The study of predictors of health risk is important to assist professionals in the area in making clinical decisions at the individual or collective level. With focus on the elderly population, in 2005, the Elders Risk Assessment (ERA) was developed in Rochester, MN, USA. Its main advantage over other predictors is the practicality of use, since the data are obtained in an administrative way through the medical record review. Until now, this instrument has not been studied in Brazil. In this sense, this work was developed to use the ERA instrument as a predictor of risk of health problems in the elderly attended at the Hospital Universitário de Santa Maria, RS. The outcomes (events) considered for risk prediction were hospital admissions and urgent/emergency care. From the review of medical records, the ERA scores were obtained from a sample of 135 older adults seen outpatient in the year 2010 and the outcomes were surveyed between 2010 and 2012. Like the original study, the results showed a positive correlation between higher ERA scores and greater number of events. It is concluded that the ERA instrument can be used in our environment as a tool for risk screening for unfavorable events in the health of the elderly. It is also possible to characterize strategies of clinical approach in order to modify the tendency towards unfavorable outcomes. Considering the population cut and the study design chosen, other works are needed to prove the reproducibility of the instrument under different conditions, both in the public health system (SUS) and in the supplementary health. / O estudo de preditores de risco em saúde é importante para auxiliar os profissionais da área na tomada de decisões clínicas no âmbito individual ou coletivo. Com foco na população de idosos, em 2005, foi desenvolvido em Rochester, MN, USA, o instrumento Elders Risk Assessment (ERA). Sua principal vantagem em relação a outros preditores é a praticidade de uso, visto que os dados são obtidos de maneira administrativa através da revisão de prontuário médico. O referido instrumento, até o presente momento, não foi estudado no Brasil. Nesse sentido, esse trabalho foi desenvolvido com o objetivo de utilizar o instrumento ERA como preditor de risco de agravos na saúde de idosos atendidos no Hospital Universitário de Santa Maria, RS. Os desfechos (eventos) considerados para a predição de risco foram internações hospitalares e atendimento em situação de urgência/emergência. A partir da revisão de prontuários médicos, foram obtidos os escores ERA de uma amostra de 135 idosos atendidos ambulatorialmente no ano 2010 e os desfechos foram pesquisados entre os anos 2010 e 2012. À semelhança do estudo original, os resultados demonstraram uma correlação positiva entre escores ERA mais elevados e maior número de eventos. Conclui-se que o instrumento ERA pode ser utilizado em nosso meio como ferramenta de rastreio de risco para eventos desfavoráveis em saúde de idosos. Pode, ainda, balizar estratégias de abordagem clínica com o objetivo de modificar a tendência para desfechos desfavoráveis. Considerando-se o recorte populacional e o desenho de estudo escolhido, novos trabalhos são necessários para comprovar a reprodutibilidade do instrumento em condições distintas, tanto no sistema público de saúde (SUS) quanto na saúde suplementar.

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WN virus has spread for over 60 years creating endemic and epidemic areas throughout Africa, Asia, and Europe, affecting human, bird, and equine populations. Its 1999 appearance in New York shows the ability of the virus to cross barriers and travel great distances, emerging into new territories previously free of infection. Spreading much faster than expected, WN virus has infected thousands of birds, equine, and humans throughout the conterminous United States (US). Case and serological studies performed in the Eastern hemisphere prior to 1999 offer detailed descriptions of endemic and epidemic locations in regards to geography, land cover, land use, population, climate, and weather patterns. Based on the severity of WN activity within each study area, the patterns associated with these environmental factors allow for the identification of values associated with different levels of risk. We can then model the landscape of the disease within the US and identify areas of high risk for infection. State and county public health officials can use this model as a decision-making tool to allocate funding for disease prevention and control. Dynamic factors associated with increased transmission, such as above average temperature and precipitation, can be closely monitored and measures of prevention can be implemented when necessary. In turn, detailed information from higher resolution analyses can be documented to an online GIS (Geographic Information System) that would contribute to a global collaboration on outbreaks and prevention of disease. / Master of Science

Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared to family history has not yet been reported. These studies aim to explore the aggregate impact of multiple genetic variants with small effect sizes on risk prediction in order to provide a clinical interpretation of genetic contributions to AD. Data simulations showed that given AD’s prevalence and heritability, a risk prediction model incorporating all genetic contributions would have an area under the receiver operating characteristic curve (AUC) approaching 0.80, which is often a target AUC for screening. Adding additional environmental factors could increase the AUC to 0.95. Using the Collaborative Study on the Genetics of Alcoholism (COGA) and the Study of Addiction: Genes and Environment (SAGE) GWAS samples, we used several different sources to capture genetic information associated with AD in discovery samples, and then tested genetic sum scores created based on this information for predictive accuracy in validation samples. Scores were assessed separately for single nucleotide polymorphisms (SNPs) associated in candidate gene studies and in GWAS analyses. Candidate gene sum scores did not exhibit significant predictive accuracy, but SNPs meeting less stringent p-value thresholds in GWAS analyses did, ranging from mean estimates of 0.549 for SNPs meeting p<0.01 to 0.565 for SNPs meeting p<0.50. Variants associated with subtypes of AD showed that there is similarly modest and significant predictive ability for an externalizing subtype. Scores created based on all individual SNP effects in aggregate across the entire genome accounted for 0.46%-0.57% of the variance in AD symptom count, and have AUCs of 0.527 to 0.549. Additional covariates and environmental factors that are correlated with AD increased the AUC to 0.865. Family history was a better classifier of case-control status than genetic sum scores, with an AUC of 0.686 in COGA and 0.614 in SAGE. This project suggests that SNPs from candidate gene studies and genome-wide association studies currently have limited clinical validity, but there is potential for enhanced predictive ability with better detection of genetic factors contributing to AD.

We built a system to participate in the eRisk 2019 T1 Shared Task. The aim of the task was to evaluate systems for early risk prediction on the internet, in particular to identify users suffering from eating disorders as accurately andquickly as possible given their history of Reddit posts in chronological order. In the controlled settings of this task, we also evaluated the performance of three different word representation methods: random indexing, GloVe, and ELMo.We discuss our system’s performance, also in the light of the scores obtained by other teams in the shared task. Our results show that our two-step learning approach was quite successful, and we obtained good scores on the early risk prediction metric ERDE across the board. Contrary to our expectations, we did not observe a clear-cut advantage of contextualized ELMo vectors over the commonly used and much more light-weight GloVevectors. Our best model in terms of F1 score turned out to be a model with GloVe vectors as input to the text classifier and a multi-layer perceptron as user classifier. The best ERDE scores were obtained by the model with ELMo vectors and a multi-layer perceptron. The model with random indexing vectors hit a good balance between precision and recall in the early processing stages but was eventually surpassed by the models with GloVe and ELMo vectors. We put forward some possible explanations for the observed results, as well as proposing some improvements to our system.

L’objectif est de tester les associations de marqueurs inflammatoires et lipidiques avec la survenue de cardiopathies ischémiques chez la personne âgée non institutionnalisée. Les analyses sont menées dans une étude cas cohorte dans le cadre de l’étude des 3 Cités. Elle inclut 199 sujets ayant développé un premier évènement coronaire sur 4 ans de suivi et 1086 sujets sans antécédents cardiovasculaires (sous cohorte). Un premier travail suggère que la protéine C-réactive (CRP-US) est un marqueur de risque indépendant des évènements coronaires (risque relatif standardisé du log de la CRP-US=1,27 ; IC95%=1,08-1,64) mais n’améliore pas la prédiction du risque coronaire. Le second travail démontre une hétérogénéité dans l’association des lipides classiques et des apolipoprotéines avec les évènements coronaires selon la prise et la nature du traitement hypolipémiant à l’inclusion. Le troisième travail indique que les apolipoprotéines AI et B100 mais pas le non-HDL cholestérol améliorent significativement la prédiction du risque coronaire sur la base d’indice de reclassification. / The aim was investigate associations of inflammatory and lipids markers with occurrence of ischaemic heart disease (IHD) in community dwelling elderly subjects. Within the Three City Study, a case cohort study was used including 199 subjects with first coronary events over 4 years and 1086 participants free from prevalent cardiovascular disease (random sample). The first paper showed that C-reactive protein was independently associated with IHD (standardized hazard ratio of log CRP-US=1.27; CI95%=1.08-1.64) but did not improve IHD risk prediction beyond usual risk factors. The second paper showed heterogeneity in the association between lipids and apolipoproteins with IHD depending on the use and the type of lipid-lowering therapy (statins or fibrates). Using imputations and reclassification metrics, the third paper suggests that apolipoproteins AI and B100 added significant predictive information beyond usual risk factors for IHD risk prediction.

Background: The prognostic significance of chest pain is well established in patients with coronary artery disease, but still ill defined in primary prevention. Therefore, the aim of our analysis was to assess the prognostic value of different forms of chest pain in a large cohort of primary care subjects under the conditions of contemporary modalities of care in primary prevention, including measurement of serum levels of the biomarker NT-pro-BNP. Design: We carried out a post-hoc analysis of the prospective DETECT cohort study. Methods: In a total of 5570 unselected subjects, free of coronary artery disease, within the 55,518 participants of the cross-sectional DETECT study, we assessed chest pain history by a comprehensive questionnaire and measured serum NT-pro-BNP levels. Three types of chest pain, which were any chest pain, exertional chest pain and classical angina, were defined. Major adverse cardiovascular events (MACEs = cardiovascular death, myocardial infarction, coronary revascularization procedures) were assessed during a 5-year follow-up period. Results: During follow-up, 109 subjects experienced a MACE. All types of reported chest pain were associated with an approximately three-fold increased risk for the occurrence of incident MACEs, even after adjusting for cardiovascular risk factors. Any form of reported chest pain had a similar predictive value for MACEs as a one-time measurement of NT-pro-BNP. However, adding a single measurement of NT-pro-BNP and the information on chest pain resulted in reclassification of approximately 40% of subjects, when compared with risk prediction based on established cardiovascular risk factors. Conclusions: In primary prevention, self-reported chest pain and a single measurement of NT-pro-BNP substantially improve cardiovascular risk prediction and allow for risk reclassification of approximately 40% of the subjects compared with assessing classical cardiovascular risk factors alone.

Objectives: Cardiovascular disease is the leading cause of mortality and morbidity in the developed world. Surgery can improve prognosis and relieve symptoms. Risk prediction models are increasingly being used to inform clinicians and patients about the risks of surgery, to facilitate clinical decision making and for the risk-adjustment of surgical outcome data. The importance of risk prediction models in cardiovascular surgery has been highlighted by the publication of cardiovascular surgery outcome data and the need for risk-adjustment. The overall objective of this thesis is to advance risk prediction modelling in cardiovascular surgery with a focus on the development of models for elective AAA repair and assessment of models for cardiac surgery. Methods: Three large clinical databases (two elective AAA repair and one cardiac surgery) were utilised. Each database was cleaned prior to analysis. Logistic regression was used to develop both regional and national risk prediction models for mortality following elective AAA repair. A regional model to identify the risk of developing renal failure following elective AAA repair was also developed. The performance of a widely used cardiac surgery risk prediction model (the logistic EuroSCORE) over time was evaluated using a national cardiac database. In addition an updated model version (EuroSCORE II) was validated and both models’ performance in emergency cardiac surgery was evaluated. Results: Regional risk models for mortality following elective AAA repair (VGNW model) and a model to predict post-operative renal failure were developed. Validation of the model for mortality using a national dataset demonstrated good performance compared to other available risk models. To improve generalisability a national model (the BAR score) with better discriminatory ability was developed. In a prospective validation of both models using regional data, the BAR score demonstrated excellent discrimination overall and good discrimination in procedural sub-groups. The EuroSCORE was found to have lost calibration over time due to a fall in observed mortality despite an increase in the predicted mortality of patients undergoing cardiac surgery. The EuroSCORE II demonstrated good performance for contemporary cardiac surgery. Both EuroSCORE models demonstrated inadequate performance for emergency cardiac surgery. Conclusions: Risk prediction models play an important role in cardiovascular surgery. Two accurate risk prediction models for mortality following elective AAA repair have been developed and can be used to risk-adjust surgical outcomes and facilitate clinical decision making. As surgical practice changes over time risk prediction models may lose accuracy which has implications for their application. Cardiac risk models may not be sufficiently accurate for high-risk patient groups such as those undergoing emergency surgery and specific emergency models may be required. Continuing research into new risk factors and model outcomes is needed and risk prediction models may play an increasing role in clinical decision making in the future.