The Impact of Color Vision Deficiency on the Capability of Ophthalmologists to Diagnose Benign and Malignant Choroidal Tumors

Background: Color vision deficiency (CVD) is an under-reported problem among medical personnel, and its impact is still not well characterized. We aim to assess the impact of CVD among ophthalmologists on the accuracy of diagnosing different benign and malignant choroidal lesions. Methods: This is a cross-sectional study conducted on ophthalmologists. We used a web-based survey to collect responses through professional ophthalmology society social media. The survey included a set of five images for normal fundus, choroidal nevus, circumscribed choroidal hemangioma, choroidal metastasis, and choroidal melanoma, wherein each image simulated the three main types of CVD: protanopia, deuteranopia, and tritanopia, in addition to a non-simulated image. Results: Forty-one participants were included, with a mean age of 40 (±9.2) years. They were 28 (68%) men and 13 (32%) women. Participants showed significantly low accuracy for definite diagnosis for circumscribed choroidal hemangioma, nevus, melanoma, and metastasis when the images simulated protanopia and deuteranopia, but not tritanopia. Nevertheless, participants maintained the capability to recognize the nature of the lesions for both simulated and non-simulated images if they were benign or malignant, thereby ensuring immediate referral for specialized care. The exception was with simulated choroidal nevi images, wherein participants incorrectly assigned simulated protanopia and deuteranopia nevi images to malignant lesions. Conclusion: Protanopia and deuteranopia affected the accuracy of diagnosing several choroidal lesions; however, ophthalmologists with those two simulated CVDs were still able to discriminate between benign and malignant tumors

Anterior Ocular Biometrics as Measured by Ultrasound Biomicroscopy

Background: High frequency ultrasonography (ultrasound biomicroscopy; UBM) is an ophthalmic diagnostic tool that can be used to measure the depth of the anterior segment (ASD), the anterior chamber angle (ACA), as well as thicknesses of the iris and the ciliary body (CB). Methods: The anterior segment dimensions and thicknesses were measured by Sonomed 35-MHz. Results: Measurements for 95 eyes from 52 adults were analyzed. The mean and median ASD and ACA were 2.91, 2.92 ± 0.41 mm and 34.1, 34.3 ± 12.1 degrees, respectively. The angle superiorly was wider than inferiorly (p = 0.04). At the root of the iris, the mid of the iris, and the juxtapupillary edge of the iris, the iris thicknesses (median, mean) were 0.40, 0.41 ± 0.1, 0.50, 0.51 ± 0.1, and 0.70, 0.71 ± 0.1 mm, respectively. The thicknesses of CB and CB together with the ciliary processes (median, mean), were 0.70, 0.71 ± 0.15 mm and 1.36, 1.41 ± 0.15 mm, respectively. The upper quadrant of both the iris and the CB was significantly thicker than the lower quadrant (p = 0.04). Conclusions: Our biometric measurements for the anterior segment can be used as normative data for anterior segment depth and angle and iris and ciliary body thickness in normal eyes

The Willingness of the Healthcare Professionals Working in Healthcare Institutions to Accept the First Dose of COVID-19 Vaccine in Jordan: A National Survey

Health workers play an important part as role models, advocates for vaccination, vaccinators and educators in a community. Furthermore, they are at high risk of being infected with COVID-19 as they are on the frontlines. Thus, this study purposed to determine the willingness of the healthcare professionals working in healthcare institutions to accept the first dose of COVID-19 vaccine in Jordan. A cross-sectional design and a convenience-sampling method were used to recruit the study population from different healthcare sectors. A web-based survey was used to collect data. Findings showed that 1594 healthcare professionals responded and 74% of them were aged less than 45 years. Almost 65% of the respondents were registered nurses and 68.4% of them were married. A total of 94.9% of the participants heard about the COVID-19 vaccine, but only 56.5% of them had had the opportunity to attend lectures/discussions about COVID-19 vaccine. Official government websites were the primary source of obtaining information about COVID-19 (36.3%). The willingness of acceptance rate of COVID-19 vaccine was 63%. There were positive correlations between vaccine acceptance and compliance toward COVID-19 infection control precautions (r = 0.119, p < 0.01), knowledge about COVID-19 (r = 0.256, p < 0.01), age (r = 0.170, p < 0.01), and years of experience (r = 0.105, p < 0.01). Furthermore, age, knowledge, and compliance were significant predictors of the acceptance of the COVID-19 vaccine. Thus, it is necessary to develop specific interventions for healthcare professionals with low acceptance rates and take into consideration the predictors of COVID-19 vaccine acceptance. Further research is needed to explore the factors influencing the refusal of the COVID-19 vaccine by healthcare professionals

Deep Learning Prediction of Response to Anti-VEGF among Diabetic Macular Edema Patients: Treatment Response Analyzer System (TRAS)

Diabetic macular edema (DME) is the most common cause of visual impairment among patients with diabetes mellitus. Anti-vascular endothelial growth factors (Anti-VEGFs) are considered the first line in its management. The aim of this research has been to develop a deep learning (DL) model for predicting response to intravitreal anti-VEGF injections among DME patients. The research included treatment naive DME patients who were treated with anti-VEGF. Patient’s pre-treatment and post-treatment clinical and macular optical coherence tomography (OCT) were assessed by retina specialists, who annotated pre-treatment images for five prognostic features. Patients were also classified based on their response to treatment in their post-treatment OCT into either good responder, defined as a reduction of thickness by >25% or 50 µm by 3 months, or poor responder. A novel modified U-net DL model for image segmentation, and another DL EfficientNet-B3 model for response classification were developed and implemented for predicting response to anti-VEGF injections among patients with DME. Finally, the classification DL model was compared with different levels of ophthalmology residents and specialists regarding response classification accuracy. The segmentation deep learning model resulted in segmentation accuracy of 95.9%, with a specificity of 98.9%, and a sensitivity of 87.9%. The classification accuracy of classifying patients’ images into good and poor responders reached 75%. Upon comparing the model’s performance with practicing ophthalmology residents, ophthalmologists and retina specialists, the model’s accuracy is comparable to ophthalmologist’s accuracy. The developed DL models can segment and predict response to anti-VEGF treatment among DME patients with comparable accuracy to general ophthalmologists. Further training on a larger dataset is nonetheless needed to yield more accurate response predictions

Delayed Intravitreal Anti-VEGF Therapy for Patients During the COVID-19 Lockdown: An Ethical Endeavor

Purpose To assess the impact of Jordanian's Corona Virus Disease (COVID-19) lockdown on visual acuity and macular thickness in patients with macular edema receiving intravitreal injections, and to assess the ethical endeavor of lockdown among serious sight threatening conditions. Patients and Methods This retrospective observational study included patients planned for intravitreal injections who did not complete the planned course before the lockdown (ie, before 20th of March 2020). Data included demographics, indication for the intravitreal injection, corrected distance visual acuity (CDVA), and central macular thickness on Optical Coherence Tomography (OCT) before and after the lockdown. Results One-hundred and sixty-six eyes of 125 patients were studied, 68 (54.4%) patients were males, and the mean (± standard deviation, SD) age was 64.79 (±9.41) years. Mean (±SD) duration of delay in the planned injection was 60.97 (±24.35) days. The change in visual acuity was statistically significant for patients with diabetic macular edema (p= 0.045 improvement), patients with central retinal vein thrombosis (CRVO) (p= 0.05 deterioration), and patients with age-related macular degeneration (AMD) (p= 0.005 deterioration). Of interest, delay of more than 2 months and the previous need for 3 or more injections were significant poor prognostic factors for visual outcome for patients with diabetic macular edema (p=0.027 and 0.045). Conclusion The impact of delay in the scheduled intravitreal injections resulted in variable outcomes depending on the indication. Triaging the urgency of patients should be based on the indication to support the equity principle of bioethics, where those in need are prioritized against others, depending on potential adverse outcome