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Purpose: To assess the diagnostic accuracy of forced eyelid closure test (FECT), ice pack test (IPT), repetitive nerve stimulation test (RNS), and acetylcholine receptor (AchR) antibody test in patients with suspected ocular myasthenia. To assess the clinical utility of AchR antibody test in predicting disease progression.Methods: Retrospective cohort study of patients diagnosed with ocular myasthenia at a South-Indian neuro-ophthalmology tertiary eye clinic. Baseline characteristics; ocular myasthenia symptoms; results of FECT, IPT, RNS, and AchR antibody test; and progression time to generalized myasthenia (GM) over 36 months from the time of diagnosis were recorded and analyzed using receiver operator curve analysis, multiple logistic regression, and Kaplan-Meier survival analysis.Results: FECT had a sensitivity of 96.7% (95% CI: 88.5-99.6) and a specificity of 75% (95% CI: 34.9-96.8). Combination of FECT and IPT, using the positivity of at least one test, increased the sensitivity to 98.3% (95% CI: 91-100), reducing the specificity to 50% (95% CI: 15.7-84.3), whereas using the positivity of both tests, we obtained a sensitivity of 71.7% (95% CI: 58.6-82.5) and a specificity of 100% (95% CI: 63.1-100). In the subset of patients with double negative RNS and AchR antibodies, the positive predictive value of combined FECT and IPT (double positive) was 100%. Patients who developed GM were more likely to have a positive AchR antibody test result (P = 0.001).Conclusion: Combined FECT and IPT (double positive) has high diagnostic accuracy even among patients with normal RNS and negative AchR antibodies. Despite low sensitivity, AchR-antibody test has a significant predictive value in disease progression. [ABSTRACT FROM AUTHOR]

Background: Artificial Intelligence (AI) is an area of computer science that encompasses the creation of intelligent machines that work and react like humans. It deals with the development algorithms that seek to simulate human brain and also mimic cognitive functions typically associated with the human mind such as learning and problem solving.Purpose: Do we need artificial intelligence in Glaucoma? Glaucoma is the second most common cause of blindness in the world. Its prevalence was over 60 million in 2010 and over 80 million by 2020. It is so common, yet so easily overlooked. More importantly, about 50% of patients in developed countries and 90% in developing countries are unaware of having glaucoma. Early detection can delay the progression of glaucoma. Hence the time is ripe to advovate glaucoma screening.Synopsis: The application of AI in ophthalmology mainly concentrates on the diseases with a high incidence, such as diabetic retinopathy, age-related macular degeneration, glaucoma, retinopathy of prematurity, age-related or congenital cataract etc AI involves mainly 1. machine learning that are algorithms with the ability to learn without being explicitly programmed and 2. deep learning in which artificial neural networks adapt and learn from vast amounts of data. But there are limitations to screening - such as disparity between ophthalmologist:patient ratio and also the availability of the specialty services. The large amount of data acquired from patients makes it nearly impossible for ophthalmologists to screen them with equal efficacy and consistency.Highlights: AI in glaucoma aims at including factors such as clinical data, genomic data, life style behaviors, risk factors, and medical history to predict the risk of developing glaucoma, help customise the most appropriate management protocol for a given patient, and estimate prognosis and surgical success.Video Link: https://youtu.be/IwYS7wDMhkY. [ABSTRACT FROM AUTHOR]

Thus, I-Verter is a safe, universal, easily disposable, and economical DIY device for lid eversion with a minimum risk of infection.{Figure 1}{Figure 2} Financial support and sponsorship Nil. Dear Editor, In this era of the COVID-19 pandemic, there is a potential risk of transmission of viral infections during lid eversion due to the exposure of ocular fluids such as tears and conjunctival secretions following contact between the examiner's finger and the patient's bare ocular surface.[[1]],[[2]] Lid eversion in deep sockets, madarosis, and pediatric patients are some of the other challenges faced. [Extracted from the article]

Dear Editor, Ocular surgeries are the most commonly performed surgeries worldwide. Cataract surgeries account for more than 50%, with half of them being performed in developing countries.[[1]] Identification and confirmation of patient and surgery details are an essential component of patient safety. Magnification of patient details, biometrics, and IOL power in the case sheet allows easy cross-verification [Figure 1]a and [Figure 1]b. [Extracted from the article]

The article informs about a rare adverse effect, Drug-induced Corneal Endothelial Deposits (DICED), caused by the usage of Tricyclic Antidepressants (TCA) and Selective Serotonin Reuptake Inhibitors (SSRI). Topic include the case study discusses a 25-year-old doctor experiencing glare in both eyes due to the long-term use of antidepressant drugs, highlighting the importance of awareness among physicians, ophthalmological referral, and a thorough risk-benefit analysis in such cases.

Dear Editor, In this era of COVID-19 pandemic, healthcare professionals are at greater risk of infection, despite the use of personal protective equipment. Materials required for making noseband are sponge (15 cm long and 2 cm wide), 1 mm diameter stainless steel wire (19 cm long), thin elastic band, cling film wrap, and super glue. It also reduces aerosol contamination of trial frames, lenses, and instruments like optical coherence tomography, non-contact tomography, Humphrey field analyzer, topography, etc. [Extracted from the article]