Vitrectomy is an important treatment for vitreoretinal diseases. After half a century of innovation and development, it has made a breakthrough from open type to micro-incision surgery. Minimally invasive vitrectomy has the advantages of wide indications and high cutting efficiency, which greatly improves the safety and efficacy of surgery, and minimizes the occurrence of trauma and complications during surgery. At present, with the development of surgical microscope system, ophthalmic microsurgery robot and other equipment, and the development and application of new artificial vitreous materials, vitrectomy is developing toward minimally invasive, accurate and intelligent development. The further development of vitrectomy innovative technology in the field of ophthalmology is hopeful in the future, so that clinicians can achieve the best surgical results with the minimum damage, and bring better light to patients.
Optical coherence tomography (OCT) is a non-invasive, rapid optical medical imaging modality and has become a hot topic in biomedical research. In recent years, several functional OCTs have emerged, including Doppler OCT, polarization-sensitive OCT, spectroscopic OCT, and optical coherence tomographic elastography, etc. These newer advances in functional OCT broaden the potential clinical application of OCT by providing novel ways to observe and understand tissue activity that cannot be accomplished by other current imaging methodologies.
With the rapid development of artificial intelligence (AI), especially deep learning, AI research in the field of ophthalmology has presented a trend of diversification in disease types, generalization in scenarios and deepening in researches. The AI algorithm has showed a good performance in the studies of diabetic retinopathy, age-related macular degeneration, glaucoma and other ocular diseases, yielding up the great potential of ophthalmic AI. However, most studies are still in their infancy, and the application of ophthalmic AI still faces many challenges such as lack of interpretability for results, deficiency of data standardization, and insufficiency of clinical applicability. At the same time, it should also be noted that the development of multi-modal imaging, the innovation of digital technologies (such as 5G and the Internet of Things) and telemedicine, and the new discovery that retina status can reflect systemic diseases have brought new opportunities for the development of ophthalmic AI. Learn the current status of AI research in the field of ophthalmology, grasp the new challenges and opportunities in its development process, successfully realizing the transformation of ophthalmic AI from research to practical application.
ObjectiveTo investigate the current status of visual disability in people with opportunistic diabetes based on the physical examination center, and explore its related factors. MethodsPeople who went to West China Hospital of Sichuan University (West China Hospital district and Wenjiang hospital district) for physical examination between January 2019 and March 2020 were selected. The subjects were those who had a history of diabetes or fasting blood glucose≥7 mmol/L or glycosylated hemoglobin≥6.5%. They were divided into two groups according to visual acuity. The physical examinees with low vision were the observation group, and the physical examinees with normal vision were the control group (the number of cases was twice that of the observation group). The relevant data of the two groups were observed and compared, and the risk factors of low vision were analyzed by logistic regression. ResultsA total of 1 636 physical examinees with diabetes were included. There were 158 cases in the observation group and 316 cases in the control group. 158 cases (203 eyes) had low vision, and the incidence was 6.20% (203/3272). The main diseases leading to low vision were cataract (92 cases, 58.23%), high myopia (32 cases, 20.25%) and diabetes retinopathy (20 cases, 12.66%). Logistic regression analysis showed that the independent risk factors for low vision were age of diabetes patients, diabetes retinopathy, systolic blood pressure and glycosylated hemoglobin. ConclusionsThe incidence of low vision in diabetes population based on physical examination centers in Chengdu is low. Visual acuity examination should be strengthened for diabetes patients, especially the elderly, with diabetes retinopathy, high systolic blood pressure and glycosylated hemoglobin. Early effective prevention and treatment can reduce the damage to vision caused by diabetes.