Incremental innovations in operation theaters

Background: The field of ophthalmology has been built upon continuous innovations. COVID?19 pandemic has been an important driving force behind many innovations in ophthalmology and other branches of medicine. Innovations in ophthalmology has been a key to surgical progress. The process of promoting innovation in surgery is imperative in the evolving practice of ophthalmology. Purpose: In this video we demonstrate some incremental innovations in operation theaters which help in increasing the efficiency and improving the performance of a surgeon. These innovations also provide a more comfortable environment for the patient undergoing the surgery. Synopsis: A few incremental innovations that are described in our video also help in preventing the spread of COVID infection during surgery. This video also showcases a few wet lab innovations that help train residents in their surgical skills. Highlights: Use and reuse of simple materials make it cost effective and ecofriendly. These incremental innovations help in the smooth running of operation theaters. Thus, they are small improvements in the existing setup and help in creating a smooth and error free OT flow

Analysis of motivating factors for eye donation among families of eye donors in South India – A questionnaire-based study

Purpose: To report the factors influencing eye donation among families of successful eye donors in India. Methods: The consenting family members of 434 deceased individuals who donated eyes between April 2019 and March 2020 were retrospectively interviewed via a telephonic questionnaire survey. Details regarding the donors and their families, motivating factors for eye donation, and time taken for tissue recovery were collected and analyzed. Results: The mean age of donors was 66.8 years, and only 13.9% of them had pledged to donate their eyes before death. For 62.3% of donations, children of donors were the primary consenters for eye donation. In 18.8% of donors, there was a previous history of eye donation in the family. Many donations were motivated by a non?governmental organization volunteer (40.5%) or by a grief counselor at the hospital (27.4%). Hospital?based corneal retrieval programs and donations where the first eye bank contact was made through hospital personnel had the greatest percentage of rapid enucleations (performed within 3 h after death) (48.7% and 49.1%, respectively; P = 0.001 and P = 0.02, respectively). Conclusion: Children of donors, typically in the working?age group, most often make the decision for donation, and hence, future awareness programs should focus on this specific population. All types of hospitals should advocate for eye donation as they are a common point of contact for a grieving family, and health?care professionals at all levels should be considered for training as motivators for eye donation.

Effectiveness of Laser Fluorescence–Based Device in Detecting the Extent of Re-Mineralisation in Primary Teeth Compared to the Conventional Method: An In vitro Study

Background: Laser fluorescence (LF)–based clinical device DIAGNOdent™ is at present being used to detect caries. Can the same be used to detect therapeutic remineralisation of early white spot lesions? Aims: To explore the feasibility of using LF?based device in monitoring the changes following remineralisation of demineralised primary teeth. Materials and Method: The sample number for the present experimental in vitro study was 10. The LF based device readings were correlated with surface microhardness (SMH) test values to evaluate its efficiency. SMH analysis was performed using a microhardness tester (Tescol?HT1000AD). All the samples were demineralised, followed by remineralisation using fluoride varnish and pH cycling. The data was analysed using the Statistical Package for the Social Sciences (SPSS) version 17.0 (IBM SPSS®) software. Paired t?test was performed to compare laser fluorescence readings and SMH test result values at baseline, after demineralisation, and after remineralisation. Pearson’s correlation was used to compare the relation between the laser fluorescence and SMH test. Results: A good negative correlation was seen between the two methods at the baseline readings even though it was not statistically significant (P = 0.069). A positive correlation between the methods existed following demineralisation which was not significant (P = 0.074). The correlation between the parameters following remineralisation showed a moderate negative correlation but was not significant (P = 0.55). Conclusion: DIAGNOdent™ values at baseline, after demineralisation, and after remineralisation was consistent with SMH values. Thus, DIAGNOdent™ can be explored to provide chairside assistance in identifying remineralisation of white spot lesions.

Artificial intelligence in glaucoma

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.