Another PhD studentship funded, please follow the link below. http://www.findaphd.com/search/showproject.asp?projectid=24843&inst=EANG-HEAL&searchtype=i&theorder=2&page=1 Here is the background to the project: Improving the prognostic accuracy of risk stratification scoring systems in community-acquired pneumonia. Community-acquired pneumonia is extremely common and associated with significant mortality. Several scoring systems have been used to estimate the severity or prognosis in patients presenting with community-acquired pneumonia. We have done some preliminary work on comparing the properties of the most commonly used pneumonia severity scales (Pneumonia Severity Index, and CURB-65 which is recommended by the British Thoracic Society), and have identified a number of weaknesses in the existing scoring systems. For instance, many patients with good outcomes were initially wrongly classified as ‘severe’ by the Pneumonia Severity Index. In contrast, some patients classified as non-severe’ by the CURB-65 turned out to have poor outcomes. We have now set up a multi-centre collaborative effort with 5 other international centres (US, Canada, Spain, Hong Kong) to improve the existing prognostic scoring systems. The research collaboration partners will take part in a shared evaluation of anonymised datasets on all their pneumonia patients, thus making available a cohort of about 10 000 patients. Additionally, we may possibly be able to gather data on biomarkers that have been measured as a means of predicting severe pneumonia. This should lead to the development of an improved prognostic scoring system for evaluating patients with pneumonia. For an informal inquiry, contact either Dr Musonda, Dr Myint, or Dr Looke via the website link above. Patrick Musonda, BSc(Hons), MSc(Medstats), PhD Honorary Lecturer Medical Statistician University of East Anglia Norwich NR4 7TJ 01603 591367 Emails: [log in to unmask] 2: [log in to unmask] 3: [log in to unmask] _________________________________________________________________ http://clk.atdmt.com/UKM/go/195013117/direct/01/ You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.