Ocular effects of exposure to low-humidity environment with contact lens wear: A pilot study.

PURPOSE: To compare the ocular effects of exposure to a low-humidity environment with and without contact lens (CL) wear using various non-invasive tests. METHODS: Fourteen habitual soft CL wearers were exposed to controlled low humidity (5% relative humidity [RH]) in an environmental chamber for 90 min on two separate occasions. First, when wearing their habitual spectacles and then, on a separate visit, when wearing silicone hydrogel CLs that were fitted specifically for this purpose. All participants had adapted to the new CL prior to data collection. Three non-invasive objective measurements were taken at each visit: blinking rate, objective ocular scatter (measured using the objective scatter index) and ocular surface cooling rate (measured using a long-wave infrared thermal camera). At each visit, measurements were taken before the exposure in comfortable environmental conditions (RH: 45%), and after exposure to environmental stress (low humidity, RH: 5%). RESULTS: CL wearers showed increased blinking rate (p < 0.005) and ocular scatter (p = 0.03) but similar cooling rate of the ocular surface (p = 0.08) when compared with spectacle wear in comfortable environmental conditions. The exposure to low humidity increased the blinking rate significantly with both types of corrections (p = 0.01). Interestingly, ocular scatter (p = 0.96) and cooling rate (p = 0.73) were not significantly different before and after exposure to low humidity. There were no significant two-way interactions between correction and exposure in any of the measurements. CONCLUSIONS: CLs significantly increased the blinking rate, which prevented a quick degradation of the tear film integrity as it was refreshed more regularly. It is hypothesised that the increased blinking rate in CL wearers aids in maintaining ocular scatter quality and cooling rate when exposed to a low-humidity environment. These results highlight the importance of blinking in maintaining tear film stability.

Visual performance of new affordable and auto-adherent lenses for presbyopia correction.

Presbyopia is a visual condition that affects all of us, evolving with time, reducing the range of accommodation and the ability to work at near. Reading glasses, bifocals or multifocal lenses are the most common solutions. In this work, we demonstrate the near visual performance of new elastomeric auto-adherent lenses developed for the correction of presbyopia. Visual acuity and contrast sensitivity were measured in 10 presbyopic subjects. The results showed that wearing either conventional trial ophthalmic lenses or the new elastomeric lenses provided similar visual quality. These elastomeric lenses can be placed in, or removed from the distance-vision spectacles of the wearers, providing an affordable solution for correcting presbyopia at its clinical onset, which might be especially useful in subjects with different refractive error in each eye and for those with astigmatism.

Are artificial intelligence chatbots a reliable source of information about contact lenses?

INTRODUCTION: Artificial Intelligence (AI) chatbots are able to explain complex concepts using plain language. The aim of this study was to assess the accuracy of three AI chatbots answering common questions related to contact lens (CL) wear. METHODS: Three open access AI chatbots were compared: Perplexity, Open Assistant and ChatGPT 3.5. Ten general CL questions were asked to all AI chatbots on the same day in two different countries, with the questions asked in Spanish from Spain and in English from the U.K. Two independent optometrists with experience working in each country assessed the accuracy of the answers provided. Also, the AI chatbots' responses were assessed if their outputs showed any bias towards (or against) any eye care professional (ECP). RESULTS: The answers obtained by the same AI chatbots were different in Spain and the U.K. Also, statistically significant differences were found between the AI chatbots for accuracy. In the U.K., ChatGPT 3.5 was the most and Open Assistant least accurate (p < 0.01). In Spain, Perplexity and ChatGPT were statistically more accurate than Open Assistant (p < 0.01). All the AI chatbots presented bias, except ChatGPT 3.5 in Spain. CONCLUSIONS: AI chatbots do not always consider local CL legislation, and their accuracy seems to be dependent on the language used to interact with them. Hence, at this time, although some AI chatbots might be a good source of information for general CL related questions, they cannot replace an ECP.

BCLA CLEAR Presbyopia: Epidemiology and impact.

The global all-ages prevalence of epidemiologically-measured 'functional' presbyopia was estimated at 24.9% in 2015, affecting 1.8 billion people. This prevalence was projected to stabilise at 24.1% in 2030 due to increasing myopia, but to affect more people (2.1 billion) due to population dynamics. Factors affecting the prevalence of presbyopia include age, geographic location, urban versus rural location, sex, and, to a lesser extent, socioeconomic status, literacy and education, health literacy and inequality. Risk factors for early onset of presbyopia included environmental factors, nutrition, near demands, refractive error, accommodative dysfunction, medications, certain health conditions and sleep. Presbyopia was found to impact on quality-of-life, in particular quality of vision, labour force participation, work productivity and financial burden, mental health, social wellbeing and physical health. Current understanding makes it clear that presbyopia is a very common age-related condition that has significant impacts on both patient-reported outcome measures and economics. However, there are complexities in defining presbyopia for epidemiological and impact studies. Standardisation of definitions will assist future synthesis, pattern analysis and sense-making between studies.