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These studies suggest that iron deficiency anemia can cause various ophthalmic complications, including central retinal vein occlusion, nonarteritic ischemic optic neuropathy, and branch retinal artery occlusion, and can affect visual processing in children.
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Iron deficiency anemia (IDA) is a prevalent nutritional deficiency that can have significant effects on various bodily functions, including vision. This article explores the relationship between iron deficiency anemia and eye health, highlighting key findings from recent research.
Iron deficiency anemia can lead to severe ophthalmologic complications such as central retinal vein occlusion (CRVO) and nonarteritic ischemic optic neuropathy (NAION). In one study, a 37-year-old woman with mild iron deficiency anemia presented with blurred vision due to CRVO. Her condition improved significantly after thrombolytic treatment and iron supplementation. Another case involved a 50-year-old woman with NAION and severe iron deficiency anemia, whose vision did not improve despite treatment. These cases underscore the importance of recognizing and treating iron deficiency anemia to prevent serious eye complications.
Another rare but serious ocular manifestation of iron deficiency anemia is branch retinal artery occlusion (BRAO). A case study reported a 49-year-old woman with severe iron deficiency anemia who experienced sudden vision loss due to BRAO. Her vision improved after receiving blood transfusions and iron supplementation. This highlights the need for clinicians to consider anemia as a potential cause of retinal vascular occlusions, especially in patients with conjunctival pallor.
Iron deficiency anemia can also affect the visual evoked potential (VEP) in children, which is a measure of the brain's electrical response to visual stimuli. A study found that children with iron deficiency anemia had longer latencies in VEP waves compared to non-anemic children, indicating delayed visual processing. This delay was negatively correlated with the severity of anemia, emphasizing the need for early detection and prevention of iron deficiency in growing children.
Recent advancements in machine learning have enabled non-invasive detection of iron deficiency anemia through the analysis of images of the conjunctiva, palm, and fingernails. A study comparing various machine learning models found that the convolutional neural network (CNN) achieved the highest accuracy in detecting anemia, demonstrating the potential of these technologies in clinical settings.
Iron deficiency anemia can have profound effects on eye health, leading to conditions such as CRVO, NAION, and BRAO, as well as delayed visual processing in children. Early detection and treatment of iron deficiency anemia are crucial to prevent these serious complications. Advances in non-invasive diagnostic techniques offer promising tools for early identification and management of this condition. Clinicians should remain vigilant for ophthalmologic manifestations in patients with iron deficiency anemia to ensure timely and effective treatment.
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