Giant cell arteritis (GCA) of the female genital tract is rare with only 30 cases, including this case, documented in the literature. We present a patient who had total abdominal hysterectomy and bilateral salpingo-oophorectomy for an ovarian cyst and on histologic examination GCA involving the arteries of the myometrium, cervical stroma, ovaries and tubes was unexpectedly discovered. Upon questioning of the patient and further investigations it became clear that the patient did have symptoms and signs suggestive of systemic GCA including fatigue, low-grade fever, weight loss and elevated erythrocyte sedimentation rate (ESR). Treatment with oral corticosteroids resulted in rapid and complete recovery. It is concluded that an incidental finding of GCA in the genitalia should alert the clinician to the possibility of systemic GCA. If upon questioning of the patient and further investigations the existence of systemic GCA is confirmed, treatment with corticosteroids should be considered.
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Giant cell arteritis (GCA), a systemic vasculitis affecting large and medium-sized arteries, poses significant diagnostic and management challenges, particularly in preventing irreversible complications like vision loss. Recent advancements in artificial intelligence (AI) technologies, including machine learning (ML) and deep learning (DL), offer promising solutions to enhance diagnostic accuracy and optimize treatment strategies for GCA. This systematic review, conducted according to the PRISMA 2020 guidelines, synthesizes existing literature on AI applications in GCA care, with a focus on diagnostic accuracy, treatment outcomes, and predictive modeling.
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