Since coronavirus disease 2019 was declared a global pandemic by the World Health Organization, it has become a challenging situation to continue medical education, including in Indonesia. The situation prohibited face-to-face (direct) educational activities in clinical settings, therefore also postponing examinations involving especially procedural skills. Adaptations were urgently needed to maintain the delivery of high-stake examinations to sustain the number of ophthalmology graduates and the continuation of eye health service. Objective structured clinical examination (OSCE) has been one of our widely used method to assess clinical competencies for ophthalmology residents, and is the one method that involves gatherings, close contact of examiners, examinees and patients, therefore the most difficult to adjust. Pandemic challenges brought technical changes in our delivering the OSCE to online, maximizing digital platforms of meetings, while still concerned to guarding the safety of candidates, patients and staffs. OSCE scenarios were also made as timely efficient as possible by changing continuous station models to a cascade one. The purpose of this article is to document our experience in conducting a feasible and reproducible OSCE in this pandemic era filled with limitations.
Fundus image is an image that captures the back of the eye (retina), which plays an important role in the detection of a disease, including diabetic retinopathy (DR). It is the most common complication in diabetics that remains an important cause of visual impairment, especially in the young and economically active age group. In patients with DR, early diagnosis can effectively help prevent the risk of vision loss. DR screening was performed by an ophthalmologist by analysing the lesions on the fundus image. However, the increasing prevalence of DR is not proportional to the availability of ophthalmologists who can read fundus images. It can lead to delayed prevention and management of DR. Therefore, there is a need for an automated diagnostic system as it can help ophthalmologists increase the efficiency of the diagnostic process. This paper provides a deep learning approach with the concatenate model for fundus image classification with three classes: no DR, non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR). The model architecture used is DenseNet121 and Inception-ResNetV2. The feature extraction results from the two models are combined and classified using the multilayer perceptron (MLP) method. The method that we propose gives an improvement compared to a single model with the results of accuracy, and average precision and recall of 91% and 90% for the F1-score, respectively. This experiment demonstrates that our proposed deep-learning approach is effective for the automatic DR classification using fundus photo data.
Background: Injection of Silicon oil (SO) is a standard procedure for vitreous replacement in vitrectomy procedure for retinal detachment cases. It acts as a great tamponading agent for reattachment of retinal breaks or retinal detachment. Despite its minor side effect, SO could cause several complications such as cataract, endothelial decompensation, increased intraocular pressure, and secondary glaucoma. Thus needed to be evacuated after the retinal reattachment is stabilized. Following the evacuation procedure, visual acuity is known to be significantly improved. However, some cases show decreased of visual acuity due to retinal redetachment, optic nerve damage due to secondary glaucoma, hypotony, vitreous hemorrhage, expulsive hemorrhage, and cornea abnormality. Methods: A retrospective descriptive study of retinal detachment patients underwent SO evacuation procedure in Cipto Mangunkusumo Hospital,Results: There were seventy-seven cases of retinal detachment undergoes SO evacuation within the period of September 2017-January 2018. There was an improvement of visual acuity (greater than 6/60) after one month of SO evacuation. Anatomical retinal reattachment was successfully observed in 91% patient. The most occurring complication after SO evacuation includes secondary glaucoma and retinal redetachment.Conclusion: SO evacuation is a standard procedure following a vitrectomy in retinal detachment cases. The evacuation procedure yields in positive benefit for patient in term of visual acuity and anatomical structure.
Introduction: Vitreous hemorrhage is the presence of blood in the vitreous cavity. This condition could impair the visual function and hindered the clinician’s ability to examine the posterior segment of the eye. Pars plana vitrectomy (PPV) not only act as a surgical treatment of choice but also diagnostic procedure. Immediate PPV has the advantage to optimalize visual acuity Methods: Retrospective descriptive study of vitreous hemorrhage patients underwent pars plana vitrectomy in Ciptomangunkusumo Hospital, Indonesia from January to December 2018 Result: There were 160 cases of vitreous hemorrhage cases undergoes pars plana vitrectomy in 2018. Most frequent etiology was proliferative diabetic retinopathy (49.4%). Rebleeding was found only in 8 cases within the period of three months follow up. Final visual acuity was improved in majority of the cases and found to be related to timing of the surgery. Conclusion: Early vitrectomy along with systemic control of underlying factors lead to improvement of visual acuity in vitreous hemorrhage.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.