Takayasu's Arteritis (TA)
What is it?
Takayasu’s arteritis, also called TAK, is a rare form of vasculitis disease involving inflammation in the walls of the largest arteries in the body: the aorta and its main branches. The disease results from an attack by the body’s own immune system, causing inflammation in the walls of arteries. The inflammation leads to narrowing of the arteries, and this can reduce blood flow to many parts of the body.
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Signs & symptoms
Some people develop an initial "inflammatory phase" characterized by systemic illness with signs and symptoms of malaise, fever, night sweats, weight loss, joint pain, fatigue, and fainting. There is also often anemia and marked elevation of the ESR or C-reactive protein (nonspecific markers of inflammation). The initial "inflammatory phase" is often followed by a secondary "pulseless phase". The "pulseless phase" is characterized by vascular insufficiency from intimal narrowing of the vessels manifesting as arm or leg claudication, renal artery stenosis causing hypertension, and neurological manifestations due to decreased blood flow to the brain.
Diagnosis
The diagnosis of Takayasu’s arteritis is based on a combination of factors, including:
- Complete medical history and careful physical exam to exclude other illnesses that may have similar symptoms
- X-rays, which show location and severity of vessel damage
- Procedures to detect blood vessel narrowing or aneurysm, including: Magnetic resonance imaging (MRI), Computed axial tomography (CAT scan) and, Angiography: X-ray pictures of the inside of blood vessels.
Treatment
Most people with Takayasu’s arteritis respond to steroids such as prednisone. Because of the significant side effects of long-term high-dose prednisone use, the starting dose is tapered over several weeks to a dose which controls symptoms while limiting the side effects of steroids.
☝️ This is not a substitute for professional medical advice. Please consult with your physician before making any medical decision.
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Source of Information - We analyze big data of more than 23 million patients de-identified medical records from the following sources:
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