Dry eye disease (DED) is among the most common eye diseases and is becoming increasingly prevalent. Its symptoms cause a long-term decline in patients’ health-related quality of life (HRQL). Inconsistencies often occur between the clinical findings and the subjective symptoms of DED. Therefore, a holistic, balanced, and quantitative evaluation of the subjective symptoms and HRQL using patient-reported outcome questionnaires, in addition to clinical findings, is crucial for accurate DED assessment in patients. This paper reviewed the characteristics of current dry eye questionnaires, including their objectives, number of questions, inclusion of HRQL-related items, and whether they were properly evaluated for psychometric properties. Twenty-four questionnaires were identified; among them, the following six questionnaires that included items assessing HRQL and were properly evaluated for psychometric properties are recommended: the Ocular Surface Disease Index, Impact of Dry Eye in Everyday Life, Dry Eye-Related Quality-of-life Score, University of North Carolina Dry Eye Management Scale, Chinese version of Dry Eye-Related Quality of Life, and 25-Item National Eye Institute Visual Function Questionnaire. Dry eye questionnaires have different objectives and are available in different languages. Therefore, medical practitioners should confirm the characteristics of applicable questionnaires before selecting the most appropriate ones.

Dry eye disease (DED) after cataract surgery is associated with various risk factors, while causing a wide range of heterogeneous symptoms including decreased quality of vision. This systematic review and meta-analysis aimed to determine the prevalence and characteristics of DED after cataract surgery. We searched PubMed and EMBASE and included studies on patients with DED after cataract surgery, between January 2011 and June 2020. Study-specific estimates (DED prevalence rates after cataract surgery in patients without preexisting DED) were combined using one-group meta-analysis in a random-effects model. We included 36 studies published between 2013 and 2020. We included nine of these in the meta-analysis of DED prevalence after cataract surgery. Overall 37.4% (95% CI 22.6–52.3; 206/775) of patients without preexisting DED developed DED after cataract surgery. The risk factors for DED after cataract surgery included age, female sex, systemic diseases, systemic medications, psychiatric conditions, preexisting DED, meibomian gland dysfunction, preservatives in eye drops, surgery techniques, and lifestyle. DED severity peak occurred 1 day postoperatively and persisted for at least 1–12 months following cataract surgery; therefore, consistent follow-up for DED is warranted for at least 1 month after cataract surgery. Topical administration of preservative-free diquafosol tetrasodium solution and preoperative meibomian gland treatment were effective in preventing and treating DED following cataract surgery. As more than one-third of patients develop DED after cataract surgery, careful DED management and treatment is needed after cataract surgery to improve satisfaction and vision quality.

Purpose: This systematic review aimed to determine currently reported clinical and prodromal ocular symptoms in patients with coronavirus disease 2019 (COVID-19). Methods: An online article search was performed in PubMed and EMBASE. Altogether 15 studies (retrospective, prospective, or case studies) involving 1533 patients with COVID-19, reporting on ocular symptoms, and with outcome data available were identified. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines were followed. Study-specific estimates (incidence rates of ocular symptoms in patients with COVID-19) of cases were combined using one-group meta-analysis in a random-effects model. Results: Of all included studies, 11.2% (95% confidence interval, 5.5–16.9; 78/1526 cases) reported ocular symptoms. The most common ocular finding was conjunctivitis. Prodromal ocular symptoms occurred in 12.5% (13/104 cases) of patients with COVID-19. Positive real-time polymerase chain reaction results were obtained for 16.7% (10/60 cases) of conjunctival samples and 0% (0/17 cases) of tear samples. Twelve ocular conjunctival swab samples tested positive for SARS-CoV-2. Ten cases were from subjects showing ocular symptoms (16.7%, 10/60 cases), and the remaining two cases were from subjects without ocular manifestation (1.8%, 2/113 cases). Limitations included the short study period, small sample size, findings were limited to the Asian population, only seven articles included ophthalmologic examination details, and there is currently no consensus on COVID-19 management. Conclusions: Ocular symptoms may occur in the presymptomatic phase as a prodromal symptom (12.5%, 13/104 cases), suggesting the possibility of viral transmission from the conjunctiva.

Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.

Dry eye disease (DED) is a chronic, multifactorial ocular surface disorder with multiple etiologies that results in tear film instability. Globally, the prevalence of DED is expected to increase with an aging society and daily use of digital devices. Unfortunately, the medical field is currently unprepared to meet the medical needs of patients with DED. Noninvasive, reliable, and readily reproducible biomarkers have not yet been identified, and the current mainstay treatment for DED relies on symptom alleviation using eye drops with no effective preventative therapies available. Medical big data analyses, mining information from multiomics studies and mobile health applications, may offer a solution for managing chronic conditions such as DED. Omics-based data on individual physiologic status may be leveraged to prevent high-risk diseases, accurately diagnose illness, and improve patient prognosis. Mobile health applications enable the portable collection of real-world medical data and biosignals through personal devices. Together, these data lay a robust foundation for personalized treatments for various ocular surface diseases and other pathologies that currently lack the components of precision medicine. To fully implement personalized and precision medicine, traditional aggregate medical data should not be applied directly to individuals without adjustments for personal etiology, phenotype, presentation, and symptoms.

Background: Discontinuation of contact lens use is mainly caused by contact lens–associated dry eye. It is crucial to delineate contact lens–associated dry eye's multifaceted nature to tailor treatment to each patient’s individual needs for future personalized medicine. Objective: This paper aims to quantify and stratify individual subjective symptoms of contact lens–associated dry eye and clarify its risk factors for future personalized medicine using the smartphone app DryEyeRhythm (Juntendo University). Methods: This cross-sectional study included iPhone (Apple Inc) users in Japan who downloaded DryEyeRhythm. DryEyeRhythm was used to collect medical big data related to contact lens–associated dry eye between November 2016 and January 2018. The main outcome measure was the incidence of contact lens–associated dry eye. Univariate and multivariate adjusted odds ratios of risk factors for contact lens–associated dry eye were determined by logistic regression analyses. The t-distributed Stochastic Neighbor Embedding algorithm was used to depict the stratification of subjective symptoms of contact lens–associated dry eye. Results: The records of 4454 individuals (median age 27.9 years, SD 12.6), including 2972 female participants (66.73%), who completed all surveys were included in this study. Among the included participants, 1844 (41.40%) were using contact lenses, and among those who used contact lenses, 1447 (78.47%) had contact lens–associated dry eye. Multivariate adjusted odds ratios of risk factors for contact lens–associated dry eye were as follows: younger age, 0.98 (95% CI 0.96-0.99); female sex, 1.53 (95% CI 1.05-2.24); hay fever, 1.38 (95% CI 1.10-1.74); mental illness other than depression or schizophrenia, 2.51 (95% CI 1.13-5.57); past diagnosis of dry eye, 2.21 (95% CI 1.63-2.99); extended screen exposure time >8 hours, 1.61 (95% CI 1.13-2.28); and smoking, 2.07 (95% CI 1.49-2.88). The t-distributed Stochastic Neighbor Embedding analysis visualized and stratified 14 groups based on the subjective symptoms of contact lens–associated dry eye. Conclusions: This study identified and stratified individuals with contact lens–associated dry eye and its risk factors. Data on subjective symptoms of contact lens–associated dry eye could be used for prospective prevention of contact lens–associated dry eye progression.