ObjectivesTo describe ocular injuries caused by badminton and to explore the implications for future prevention strategies.MethodsWe enrolled 85 patients with ocular trauma caused by badminton. Information collected from patients included type of game, instigator, instrument of injury and lessons in badminton from a professional, and ocular trauma information such as type of injury, treatment and final outcomes.ResultsThe 85 patients (52 men, 33 women) were aged 15–65 years with an average age of 42.9 (±10.7) years. In 60 cases the player was hit by a shuttlecock and in 25 the player was hit by a racquet. 73 cases occurred in doubles matches and 10 in singles matches. In 31 cases the trauma was caused by an opponent and in 52 cases by a partner; 2 cases involved bystanders, not players. About 70% (43/61) of the injured and 82% (40/49) of the instigators had not received badminton lessons from a professional. 80 injuries were non-penetrating and 5 were penetrating. There were 58 cases with hyphaema, 36 with secondary glaucoma, 23 with lens subluxation and 2 with retinal detachment. Surgery comprised phacoemulsification or lensectomy and vitrectomy in 16 cases, silicone oil tamponade in 2 cases, trabeculectomy in 3 cases and direct cyclopexy in 5 cases.ConclusionThe vast majority of the badminton related eye injuries occurred among doubles players and were instigated by the injured person’s partner. Non-penetrating injury was more frequent; penetrating injury was usually more serious. We recommend that badminton players use protective eyewear and receive safety education and professional coaching/instruction on techniques to protect against serious eye injuries.
Purpose Automatic multilabel classification of multiple fundus diseases is of importance for ophthalmologists. This study aims to design an effective multilabel classification model that can automatically classify multiple fundus diseases based on color fundus images. Methods We proposed a multilabel fundus disease classification model based on a convolutional neural network to classify normal and seven categories of common fundus diseases. Specifically, an attention mechanism was introduced into the network to further extract information features from color fundus images. The fundus images with eight categories of labels were applied to train, validate, and test our model. We employed the validation accuracy, area under the receiver operating characteristic curve (AUC), and F1-score as performance metrics to evaluate our model. Results Our proposed model achieved better performance with a validation accuracy of 94.27%, an AUC of 85.80%, and an F1-score of 86.08%, compared to two state-of-the-art models. Most important, the number of training parameters has dramatically dropped by three and eight times compared to the two state-of-the-art models. Conclusions This model can automatically classify multiple fundus diseases with not only excellent accuracy, AUC, and F1-score but also significantly fewer training parameters and lower computational cost, providing a reliable assistant in clinical screening. Translational Relevance The proposed model can be widely applied in large-scale multiple fundus disease screening, helping to create more efficient diagnostics in primary care settings.
Objective: To determine whether pars plana vitrectomy (PPV) combined with the internal limiting membrane (ILM) peeling technique improves the anatomic and functional outcomes of refractory diabetic macular oedema (DME) in comparison with PPV alone. Methods: All relevant articles published in English were retrieved from PubMed, google scholar, web of Science, scopes, and Cochrane library databases between January 1st 1990 and September 28 2022. The meta-analysis was conducted using the Statistical software R 4.2.2. Results: Among 709 articles that were initially identified, 10 studies involving 1126 eyes with DME were found to be eligible for this meta-analysis and systematic review. Our results revealed that postoperative best corrected visual acuity (BCVA) was better in the non-peeling group than in the ILM peeling group (MD=-0.08, 95% CI: -0.12, -0.04, p<0.001), the improvement of BCVA was not significant between the two groups (RD=5.59, 95% CI: -4.81, 15.99, p=0.13). The random effects model showed that changes in central macular thickness were not significantly different between the ILM peeling group and the non-ILM peel group (MD=23.10, 95% CI: -53.82, 100.02, p=0.56). Conclusion: The functional and morphological clinical outcomes in the non-inferior group are equal to that of the ILM peeling group. Yet, further large-scale prospective, randomized, controlled trials are warranted to further validate the reported results.
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