<p>The aim was to contribute to the optimal use of the resting ECG by exploring, in middle-aged and elderly men, the development and regression of ECG abnormalities; the prognostic value of the ECG for cardiovascular disease compared to conventional risk factors; and the impact of age at baseline and follow-up time for prediction of cardiovascular disease.</p><p>It was based on the Uppsala Study of Adult Men cohort that was started in 1970. Participants were examined at ages 50, 70, 77, and 82, with annual updates on mortality and in-hospital morbidity using national registries. </p><p>The studies indicated that the prevalence of silent MI and frequency of regression of major Q/QS patterns may be higher than previously believed. Considering that persistent T wave abnormalities and ST segment depression carried twice as high a risk for future cardiovascular disease (CVD) mortality as new or reverted abnormalities, the results suggested that serial electrocardiograms (ECG) would contribute to proper risk assessment. Also, the inclusion of ischemic ECG findings significantly increased the predictive power of the Framingham score at age 70 for CVD. </p><p>While hypertension and dyslipidemia were consistent long-term risk factors for myocardial infarction at ages 50 and 70, the length of follow-up period and age at baseline affected the predictive power of ECG abnormalities, fasting insulin, BMI, and smoking. </p><p>For stroke, midlife values for blood pressure and ECG abnormalities retained prognostic value over long follow-up periods, even though they improved when re-measured in elderly participants. ApoB/apoA1 ratio, driven by apoA1, was associated with stroke in elderly but not middle-aged men. Hyperinsulinemia and diabetes mellitus were more specifically associated with ischemic stroke than with any-cause stroke. </p><p>In summary, the resting ECG carried prognostic information beyond conventional risk factors. Even though the low prevalence of ECG abnormalities at the age of 50 calls into question the role of the ECG as a screening tool, the additional risk information it carries with it justifies its regular and repeated registration above the age of 50. </p>

The aim was to contribute to the optimal use of the resting ECG by exploring, in middle-aged and elderly men, the development and regression of ECG abnormalities; the prognostic value of the ECG for cardiovascular disease compared to conventional risk factors; and the impact of age at baseline and follow-up time for prediction of cardiovascular disease. It was based on the Uppsala Study of Adult Men cohort that was started in 1970. Participants were examined at ages 50, 70, 77, and 82, with annual updates on mortality and in-hospital morbidity using national registries. The studies indicated that the prevalence of silent MI and frequency of regression of major Q/QS patterns may be higher than previously believed. Considering that persistent T wave abnormalities and ST segment depression carried twice as high a risk for future cardiovascular disease (CVD) mortality as new or reverted abnormalities, the results suggested that serial electrocardiograms (ECG) would contribute to proper risk assessment. Also, the inclusion of ischemic ECG findings significantly increased the predictive power of the Framingham score at age 70 for CVD. While hypertension and dyslipidemia were consistent long-term risk factors for myocardial infarction at ages 50 and 70, the length of follow-up period and age at baseline affected the predictive power of ECG abnormalities, fasting insulin, BMI, and smoking. For stroke, midlife values for blood pressure and ECG abnormalities retained prognostic value over long follow-up periods, even though they improved when re-measured in elderly participants. ApoB/apoA1 ratio, driven by apoA1, was associated with stroke in elderly but not middle-aged men. Hyperinsulinemia and diabetes mellitus were more specifically associated with ischemic stroke than with any-cause stroke. In summary, the resting ECG carried prognostic information beyond conventional risk factors. Even though the low prevalence of ECG abnormalities at the age of 50 calls into question the role of the ECG as a screening tool, the additional risk information it carries with it justifies its regular and repeated registration above the age of 50.

Increases in cases of diarrheal disease, respiratory infections and pregnancy complications have been reported in the literature following floods caused by heavy rainfall. Analyzing the association between health records of outcomes related to flooding demarcated by satellite observations will be helpful to evaluate the use of satellite observed products in the mitigation of health risks for future flood events. The Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI), a relative index assigned to census tracts, measures sociodemographic factors that may affect the ability of communities to prepare for, respond to, and recover from extreme weather events. This index, which quantifies social vulnerability is expected to have a positive relationship with health outcomes associated with flooding. This study uses an inundation map created using observations from active remote sensing satellites to classify census tracts that were flooded after the historic rainfall caused by Hurricane Harvey in Texas in 2017. The duration or period of the inundation was determined using United States Geological Survey (USGS) stream gauge data. A controlled before and after study design was used, and the relative risk (RR) of 11 cause-specific emergency department (ED) visits among the flooded census tracts compared to non-flooded tracts during and after the flood period was modelled using modified Poisson regression while adjusting for a baseline period and the age, ethnicity, race and sex of the patient. Further modification of this relationship by social vulnerability, as measured by CDC SVI quartiles, was examined. The results of this study show that flooding was associated with an increase in ED visits related to carbon monoxide poisoning, insect bites, dehydration, hypothermia, intestinal infectious diseases, and pregnancy complications during the flood period. The average rate of ED visits related to pregnancy complications and insect bites were greater among the flooded tracts compared to the non-flooded tracts in the month following the inundation. Modification of this association by CDC SVI was observed in some cases, such that ED visits were higher or lower in census tracts within higher vulnerable quartiles compared to the least vulnerable quartile. Evaluating the usefulness of earth observations and the CDC SVI in estimating the health risk associated with floods due to Hurricane Harvey has provided understanding the use of these products for future flooding events in identifying specific communities with increased health risks during and following flooding events. / Master of Science / Studies have shown that flooding following heavy rains might increase cases of flood-related health outcomes such as diarrhea, respiratory infections and pregnancy complications among the people in flooded communities. With advancements in satellite technology and image processing, areas that are flooded can be mapped using images captured by satellites within a few days after the flooding. Such maps can then be used to identify communities that might experience greater health risks due to the flooding. This study evaluated the use of such an inundation map created after Hurricane Harvey's floods of 2017 to determine the health risk among the flooded communities with respect to the non-flooded communities. We found that the census tracts that were identified as flooded using the inundation map experienced a greater number of ED visits related to carbon monoxide poisoning, insect bite, dehydration, hypothermia, intestinal infectious diseases, and pregnancy complications compared to the non-flooded census tracts during the period of 19 days after the landfall of Hurricane Harvey. Also, the month following this period, ED visits related to pregnancy complications and insect bites were still greater among the flooded tracts compared to the non-flooded tracts. As the socio-economic status, housing and transportation quality vary among different communities, the association between flooding and the health of the people in different communities may also differ. The Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI) is a relative vulnerability value assigned to each census tract based on the social characteristics of the population that influence the ability to prevent human suffering and financial loss in a disaster. We analyzed how census tracts grouped as very high, high and moderate vulnerability based on the SVI differ from least vulnerable census tracts in terms of this association. The results show that the association differs between different vulnerability groups for total ED visits and ED visits related to insect bites, intestinal infectious diseases and dehydration. We conclude that the satellite-based products along with the CDC SVI might be useful in identifying communities that might need support to overcome health risks following flooding.

L'étude de la survie nette des patients atteints de cancer en population générale permet d'apprécier l'efficience globale du système de soin d'un pays. La survie nette se définit comme la survie qui serait observée si la seule cause de décès possible était le cancer. Ce concept est fondamental dans les comparaisons entre zones géographiques et/ou périodes de diagnostic dont l'intérêt est d'estimer les variations spécifiques de la mortalité due au cancer. Le concept de survie nette permet de prendre en compte les éventuelles différences de mortalité naturelle entre les groupes comparés. Actuellement, seuls deux outils estiment la survie nette sans biais : l'estimateur non paramétrique de Pohar-Perme et la modélisation paramétrique ajustée sur certaines covariables (essentiellement l'âge). Par ailleurs, les outils paramétriques s'étant perfectionnés, de nouveaux modèles flexibles permettent de modéliser les effets complexes des variables sur la mortalité. Ce travail repose sur la modélisation du taux de mortalité en excès à la suite d'un lymphome malin non hodgkinien, en se basant sur le modèle proposé par Remontet et al. et sur la nécessité de modéliser conjointement les effets complexes des covariables (telles que le temps de suivi, l'année de diagnostic et l'âge) sur la mortalité à l'aide d'une stratégie de modélisation adaptée. L'effet des variables est restitué sur la survie nette mais aussi sur le taux de mortalité en excès ce qui représente un élément nouveau dans les études de survie. Deux applications ont été menées sur des bases de données collaboratives de population : d'une part sur les données françaises du réseau FRANCIM à la suite d'un diagnostic de lymphome folliculaire entre 1995 et 2010 et, d'autre part, sur les données européennes d'EUROCARE-5 après un lymphome folliculaire ou un lymphome B diffus à grandes cellules diagnostiqué entre 1996 et 2004. Les résultats montrent que la dynamique du taux de mortalité en excès au cours du temps de suivi varie en fonction du sous-type de lymphome, de l'âge et de la zone géographique. Les tendances de cette dynamique en fonction de l'année de diagnostic sont également différentes / The net survival of cancer patients in population studies is the most relevant indicator to assess the overall efficiency of the healthcare system of a country. Net survival is defined as the survival that would be observed if the sole cause of death were cancer. This concept is crucial in comparative studies (between geographical areas and/or periods of diagnosis) that estimate specific variations of cancer-related deaths. Net survival takes into account potential differences in mortality patterns between groups. Currently, two methods provide unbiased estimations of net survival: the non-parametric estimator of Pohar-Perme and the parametric model adjusted on specific covariates (mainly, the age at diagnosis). Moreover, new improved parametric tools, such as flexible models, can model the complex covariate effects on mortality. In this work, we modeled the excess mortality rate after a non Hodgkin lymphoma diagnosis, with a model developed by Remontet et al. In addition, we used an appropriate model-building-strategy to model jointly the complex effects of some covariates (such as the time elapsed since diagnosis, the year of diagnosis, and age) on the excess mortality. Finally, this approach allowed for the covariate effects on the net survival and on the excess mortality rate. We applied this method to two different collaborative databases: first on the French database FRANCIM (1995 to 2010) to study the excess mortality after diagnosis of follicular lymphoma, then on the European data of EUROCARE-5 (1996 to 2004) to study the excess mortality after diagnosis of follicular lymphoma and diffuse large B-cell lymphoma. According to the results, the dynamics of the excess mortality rate varies over the time elapsed since diagnosis according to the lymphoma subtype, the age, and the geographical area. The trends of these dynamics over the years of diagnosis are different too