RESUMEN
Glaucoma, a prevalent and debilitating eye disease, has long been associated with vision impairment and blindness. However, recent research has shed light on the often-underestimated psychological dimensions of this condition. Anxiety and depression, two pervasive psychiatric comorbidities, have been increasingly recognized among glaucoma patients. This comprehensive review aims to explore the intricate relationship between psychiatry and ophthalmology, in the context of managing depression and anxiety in glaucoma patients. By meticulously examining peer-reviewed literature, we synthesize current knowledge on the prevalence, risk factors, and underlying mechanisms of anxiety and depression in glaucoma. The evidence reveals that glaucoma patients face an elevated risk of experiencing these mood disorders. Factors such as progressive vision loss, complex medication regimens, and the fear of further visual deterioration contribute to their vulnerability. Moreover, we delve into the bidirectional relationship between glaucoma and mood disorders, shedding light on the complex interplay between ocular and emotional health. Our review investigates the implications of anxiety and depression on glaucoma management, including their potential impact on treatment adherence, disease progression, and overall quality of life. We also explore the neurobiological pathways linking glaucoma and mood disorders, providing a foundation for future research and potential therapeutic interventions. In conclusion, recognizing the psychological burden carried by glaucoma patients is essential for holistic and patient-centered care. This review underscores the pressing need for integrated approaches that bring together ophthalmological and psychiatric expertise to optimize the well-being of individuals facing the challenges of glaucoma. By addressing anxiety and depression in glaucoma care, healthcare providers can enhance the overall quality of life for these patients, ultimately leading to improved outcomes and a brighter future for those affected by this condition. This review offers valuable insight for healthcare practitioners and researchers, providing a concise overview of key topics and research in the field of managing depression and anxiety in glaucoma patients.
RESUMEN
This comprehensive review embarks on a captivating journey into the complex relationship between cardiology and normal-tension glaucoma (NTG), a condition that continues to baffle clinicians and researchers alike. NTG, characterized by optic nerve damage and visual field loss despite normal intraocular pressure, has long puzzled clinicians. One emerging perspective suggests that alterations in ocular blood flow, particularly within the optic nerve head, may play a pivotal role in its pathogenesis. While NTG shares commonalities with its high-tension counterpart, its unique pathogenesis and potential ties to cardiovascular health make it a fascinating subject of exploration. It navigates through the complex web of vascular dysregulation, blood pressure and perfusion pressure, neurovascular coupling, and oxidative stress, seeking to uncover the hidden threads that tie the heart and eyes together in NTG. This review explores into the intricate mechanisms connecting cardiovascular factors to NTG, shedding light on how cardiac dynamics can influence ocular health, particularly in cases where intraocular pressure remains within the normal range. NTG's enigmatic nature, often characterized by seemingly contradictory risk factors and clinical profiles, underscores the need for a holistic approach to patient care. Drawing parallels to cardiac health, we examine into the shared vascular terrain connecting the heart and the eyes. Cardiovascular factors, including systemic blood flow, endothelial dysfunction, and microcirculatory anomalies, may exert a profound influence on ocular perfusion, impacting the delicate balance within the optic nerve head. By elucidating the subtle clues and potential associations between cardiology and NTG, this review invites clinicians to consider a broader perspective in their evaluation and management of this elusive condition. As the understanding of these connections evolves, so too may the prospects for early diagnosis and tailored interventions, ultimately enhancing the quality of life for those living with NTG.
RESUMEN
Purpose: For diagnosing glaucomatous damage, we have employed a novel convolutional neural network (CNN) from TrueColor confocal fundus images to conquer the black box dilemma in artificial intelligence (AI). This neural network with CNN architecture with human-in-the-loop (HITL) data annotation helps not only in diagnosing glaucoma but also in predicting and locating detailed signs in the glaucomatous fundus, such as splinter hemorrhages, glaucomatous optic atrophy, vertical glaucomatous cupping, peripapillary atrophy, and retinal nerve fiber layer (RNFL) defect. Methods: The training was done on a well-curated private dataset of 1,400 high-resolution confocal fundus images, out of which 1,120 images (80%) were used exclusively for training and 280 images (20%) were used exclusively for testing. A custom trained You Only Look Once version 5 (YOLOv5)-based object detection methodology was used to identify the underlying conditions precisely. Twenty-six predefined medical conditions were annotated by a team of humans (comprising two glaucoma specialists and two optometrists) by using the Microsoft Visual Object Tagging Tool (VoTT) tool. The 280 testing images were split into three groups (90,100, and 90 images) for three test runs done once every 15 days. Results: Test results showed consistent increments in the accuracy, from 94.44% to 98.89%, in predicting the glaucoma diagnosis along with the detailed signs of the glaucomatous fundus. Conclusion: Utilizing human intelligence in AI for detecting glaucomatous fundus images by using HITL machine learning has never been reported in the literature before. This AI model not only has good sensitivity and specificity in accurate glaucoma predictions but is also an explainable AI, thus overcoming the black box dilemma.