Magister Pharmaceuticae - MPharm / Antimicrobial resistance is a global concern associated with increased morbidity and mortality. It has been estimated that, by 2050, the continuous escalation of antimicrobial resistance, globally, will result in more deaths per year, compared to cancer and diabetes. The direct and indirect impact of ineffective antibiotics, and therefore, antimicrobial resistance, will be hardest felt by low and middle-income countries, as the financial burden will be too great to manage. Carbapenems are considered the last line of antimicrobials to treat multidrug-resistant bacterial infections. They are the preferred choice to treat infections, presenting with extended-spectrum beta-lactamases (ESBL) producing Enterobacteriacea. Various strains of bacteria that have become resistant, due to the selective pressure, as a result of carbapenem over use, are referred to as Carbapenem-resistant Enterobacteriaceae (CRE). / 2022

Contamination is a prevalent issue with reprocessed levered endoscopes. The number of infections caused by resistant enterobacteriaceae in patients due to contaminated endoscopes increased to the point that the United States Food and Drug Administration released a safety alert to health care facilities that perform endoscopic retrograde cholangiopancreatography (ERCP). The purpose of this descriptive project was to evaluate if levered endoscopes used in ERCP procedures met high level disinfection criteria, were properly processed, and were germ free after reprocessing. The project was supported by 2 theories: the middle range theory of patient advocacy and the germ theory. Data (counts and percentages) were collected from testing 150 endoscopes at each of 4 facilities within an organization regarding the effectiveness of the reprocessing of the levered endoscopes. According to the project findings, there was a 7% average germ-free failure rate across the sites after the initial reprocessing. The cleaning process of the levered endoscopes allowed bacteria to remain on the scopes after the manufacturer-recommended cleaning was completed at the sites. Standardization of the organization's cleaning process and improvement in the national protocols were recommended. The project supported protecting the safety of endoscopy patients by identifying that the cleaning process could be improved to prevent introduction of infectious bacteria through a procedure. The results will be informative for laboratory staff who clean levered endoscopes, physicians who use the scopes in patient procedures, patients who undergo the procedures, and nurses who are tasked with improving patient safety in perioperative environments.

Bacteriophages (phages) are the smallest biological entity on the planet. They provide vast amounts of valuable knowledge to biologists. Phage genomes are relatively simple compared to the organisms they infect (prokaryotes) and yet continually point to the complexity surrounding molecular- and microbiological mechanisms of life. By studying phages we can learn of the systems of gene expression, protein interaction and DNA organization. Phages are useful not only from an academic perspective, but may also have useful clinical applications. In the face of the rise of antibiotic-resistant bacterial “super pathogens”, scientists and researchers turn to phages as alternative treatments to these types of infections. Phages are capable of infecting and killing even the deadliest of bacterial pathogens, such as carbapenem-resistant Enterobacteriaceae (CRE) or Bacillus anthracis, and may prove increasingly useful in the future for combatting harmful pathogens. This thesis looks at several aspects of phage biology—from the underlying genetics contributing to phage virulence, to the clinical application of phage therapy to treat infections. First, a look at CRE-Klebsiella pneumoniae isolates and phages capable of infecting some strains may reveal a potential therapeutic approach in the future. Additionally, genomic analysis reveals interesting features that may explain aspects of phage virulence and evolutionary history. Then, a collection of genetically diverse phages is used in infection assays on pathogenic strains of Bacillus anthracis to establish the first-reported phages capable of infecting these strains. Finally, the process of preparing phage samples for therapeutic application is explored in-depth to conclude with discussion of clinical application. During the course of these projects over 25 phages were isolated, as many phage genomes were assembled and annotated, resulting in the preparation of two genome announcements and near-completion of two publishable first-author papers (chapters II and III). In addition, participation in a variety of collaborative efforts may lead to a handful of co-author papers and on various topics, including phage biology and application.

京都大学 / 新制・論文博士 / 博士(工学) / 乙第13581号 / 論工博第4212号 / 新制||工||1990(附属図書館) / (主査)教授 松原 誠二郎, 教授 中尾 佳亮, 教授 浦山 健治 / 学位規則第4条第2項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Background. Carbapenem-resistant Enterobacteriaceae, including Escherichia coli and Klebsiella pneumoniae, are newly emerging pathogens of public health importance. Currently no nationally representative or mandatory surveillance or reporting system exists to examine trends of these important pathogens. Objective. The purpose of the current study was to estimate trends in overall microbial burden and carbapenem resistance in E. coli and K. pneumoniae and to understand the extent to which hospitals which report to voluntary surveillance systems represent all hospitals in the United States. Design. We conducted a descriptive study to compare the hospitals participating in voluntary reporting systems of the University HealthSystem Consortium and the National Healthcare Safety Network with the Healthcare Utilization Project’s Nationwide Inpatient Sample, a nationally representative sample of hospital discharges. Methods. Descriptive analyses examined hospital characteristics (region, bed size, hospital control, teaching status, case mix index) and patient characteristics (age, sex, race/ethnicity, admission source, admission type, discharge status, primary payer) of participant hospitals versus all US hospitals. ICD-9-CM codes identified discharges coded for E. coli and K. pneumoniae diagnoses; linear regression was used to evaluate trends in overall microbial burden of E. coli and K. pneumoniae in all US Hospitals and US Academic Centers. Trends in E. coli and K. pneumoniae resistance to carbapenem were also evaluated in hospitals participating in voluntary surveillance systems (n=13). Results. Between 2002 and 2007, slight increasing trends in burden of both E. coli and K. pneumoniae were observed (E. coli: slope = 0.0537; K. pneumoniae slope = 0.0168). Hospitals participating in voluntary surveillance systems are larger and care for fewer elderly patients than all US hospitals. Conclusions. These results suggest that hospitals that participate in voluntary surveillance systems like the National Healthcare Safety Network and the University HealthSystem Consortium may underrepresent trends in smaller hospitals, as well as those that treat elderly patients. Increasing overall burden of infection due to these isolates only reinforces the importance carbapenem resistance in E. coli and K. pneumoniae. This important public health threat may warrant the creation of a national, mandatory reporting system for these and other antimicrobial resistant organisms.

This work will look at two factors that add to the diversity of carbapenem resistant bacteria. First, it focuses on the diversity of carbapenemase resistance plasmids. 446 plasmids were characterized by size, gene content and replicon groups. We identified that on average, over 30% of the encoded proteins on each plasmid have an unknown function. Plasmid sizes ranged from 1.6kb to 500kb, with an average of around 100kb and median of 80kb. Additionally, six replicon groups account for 80% of all the carbapenemase resistance plasmids. We also highlight the lack of data available for carbapenemase carrying plasmids from bacterial genera other than Escherichia and Klebsiella, and plasmids that carry the New Delhi metallo-β- lactamase or the Verona-integron encoded metallo-β-lactamase. Second, we characterized the β-lactamase diversity of a single carbapenemase resistant Klebsiella pneumoniae. This isolate encodes six distinct β-lactamases, all of which are functional, and three of which are redundant. Additionally, we determined that the CTX-M-15 cephalosporinase imparts a greater fitness when grown in aztreonam (a monobactam) than ceftazidime (a cephalosporin). Finally, we show that individually, these β-lactamases do not account for the elevated levels of resistance seen in the parent strain, indicating that the passive resistance mechanisms (i.e. efflux pumps, altered membrane porins) may play a larger role than originally thought.

[pt] As infecções por bactérias Gram-negativas Resistentes aos Carbapenêmicos (CR-GNB) estão entre as maiores preocupações atuais da área da, especialmente em Unidades de Terapia Intensiva (UTI), e podem estar associadas ao aumento do tempo de hospitalização, morbidade, custos e mortalidade. Esta tese tem como objetivo desenvolver uma abordagem abrangente e sistemática aplicando técnicas de aprendizado de máquina para construir modelos para prever a aquisição de CR-GNB em UTIs de hospitais brasileiros. Propusemos modelos de triagem para detectar pacientes que não precisam ser testados e um modelo de risco que estima a probabilidade de pacientes de UTI adquirirem CR-GNB. Aplicamos métodos de seleção de características, técnicas de aprendizado de máquina e estratégias de balanceamento para construir e comparar os modelos. Os critérios de desempenho escolhidos para avaliação foram Negative Predictive Value (NPV) and Matthews Correlation Coefficient (MCC) para o modelo de triagem e Brier score e curvas de calibração para o modelo de risco de aquisição de CR-GNB. A estatística de Friedman e os testes post hoc de Nemenyi foram usados para testar a significância das diferenças entre as técnicas. O método de ganho de informações e a mineração de regras de associação avaliam a importância e a força entre os recursos. Nosso banco de dados reúne dados de pacientes, antibióticos e microbiologia de cinco hospitais brasileiros de 8 de maio de 2017 a 31 de agosto de 2019, envolvendo pacientes hospitalizados em 24 UTIs adultas. As informações do laboratório foram usadas para identificar todos os pacientes com teste positivo ou negativo para CR-GNB, A. baumannii, P. aeruginosa ou Enterobacteriaceae. Há um total de 539 testes positivos e 7.462 negativos, resultando em 3.604 pacientes com pelo menos um exame após 48 horas de hospitalização. Dois modelos de triagem foram propostos ao tomador de decisão do hospital. O modelo da floresta aleatória reduz aproximadamente 39 por cento dos testes desnecessários e prevê corretamente 92 por cento dos positivos. A rede neural evita testes desnecessários em 64 por cento dos casos, mas 24 por cento dos testes positivos são classificados incorretamente. Os resultados mostram que as estratégias de amostragem tradicional, SMOTEBagging e UnderBagging obtiveram melhores resultados. As técnicas lineares como Regressão Logística com regularização apresentam bom desempenho e são mais interpretáveis; elas não são significativamente diferentes dos classificadores mais complexos. Para o modelo de risco de aquisição, o Centroides Encolhidos Mais Próximos é o melhor modelo com um Brier score de 0,152 e um cinto de calibração aceitável. Desenvolvemos uma validação externa a partir de 624 pacientes de dois outros hospitais da mesma rede, encontrando bons valores de Brier score (0,128 and 0,079) em ambos. O uso de antibióticos e procedimentos invasivos, principalmente ventilação mecânica, são os atributos mais importantes e significativos para a colonização ou infecção de CR-GNB. Os modelos preditivos podem ajudar a evitar testes de rastreamento e tratamento inadequado em pacientes de baixo risco. Políticas de controle de infecção podem ser estabelecidas para controlar a propagação dessas bactérias. A identificação de pacientes que não precisam ser testados diminui os custos hospitalares e o tempo de espera do laboratório. Concluímos que nossos modelos apresentam bom desempenho e parecem suficientemente confiáveis para prever um paciente com esses patógenos. Esses modelos preditivos podem ser incluídos no sistema hospitalar. A metodologia proposta pode ser replicada em diferentes ambientes de saúde. / [en] Infections by Carbapenem-Resistant Gram-negative bacteria (CR-GNB) are among the most significant contemporary health concerns, especially in intensive care units (ICUs), and may be associated with increased hospitalization time, morbidity, costs, and mortality. This thesis aims to develop a comprehensive and systematic approach applying machine-learning techniques to build models to predict the CR-GNB acquisition in ICUs from Brazilian hospitals. We proposed screening models to detect ICU patients who do not need to be tested and a risk model that estimates ICU patients probability of acquiring CR-GNB. We applied feature selection methods, machine-learning techniques, and balancing strategies to build and compare the models. The performance criteria chosen to evaluate the models were Negative Predictive Value (NPV) and Matthews Correlation Coefficient (MCC) for the screening model and Brier score and calibration curves for the CR-GNB acquisition risk model. Friedman s statistic and Nemenyi post hoc tests are used to test the significance of differences among techniques. Information gain method and association rules mining assess the importance and strength among features. Our database gathers the patients, antibiotic, and microbiology data from five Brazilian hospitals from May 8th, 2017 to August 31st, 2019, involving hospitalized patients in 24 adult ICUs. Information from the laboratory was used to identify all patients with a positive or negative test for carbapenem-resistant GNB, A. baumannii, P. aeruginosa, or Enterobacteriaceae. We have a total of 539 positive and 7,462 negative tests, resulting in 3,604 patients with at least one exam after 48 hours hospitalized. We proposed to the hospital s decision-maker two screening models. The random forest s model would reduce approximately 39 percent of the unnecessary tests and correctly predict 92 percent of positives. The Neural Network model avoids unnecessary tests in 64 percent of the cases, but 24 percent of positive tests are misclassified as negatives. Our results show that the sampling, SMOTEBagging, and UnderBagging approaches obtain better results. The linear techniques such as Logistic Regression with regularization give a relatively good performance and are more interpretable; they are not significantly different from the more complex classifiers. For the acquisition risk model, the Nearest Shrunken Centroids is the best model with a Brier score of 0.152 and a calibration belt acceptable. We developed an external validation of 624 patients from two other hospitals in the same network, finding good Brier score (0.128 and 0.079) values in both. The antibiotic and invasive procedures used, especially mechanical ventilation, are the most important attributes for the colonization or infection of CR-GNB. The predictive models can help avoid screening tests and inappropriate treatment in patients at low risk. Infection control policies can be established to control these bacteria s spread. Identifying patients who do not need to be tested decreases hospital costs and laboratory waiting times. We concluded that our models present good performance and seem sufficiently reliable to predict a patient with these pathogens. These predictive models can be included in the hospital system. The proposed methodology can be replicated in different healthcare settings.