Article Annotation: COPD Identification
Worldwide around 65 million people are suffering from a mild to severe form of Chronic Obstructive Pulmonary Disease (COPD). The World Health Organization (WHO) predicts that it will be the third cause of death worldwide in 2020.1 Smoking is the number one cause of COPD. Other causes are exposure to chemical fumes, allergic reactions and in poorer countries in can be a result of cooking fuels in poorly ventilated homes. Because it is caused by exposure to this kinds of stressors over an extended period, COPD is found mainly in older people. It can, but is rarely caused by a genetic alpha-1-antitrypsin (AAt) deficiency.1,2 Read more about COPD here: https://genematics.com/copd/
The complications of this disease are divers and can be found on different levels that impact the human life. Looking at the body itself the disease directly effects the lungs and heart. Medication used to treat COPD, for examples prednisone, can indirectly effect hormone levels, the kidneys and the liver. Additionally, COPD patients more often suffer of depression. The burden of the disease has also effects on a social level. Relationships in which the partner of a patient becomes a caregiver and less participation in social activities due to reduced mobility. Work related problems are more common, as a result of absenteeism due to impaired condition.
PubMed is one of the most used literature search engines by researchers. When you use the search term ‘COPD’ in PubMed we will find 73155 publications.3 By the time you are reading this article this number will undoubtedly have increased.
As a researcher you are usually interested in one of the complications or implications of a disease. With this amount of search hits every researcher, independent of the subject, is facing the same dilemma: how do I find all the related articles, without reading every article? Most researchers use a search strategy to narrow the search. However, it takes time to create and test an effective strategy. Narrowing your search term too much automatically creates the risk that you miss potentially important articles.
With the annotation module developed by Genematics researchers can more easily determine the nature of a study. Depending on whether you are a doctor, biomedical or for instance a toxicologist you can choose the set of annotations that are interesting for you. The module scans dozens of articles in seconds looking for related words. You are looking for a gene that is involved in the development of COPD and an article is mainly yellow? Bingo, you found a related article! Are the first five articles coloured mainly pink, this means that they are most likely about a social impact of COPD and therefore you can skip this one. Easy right?