings most likely exist in the data set. Hierarchical clustering created higher quality clusters than k-means, and the cosine measure yielded a good interpretation of distance. The data imputation imposed large effects to the data and likewise to the clustering results, and other or more sophisticated techniques are needed for handling missing values in the data set. / Användandet av digitala journaler för att rapportera patientdata har ökat i takt med digitaliseringen av vården. Dessa data kan innehålla många typer av medicinsk information så som sjukdomssymptom, labbresultat, ICD-10 diagnoskoder och annan patientinformation. EHR data är vanligtvis högdimensionell och innehåller saknade värden, vilket kan leda till beräkningssvårigheter i ett digitalt format. Att upptäcka grupperingar i sådana patientdata kan ge värdefulla insikter inom diagnosprediktion och i utveckling av medicinska beslutsstöd. I detta arbete så undersöker vi en delmängd av digital patientdata som innehåller patientsvar på sjukdomsfrågor. Detta dataset undersöks genom att applicera två populära klustringsalgoritmer: k-means och agglomerativ hierarkisk klustring. Algoritmerna är ställda mot varandra och på olika typer av dataset, primärt rådata och två dataset där saknade värden har ersatts genom imputationstekniker. Det primära utvärderingsmåttet för klustringsalgoritmerna var silhuettvärdet tillsammans med beräknandet av ett euklidiskt distansmått och ett cosinusmått. Resultatet visar att naturliga grupperingar med stor sannolikhet finns att hitta i datasetet. Hierarkisk klustring visade på en högre klusterkvalitet än k-means, och cosinusmåttet var att föredra för detta dataset. Imputation av saknade data ledde till stora förändringar på datastrukturen och således på resultatet av klustringsexperimenten, vilket tyder på att andra och mer avancerade dataspecifika imputationstekniker är att föredra.