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Record W3114883268 · doi:10.4103/ijo.ijo_3250_20

Mask-associated dry eye disease and dry eye due to prolonged screen time

2020· article· en· W3114883268 on OpenAlex
Suresh K Pandey, Vidushi Sharma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndian Journal of Ophthalmology · 2020
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFace masksFace shieldCoronavirus disease 2019 (COVID-19)PandemicOptometryHygienePopulationMedical emergencyDiseaseEnvironmental healthHealth care

Abstract

fetched live from OpenAlex

Dear Editor, The entire world is currently struggling with coronavirus disease-2019 (COVID-19) pandemic and safety measures such as widespread use of face masks, respiratory hygiene, hand hygiene, physical distancing, and throat hygiene have been determined essential to combat COVID-19's spread. To avoid social gatherings and crowded workplaces, most of the work and meetings are done using digital devices on virtual platforms resulting in a considerable increase in screen time. Measures such as the use of face masks by the public remain the single most important aspect to limit the COVID-19 pandemic in the community. However, the ophthalmologists, as well as the general population, need to be aware that the facial mask together with prolonged use of digital devices is giving rise to increased reports of dry eyes in a large number of patients. Scientists from the Centre for Ocular Research & Education (CORE), Waterloo, Canada termed dry eye after use of face mask as mask-associated dry eye (MADE).[123] Face masks, face shields are crucial in the fight against COVID-19, and most of the ophthalmologists are seeing more and more patients with dry eye as a result of prolong use of face mask and increase in screen time during the COVID-19 pandemic era. The use of face masks significantly reduces the outward spread of air. However, exhaled air still needs to disperse; when a face mask sits loosely against the face (nose and cheek), the likely route of the exhaled air is upwards. This forces a stream of air over the surface of the cornea, creating conditions that accelerate corneal tear film evaporation, leading to dry spots on the ocular surface, ocular irritation, and discomfort. MADE can also cause worsening of symptoms in patients with pre-existing dry eye disease, post-menopausal dry eye, people using a smartphone or digital devices or computer for more than 2 h. MADE may aggravate dry eye symptoms in the elderly males or post-menopausal females, post-cataract IOL surgery cases, post-Lasik cases, contact lens wearers, who typically have a poorer quality corneal tear film, and masked people working extended hours in air-conditioned settings and/or while using digital screens. Beyond discomfort, MADE patients may rub their eyes or clean their spectacle for temporary relief—raising the possibility of unwashed hands being brought to the face. In turn, this increases the likelihood of novel coronavirus infection through the mouth, nose, and to a lesser extent, the eye. This can also increase the possibility of allergic conjunctivitis secondary to contents of sanitizers via frequent hand-eye contact. The ophthalmologists should be aware of this new entity of MADE and educate patients to wear the masks properly, such that exhaled air is not forced over the eyes, while also taking care to continue to encourage the widespread use of masks. Provide advice on alleviating the symptoms, including using info-graphic to help show how a few simple steps can likely provide relief and minimize re-occurrence [Fig. 1]. The ophthalmologist must ensure that a face mask is worn appropriately, particularly with spectacles or sunglasses. A carefully taped top edge on the nose (that does not interfere with blinking) may be helpful to minimize the symptoms. Frequent use of lubricating eye drops (as per recommendations by an ophthalmologist) can be helpful to minimize MADE. It is important to limit time in air-conditioned environments, take regular breaks from digital devices by following the 20:20:20 rule to minimize the digital eye strain.Figure 1: Mask-associated dry eye (MADE)As an effort for overcoming the global COVID-19 pandemic, it is everyone's responsibility to wear a mask when going out at public places, even when having to contend with eye dryness. MADE should not be used as an excuse for not using the mask. However, the ophthalmologists as well as the public need to remain aware of the MADE. The ophthalmologists should further communicate their knowledge about this entity to all their patients during this time of COVID-19 Pandemic when sound, scientific guidance is needed more than ever to win the battle against this invisible enemy. Future studies will reveal the incidence as well as the magnitude of the problem of the MADE. The use of masks, combined with prolonged screen time due to the easy availability of smartphone and cheap data plans in India, maybe a contributing factor to an epidemic of dry eye diseases in near future. Over 50 crore Indians are now using smart-phones, a 15% increase from 2018. Factors like availability of good-quality affordable smart-phones, expansion of online as well as offline channels, expansion of 4G/LTE networks by the operators are among the key reasons driving the smartphone user growth and most of these users are spending at least 6–8 h on phone each day. A study during the pre-COVID-19 era on dry-eye disease conducted by researchers from Hyderabad, on 1.45 million patients was recently published.[4] The study estimated that based on current incidence rates, 45% or nearly half of India's urban population is likely to be affected by this condition by the year 2030, roughly translating to a staggering 275 million people. Even rural India is likely to see 17 million new patients of the dry-eye disease every year. This would make dry-eye disease a serious health concern, even more common than diseases like diabetes or heart disease. Ophthalmologists, optometrists, vision scientists, health-care workers- let us all join hands together to educate the public and do our best to overcome the forthcoming epidemic of dry eye disease. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.273
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it