Background: Vaccination against SARS-CoV-2 significantly reduces the transmissibility of the virus and the likelihood of a severe course of COVID-19, and is thus a critical component in overcoming the current pandemic. The factors associated with adverse reactions after vaccination against SARS-CoV-2 have not yet been sufficiently evaluated. Methods: We used the Disease Analyzer database (IQVIA) to identify 531,468 individuals who received a total of 908,869 SARS-CoV-2 vaccinations in 827 general practices in Germany between April and September 2021. Cox regression models were used to analyze the frequency of vaccination-related side effects reported within 14 days after SARS-CoV-2 vaccination, as well as subjects’ demographic characteristics and comorbidities. Results: The total number of side effects documented was 28,287 (3.1% of all vaccinations). Pain in the limb (24.3%), fatigue (21.0%), dizziness (17.9%), joint pain (15.7%), fever (9.5%), nausea (7.5%), and myalgia (6.4%) were the most common side effects documented among the 12,575 vaccinations with definite side effects. In the multivariate regression analysis, young age was associated with much higher odds of reported side effects (OR18–30 years: 4.45, OR31–40 years: 3.50, OR41–50 years: 2.89). In addition, pre-existing comorbidities such as dementia (OR: 1.54), somatoform disorder (OR: 1.53), anxiety disorder (OR: 1.43), depression (OR: 1.37), chronic respiratory tract disease (OR: 1.27), hypertension (OR: 1.20), and obesity (1.14) significantly increased the odds of side effects. Finally, the male sex was associated with increased odds of reported side effects (OR: 1.17). Conclusion: Our study, based on a large outpatient database from Germany, identified young age, male sex, and pre-existing comorbidities such as dementia, somatoform disorders, anxiety disorders, and depression as factors associated with vaccine-related adverse events diagnosed in GP practices. These data could help to identify subgroups needing particular advice and care in the context of SARS-CoV-2 vaccinations.

京都大学 / 新制・課程博士 / 博士(薬科学) / 甲第24559号 / 薬科博第176号 / 新制||薬科||19(附属図書館) / 京都大学大学院薬学研究科医薬創成情報科学専攻 / (主査)教授 馬見塚 拓, 教授 山下 富義, 教授 金子 周司 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

剖面所進行的運算通常都牽涉到狀態處理。在純粹函數式語言中，利用monadification技術添加狀態處理的剖面必須對程式碼做橫跨性的修改。本論文提出讓純粹函數式語言的剖面具備狀態處理功能，而使用者不須額外改寫既有程式碼的方法。我們提出了簡單直接的狀態操作語言機制，可以用來開發狀態處理剖面；並且設計出系統化的monadification規則，讓編譯器自動對程式碼做轉換，並維持惰性求值的特性。 / Computations performed in many typical aspects involve side effects. In a purely functional setting, adding such aspects using techniques such as monadification will generally lead to crosscutting changes. This thesis presents an approach to provide side-effecting aspects for purely lazy functional languages in a user transparent fashion. We propose a simple yet direct state manipulation construct for developing side-effecting aspects and devise a systematic monadification scheme to translate the woven code to a purely monadic style functional code. To maintain the lazy evaluation feature, the monad employed is extended with cache functionality.

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Les effets indésirables médicamenteux (EIM) ont des répercussions considérables tant sur la santé que sur l'économie. De 1,9% à 2,3% des patients hospitalisés en sont victimes, et leur coût a récemment été estimé aux alentours de 400 millions d'euros pour la seule Allemagne. De plus, les EIM sont fréquemment la cause du retrait d'un médicament du marché, conduisant à des pertes pour l'industrie pharmaceutique se chiffrant parfois en millions d'euros.De multiples études suggèrent que des facteurs génétiques jouent un rôle non négligeable dans la réponse des patients à leur traitement. Cette réponse comprend non seulement les effets thérapeutiques attendus, mais aussi les effets secondaires potentiels. C'est un phénomène complexe, et nous nous tournons vers l'apprentissage statistique pour proposer de nouveaux outils permettant de mieux le comprendre.Nous étudions différents problèmes liés à la prédiction de la réponse d'un patient à son traitement à partir de son profil génétique. Pour ce faire, nous nous plaçons dans le cadre de l'apprentissage statistique multitâche, qui consiste à combiner les données disponibles pour plusieurs problèmes liés afin de les résoudre simultanément.Nous proposons un nouveau modèle linéaire de prédiction multitâche qui s'appuie sur des descripteurs des tâches pour sélectionner les variables pertinentes et améliorer les prédictions obtenues par les algorithmes de l'état de l'art. Enfin, nous étudions comment améliorer la stabilité des variables sélectionnées, afin d'obtenir des modèles interprétables. / Adverse drug reaction (ADR) is a serious concern that has important health and economical repercussions. Between 1.9%-2.3% of the hospitalized patients suffer from ADR, and the annual cost of ADR have been estimated to be of 400 million euros in Germany alone. Furthermore, ADRs can cause the withdrawal of a drug from the market, which can cause up to millions of dollars of losses to the pharmaceutical industry.Multiple studies suggest that genetic factors may play a role in the response of the patients to their treatment. This covers not only the response in terms of the intended main effect, but also % according toin terms of potential side effects. The complexity of predicting drug response suggests that machine learning could bring new tools and techniques for understanding ADR.In this doctoral thesis, we study different problems related to drug response prediction, based on the genetic characteristics of patients.We frame them through multitask machine learning frameworks, which combine all data available for related problems in order to solve them at the same time.We propose a novel model for multitask linear prediction that uses task descriptors to select relevant features and make predictions with better performance as state-of-the-art algorithms. Finally, we study strategies for increasing the stability of the selected features, in order to improve interpretability for biological applications.

Kontinuerlig infusion med levodopa/karbidopa gel hos patienter med avancerad Parkinsons sjukdom har visat sig vara en effektiv behandling men innebär även komplikationer. Studiens syfte är att kartlägga vilka behandlingskomplikationer som redovisas i litteraturen. Metoden är en systematisk litteraturstudie där databaserna PubMed, Cochrane, Cinahl och Embase har genomsökts. Resultatet grundar sig på 12 observationsartiklar och en randomiserad kontrollerad studie som visar att behandlingskomplikationer är vanliga, de är varierande i allvarlighetsgrad och kan indelas i fyra grupper beroende på om de är relaterade till kirurgi, det tekniska systemet, den medicinska behandlingen eller inte relaterat alls till behandlingen utifrån dagens kunskap. Slutsats: Det vetenskapliga underlaget är otillräckligt för att sammanställa hur de redovisade behandlingskomplikationerna hör ihop med behandlingen. Därför rekommenderas ytterligare forskning där samband kopplat till baslinjevariabler och socioekonomiska variabler samt samband mellan de olika behandlingskomplikationerna att undersökas ytterligare. / Continuous levodopa/carbidopa intestinal gel is reported to be efficient in the treatment of advanced Parkinson Disease but also associated with adverse events. The aim of this study was to provide an overview of the reported adverse events through a systematic review. The databases PubMed, Cochrane, Cinahl and Embase were searched. The results are based on 12 observational studies and one randomized control trial and shows that adverse events are common and the degree varies. Four categories to which the adverse events can be related were identified; due to the surgery, the device, the medication or not related to the treatment at all. Conclusions: The evidence is considered inadequate to base a statement of how the adverse events are correlated to the treatment why further studies with evaluation of baseline and socioeconomic variables as well as among the different adverse events are recommended.

The purposes of this study are: a) to understand the treatments compliance behavior of the patient with chronic disease at the behavioral level, particularly, the relationship between treatments compliance behavior and normative beliefs; b) develop a behavioral model of patient's treatments compliance behavior that could be used for predicting, combating, treating, tracking and controlling the treatments compliance behavior of the patients with chronic disease. Seventy-two patients from senior daycare centers in the Dallas area, who suffer or had suffered from at least, one chronic disease, participated in the study. Data gathering was conducted using paper-based questionnaire. The most significant finding of this study is the relationship between normative beliefs and the treatments compliance behavior of the patient with chronic disease. Normative beliefs were found to have significant impact on the treatments compliance intent and behavior of the patients with chronic disease. Another important finding showed that side-effects of prescribed treatments have little or no influence on the treatments compliance behavior of the patient with chronic disease. A relationship between the effectiveness of medicine, particularly, predictive medicine, and treatments compliance behavior was established. The design of the study was intended to provide coverages for a set of constructs that may be the interacting units in the environment of any chronic disease treatments decision. It depicts relational, information communications links between the constructs. The Imhonde model of treatments compliance behavior was designed to include cultural norms and other beliefs that are significant for real-time human ailments decisions behaviors. It is recommended that further studies may include the use of a larger population of participants from diverse cultures and localities in multiple states and countries, with the object of finding the differences that culture and local environments may have on the normative leaning for treatments compliance behavioral decisions in chronic disease cases.

Indiana University-Purdue University Indianapolis (IUPUI) / Traditional treatment strategy development for diseases involves the identification of target proteins related to disease states, and the interference of these proteins with drug molecules. Computational drug discovery and virtual screening from thousands of chemical compounds have accelerated this process. The thesis presents a comprehensive framework of computational drug discovery using system biology approaches. The thesis mainly consists of two parts: disease biomarker identification and disease treatment discoveries. The first part of the thesis focuses on the research in biomarker identification for human diseases in the post-genomic era with an emphasis in system biology approaches such as using the protein interaction networks. There are two major types of biomarkers: Diagnostic Biomarker is expected to detect a given type of disease in an individual with both high sensitivity and specificity; Predictive Biomarker serves to predict drug response before treatment is started. Both are essential before we even start seeking any treatment for the patients. In this part, we first studied how the coverage of the disease genes, the protein interaction quality, and gene ranking strategies can affect the identification of disease genes. Second, we addressed the challenge of constructing a central database to collect the system level data such as protein interaction, pathway, etc. Finally, we built case studies for biomarker identification for using dabetes as a case study. The second part of the thesis mainly addresses how to find treatments after disease identification. It specifically focuses on computational drug repositioning due to its low lost, few translational issues and other benefits. First, we described how to implement literature mining approaches to build the disease-protein-drug connectivity map and demonstrated its superior performances compared to other existing applications. Second, we presented a valuable drug-protein directionality database which filled the research gap of lacking alternatives for the experimental CMAP in computational drug discovery field. We also extended the correlation based ranking algorithms by including the underlying topology among proteins. Finally, we demonstrated how to study drug repositioning beyond genomic level and from one dimension to two dimensions with clinical side effect as prediction features.

Introduktion: ADHD är en uppmärksamhet -och hyperaktiv störning, där 90 % i Sverige behandlas med det farmakologiska läkemedlet Metylfenidat (MPH). En stor andel med ADHD utvecklar psykiatrisk komorbiditet i form av psykisk ohälsa (frånvaro av mentalt välbefinnande). Patofysiologin hur MPH påverkar hjärnan är okänd och behandlingsformen har diskuterats som bristfällig på grund av förekommande bieffekter. Fysisk aktivitet har föreslagits som ett hälsosammare behandlingsalternativ, då evidens visat att fysisk aktivitet kan förbättra ADHD-symptom och samsjuklighet av psykisk ohälsa. Det finns inga studier som undersökt hur individer med ADHD upplever nuvarande- och önskar behandling. Syftet med denna studie blev därför att undersöka upplevda erfarenheter av ADHD och hur det farmakologiska läkemedlet MPH och fysisk aktivitet upplevs ha påverkat diagnosens symptom och individernas psykiska hälsa samt att ta reda på vilken behandling individerna önskar utifrån deras livserfarenheter. Metoden utgick från ett fenomenologiskt ramverk med hjälp av en deskriptiv kvalitativ tvärsnittsstudie, där data extraherades genom en innehållsanalys med en induktiv ansats. Urvalet selekterades genom snöbollsurval, där inklusionskriteriet var att deltagarna blivit diagnostiserad med ADHD och har erfarenheter av MPH och fysisk aktivitet. Resultatet visade att symptom för ADHD var problematik med koncentration-, hyperaktivitet-, uppmärksamhet- och systematiska svårigheter, där symptom försämrat den psykiska hälsan. Det framgick att både MPH och fysisk aktivitet effektiviserade symptom mot koncentration, hyperaktivitet och uppmärksamhet, varav KBT (kognitiv beteendeterapi) förbättrade systematiska svårigheter. Vidare bidrog MPH med fysiska, mentala och beteendeföränderliga bieffekter som försämrade den psykiska hälsan. Fysisk aktivitet visade däremot förbättra den psykiska hälsan, där inaktivitet framgick som en central nackdel för förvärring av symptom och psykisk hälsa. Deltagarnas önskan var att behandling bör uppföljas och baseras på en överenskommelse som anpassas efter individuella svårigheter och hälsotillstånd. Slutsatsen med studien kom fram till att behandlas med fysisk aktivitet i kombination med KBT skulle vara hälsosammare som första behandling mot samtliga ADHD-symptom och psykisk hälsa. I andra hand var det deltagarnas önskan att applicera MPH vid akut behov, och är därav förslag att forska fram MPH som engångsbehandling som kan användas vid inaktiva tillstånd. Studien kom fram till att inkludering av fler idrottsvetenskapliga tjänster till vård och skola behövs för mer kompetens om vikten av fysisk aktivitet för individer som har ADHD. / Introduction: ADHD is an attention-deficit/hyperactivity disorder, where 90% in Sweden is treated with the pharmacological drug Methylphenidate (MPH). People diagnosed with ADHD develop often psychiatric comorbidity in form of mental illness. The pathophysiology behind how MPH influence the brain is unknown and the treatment have been discussed as deficient due to side effects. Physical activity has been suggested as a healthier treatment option, as evidence shows that physical activity can improve ADHD-symptoms and comorbidity of mental illness. There are no studies that have invastigate how individuals with ADHD experience current- and desired treatment. The aim of this study was therefore to investigate the experiences of having ADHD and how the pharmacological treatment MPH and physical activity has affected the symptoms and mental health, and also find out what treatment the individuals want based on their life experiences. The method was derived from a phenomenological framework using a descriptive qualitative cross-sectional study. Data was analyzed with an inductive approach using an interpretive analysis. Participants was recruited through a snowball selection, where the inclusion criteria stated that participants been diagnosed with ADHD and have experience of MPH and physical activity. The results showed that the frequent occurring symptoms of ADHD were difficulties with concentration-, hyperactivity-, attention- and systematic symptoms, where symptoms had shown a negative effect on the mental health. It appeared that both MPH and physical activity made symptom improvement against concentration-, hyperactivity- and attention difficulties, while CBT (Cognitive Behavioral Therapy) improved systematic difficulties. MPH contributed to side effects that affected physiological-, psychological- and behavioral aspects, which all were perceived to have a negative influence on mental health. In contrast, physical activity improved mental health and showed no evidence of side effects, except when physical activity was absent from daily life. Inactivity appeard to be a central disadvantage for worsening symptoms and mental health. The participants desired that their treatment should be tailored to individual difficulties and health condition in a collaborative way and with follow-up from the health care worker. The study concluded that physical activity in combination with CBT would be a healthier as first treatment option to reduce symptoms of ADHD and improve mental heatlh. Additionally, the participants desired treatment with MPH in form of single doses for urgent need, and it is therefore to suggest development of such treatment option. Furthermore, the study proposes more services for sport science within healthcare and schools for containing applicable knowledge in physical activity for dose with ADHD.