Published: May 30. The Conversation. Author: Dr Jonathan Kennedy, Data Lab Manager, The National Centre for Population Health & Wellbeing Research
Ankylosing spondylitis (AS) is the second most common type of inflammatory arthritis, often affecting teenagers and young adults. Symptoms of AS can include back pain, stiffness, joint inflammation (arthritis), inflammation where tendons attach to bones (enthesitis), and fatigue. Over time, these symptoms can lead to spinal fusion, which significantly affects quality of life, particularly in young people.
Unfortunately, diagnosing AS can be a lengthy process, taking up to ten years from the onset of symptoms and usually requiring X-rays. The slow progression of the condition, coupled with the lack of a definitive test, contributes to these delays.
However, early detection of the condition can make a tremendous difference, halting the degenerative process and preserving a good quality of life for those affected.
Our study explored the potential of using routinely collected healthcare data from GPs and hospitals, combined with advanced machine learning techniques, to identify AS at an earlier stage.