Evaluation of Epidemiologic Evidence for Primary Adult Brain Tumor Risk Factors Using Evidence-Based Medicine

2006 ◽  
pp. 54-79 ◽  
Author(s):  
James L. Fisher ◽  
Judith A. Schwartzbaum ◽  
Margaret Wrensch ◽  
Mitchel S. Berger
Keyword(s):  
Risk Factors ◽  
Brain Tumor ◽  
Evidence Based Medicine ◽  
Adult Brain ◽  
Evidence Based ◽  
Epidemiologic Evidence ◽  
Tumor Risk ◽  
Based Medicine

scholarly journals Scar Epidemiology and Consequences

2020 ◽  
pp. 45-49
Author(s):  
M. El Kinani ◽  
F. Duteille
Keyword(s):  
Risk Factors ◽  
Functional Impairment ◽  
Evidence Based Medicine ◽  
Genetic Factors ◽  
Evidence Based ◽  
Epidemiological Factors ◽  
Keloid Scars ◽  
Based Medicine

AbstractIn this chapter, after a short reminder of the different scars types, epidemiological factors and risk factors are described. The consequences for the patient of an impairment of healing are multiple: aesthetic discomfort, itching, pain, or even functional impairment, especially in the periarticular area, can lead not only to physical but also to psychological and social repercussions.This chapter focuses on the epidemiology of scars, including hypertrophic and keloid scars. The role of mechanobiology looks major as the pathology may start in specific anatomical locations submitted to excessive tension, and the influence of genetic factors, even if not completely confirmed with evidence-based medicine, is highly suspected.

scholarly journals Skin tears and risk factors assessment: a systematic review on evidence-based medicine

2017 ◽  
Vol 15 (1) ◽  
pp. 38-42 ◽  
Author(s):  
Raffaele Serra ◽  
Nicola Ielapi ◽  
Andrea Barbetta ◽  
Stefano de Franciscis
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Evidence Based Medicine ◽  
Evidence Based ◽  
Skin Tears ◽  
Based Medicine

Achieving good health and well-being in Africa by 2030 using multi-state models, survival analysis, statistical methods for evidence-based medicine, diagnosis and determination of risk factors

2020 ◽  
Vol 36 ◽  
pp. 137-145
Author(s):  
Humphrey E. Misiri
Keyword(s):  
Risk Factors ◽  
Sustainable Development ◽  
Statistical Methods ◽  
Evidence Based Medicine ◽  
Well Being ◽  
Good Health ◽  
Evidence Based ◽  
Based Medicine ◽  
Health And Well Being

Seventeen Sustainable Development Goals (SGDs) were adopted by the World Health Organization (WHO) in 2015 for the 2030 Agenda for Sustainable Development. Sustainable Development Goal 3 (SDG3) is ‘Better health and well-being by 2030’. According to WHO, good health in the context of SDG3 is assessed with respect to the level and distribution of individuals’ and communities’ healthy life, conditions that affect health and well-being and risk factors whose presence would affect health and well-being. The overall aim is that each SDG target is achieved by 2030. In 2018 the WHO used statistical methods to assess the state of health in Africa in the context of SDG3. Their analysis revealed successes and shortfalls towards attaining SDG3. Backed by public health and other activities, statistics play an important role in improving the health and well-being of Africa. This paper explains how statistics can be used to help African countries to attain SDG3, in its role in modeling event histories, diagnosis, evidence-based medicine, determination of risk factors of exposures of morbidity and mortality, determination of risk factors of morbidity and mortality, the computation of the level and distribution of vital events, measuring disease frequency and progress, quantification of life expectancy and monitoring and evaluation.

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