Smartphone App-Based and Paper-Based Patient-Reported Outcomes Using a Disease-Specific Questionnaire for Dry Eye Disease: Randomized Crossover Equivalence Study.

BACKGROUND: Using traditional patient-reported outcomes (PROs), such as paper-based questionnaires, is cumbersome in the era of web-based medical consultation and telemedicine. Electronic PROs may reduce the burden on patients if implemented widely. Considering promising reports of DryEyeRhythm, our in-house mHealth smartphone app for investigating dry eye disease (DED) and the electronic and paper-based Ocular Surface Disease Index (OSDI) should be evaluated and compared to determine their equivalency. OBJECTIVE: The purpose of this study is to assess the equivalence between smartphone app-based and paper-based questionnaires for DED. METHODS: This prospective, nonblinded, randomized crossover study enrolled 34 participants between April 2022 and June 2022 at a university hospital in Japan. The participants were allocated randomly into 2 groups in a 1:1 ratio. The paper-app group initially responded to the paper-based Japanese version of the OSDI (J-OSDI), followed by the app-based J-OSDI. The app-paper group responded to similar questionnaires but in reverse order. We performed an equivalence test based on minimal clinically important differences to assess the equivalence of the J-OSDI total scores between the 2 platforms (paper-based vs app-based). A 95% CI of the mean difference between the J-OSDI total scores within the ±7.0 range between the 2 platforms indicated equivalence. The internal consistency and agreement of the app-based J-OSDI were assessed with Cronbach α coefficients and intraclass correlation coefficient values. RESULTS: A total of 33 participants were included in this study. The total scores for the app- and paper-based J-OSDI indicated satisfactory equivalence per our study definition (mean difference 1.8, 95% CI -1.4 to 5.0). Moreover, the app-based J-OSDI total score demonstrated good internal consistency and agreement (Cronbach α=.958; intraclass correlation=0.919; 95% CI 0.842 to 0.959) and was significantly correlated with its paper-based counterpart (Pearson correlation=0.932, P<.001). CONCLUSIONS: This study demonstrated the equivalence of PROs between the app- and paper-based J-OSDI. Implementing the app-based J-OSDI in various scenarios, including telehealth, may have implications for the early diagnosis of DED and longitudinal monitoring of PROs.

Using the AllerSearch Smartphone App to Assess the Association Between Dry Eye and Hay Fever: mHealth-Based Cross-Sectional Study.

BACKGROUND: Dry eye (DE) and hay fever (HF) show synergistic exacerbation of each other's pathology through inflammatory pathways. OBJECTIVE: This study aimed to investigate the association between DE and HF comorbidity and the related risk factors. METHODS: A cross-sectional observational study was conducted using crowdsourced multidimensional data from individuals who downloaded the AllerSearch smartphone app in Japan between February 2018 and May 2020. AllerSearch collected the demographics, medical history, lifestyle and residential information, HF status, DE symptoms, and HF-related quality of life. HF symptoms were evaluated using the nasal symptom score (0-15 points) and nonnasal symptom score (0-12 points). HF was defined by the participants' responses to the questionnaire as HF, non-HF, or unknown. Symptomatic DE was defined as an Ocular Surface Disease Index total score (0-100 points), with a threshold score of 13 points. HF-related quality of life was assessed using the Japanese Allergic Conjunctival Disease Standard Quality of Life Questionnaire (0-68 points). We conducted a multivariable linear regression analysis to examine the association between the severity of DE and HF symptoms. We subsequently conducted a multivariable logistic regression analysis to identify the factors associated with symptomatic DE (vs nonsymptomatic DE) among individuals with HF. Dimension reduction via Uniform Manifold Approximation and Projection stratified the comorbid DE and HF symptoms. The symptom profiles in each cluster were identified using hierarchical heat maps. RESULTS: This study included 11,284 participants, classified into experiencing HF (9041 participants), non-HF (720 participants), and unknown (1523 participants) groups. The prevalence of symptomatic DE among individuals with HF was 49.99% (4429/9041). Severe DE symptoms were significantly associated with severe HF symptoms: coefficient 1.33 (95% CI 1.10-1.57; P<.001) for mild DE, coefficient 2.16 (95% CI 1.84-2.48; P<.001) for moderate DE, and coefficient 3.80 (95% CI 3.50-4.11; P<.001) for severe DE. The risk factors for comorbid symptomatic DE among individuals with HF were identified as female sex; lower BMI; medicated hypertension; history of hematologic, collagen, heart, liver, respiratory, or atopic disease; tomato allergy; current and previous mental illness; pet ownership; living room and bedrooms furnished with materials other than hardwood, carpet, tatami, and vinyl; discontinuation of contact lens use during the HF season; current contact lens use; smoking habits; and sleep duration of <6 hours per day. Uniform Manifold Approximation and Projection stratified the heterogeneous comorbid DE and HF symptoms into 14 clusters. In the hierarchical heat map, cluster 9 was comorbid with the most severe HF and DE symptoms, and cluster 1 showed severe HF symptoms with minimal DE-related symptoms. CONCLUSIONS: This crowdsourced study suggested a significant association between severe DE and HF symptoms. Detecting DE among individuals with HF could allow effective prevention and interventions through concurrent treatment for ocular surface management along with HF treatment.

Individual multidisciplinary clinical phenotypes of nasal and ocular symptoms in hay fever: Crowdsourced cross-sectional study using AllerSearch.

BACKGROUND: Multidisciplinary efforts to prospectively collect and analyze symptoms of hay fever are limited. We aimed to identify the characteristics of nasal and ocular symptoms of hay fever, using the AllerSearch smartphone application. METHODS: This mobile health-based prospective observational study using the AllerSearch smartphone application was conducted between February 1, 2018, and May 1, 2020. Individuals who downloaded AllerSearch from Japan and provided comprehensive self-assessments (including 17 items related to quality of life [QoL]-related items) were included. The characteristics and risk factors for allergic rhinitis (AR) and allergic conjunctivitis (AC) were identified using hierarchical heat maps and multivariate logistic regression. RESULTS: Of the 9041 participants with hay fever, 58.8% had AR and AC, 22.2% had AR, and 5.7% had AC. The AR-AC comorbid cohort showed worse symptoms of hay fever and QoL scores than the other cohorts. Factors (odds ratio, 95% confidence interval) associated with AR-AC included a lower age (0.98, 0.97-0.98), female sex (1.31, 1.19-1.45), liver disease (1.58, 1.26-2.35), dry eye disease (1.45, 1.30-1.63), unknown dry eye disease status (1.46, 1.31-1.62), contact lens use discontinuation during the hay fever season (1.69, 1.28-2.23), and bedroom flooring material other than hardwood, carpet, tatami, or vinyl (1.91, 1.16-3.14). CONCLUSIONS: Analysis of medical big data for hay fever performed using a mobile health app helped identify risk factors and characteristics of AC, AR, and AR-AC. Phenotyping of highly variable symptoms of hay fever, such as nasal and ocular symptoms, can facilitate better-quality clinical care.

Individual characteristics and associated factors of hay fever: A large-scale mHealth study using AllerSearch.

BACKGROUND: The prevalence of hay fever, a multifactorial allergic disease, is increasing. Identifying individual characteristics and associated factors of hay fever is essential for predictive, preventive, personalized, and participatory (P4) medicine. This study aimed to identify individual characteristics and associated factors of hay fever using an iPhone application AllerSearch. METHODS: This large-scale mobile health-based cross-sectional study was conducted between February 2018 and May 2020. Individuals who downloaded AllerSearch in Japan and provided a comprehensive self-assessment (general characteristics, medical history, lifestyle habits, and hay fever symptoms [score range 0-36]) were included. Associated factors of hay fever (vs. non-hay fever) and severe hay fever symptoms were identified using multivariate logistic and linear regression analyses, respectively. RESULTS: Of the included 11,284 individuals, 9041 had hay fever. Factors associated with hay fever (odds ratio) included age (0.98), female sex (1.33), atopic dermatitis (1.40), history of dry eye diagnosis (1.36), discontinuation of contact lens use during hay fever season (3.34), frequent bowel movements (1.03), and less sleep duration (0.91). The factors associated with severe hay fever symptoms among individuals with hay fever (coefficient) included age (-0.104), female sex (1.329), history of respiratory disease (1.539), history of dry eye diagnosis (0.824), tomato allergy (1.346), discontinuation of contact lens use during hay fever season (1.479), smoking habit (0.614), and having a pet (0.303). CONCLUSIONS: Our large-scale mobile health-based study using AllerSearch elucidated distinct hay fever presentation patterns, characteristics, and factors associated with hay fever. Our study establishes the groundwork for effective individualized interventions for P4 medicine.

Stratification of Individual Symptoms of Contact Lens-Associated Dry Eye Using the iPhone App DryEyeRhythm: Crowdsourced Cross-Sectional Study.

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.

New medical big data for P4 medicine on allergic conjunctivitis.

Allergic conjunctivitis affects approximately 15-20% of the global population and can permanently deteriorate one's quality of life (QoL) and work productivity, leading to societal work force costs. Although not fully understood, allergic conjunctivitis is a multifactorial disease with a complex network of environmental, lifestyle, and host contributory risk factors. To effectively enhance the quality of treatment for patients with allergic conjunctivitis, as well as other allergic diseases, the field must first comprehend the pathology underlying various individualized subjective symptoms and stratify the disease according to risk factors and presentations. Such competent stratification and societal reconstruction that targets the alleviation of the damage due to allergic diseases would greatly help ramify personalized treatments and prevent the projected increase in societal costs imposed by allergic diseases. Owing to the rapid advancements in the information and technology sector, medical big data are greatly accessible and useful to decipher the pathophysiology of many diseases. Such data collected through multi-omics and mobile health have been effective for research on chronic diseases including allergic and immune-mediated diseases. Novel big data containing vast and continuous information on individuals with allergic conjunctivitis and other allergic symptoms are being used to search for causative genes of diseases, gain insights into new biomarkers, prevent disease progression, and, ultimately, improve QoL. The individualized and holistic data accrued from new angles using technological innovations are helping the field realize the principles of P4 medicine: predictive, preventive, personalized, and participatory medicine.

Decoupled epineurial and axonal deformation in mouse median and ulnar nerves.

INTRODUCTION: Peripheral nerves accommodate mechanical loads during joint movement. Hypothesized protective features include increased nerve compliance near joints and axonal undulation. How axons perceive nerve deformation is poorly understood. We tested whether nerves increase local axonal undulation in regions of high epineurial strain to protect nerve fibers from strain-induced damage. METHODS: Regional epineurial strain was measured near the elbow in median and ulnar nerves of mice expressing axonal fluorescence before and after decompression. Regional axonal tortuosity was quantified under confocal microscopy. RESULTS: Nerves showed higher epineurial strain just distal to the medial epicondyle; these differences were eliminated after decompression. Axonal tortuosity also varied regionally; however, unlike in the epineurium, it was greater in proximal regions. DISCUSSION: In this study we have proposed a neuromechanical model whereby axons can unravel along their entire length due to looser mechanical coupling to the peri/epineurium. Our findings have major implications for understanding nerve biomechanics and dysfunction. Muscle Nerve 59:619-619, 2019.

Optimal cutoff value of the dry eye-related quality-of-life score for diagnosing dry eye disease.

This retrospective study aimed to determine the optimal cutoff values of the Dry Eye-Related Quality-of-Life Score (DEQS) questionnaire for diagnosing dry eye disease (DED) and classifying DED severities. Participants completed the DEQS questionnaire, the Japanese version of the Ocular Surface Disease Index (J-OSDI) questionnaire, and DED examinations. DED was diagnosed according to the 2016 Asia Dry Eye Society diagnostic criteria based on DED symptoms (J-OSDI ≥ 13 points) and tear film breakup time ≤ 5 s. Receiver operating characteristic (ROC) analysis was used to calculate the optimal cutoff values of the DEQS summary score for detecting DED and grading its severity. Among 427 patients, 296 (69.3%) and 131 (30.7%) were diagnosed with DED and non-DED, respectively. ROC analysis determined an optimal cutoff value of 15.0 points for DED diagnosis, with 83.5% sensitivity, 87.0% specificity, and an area under the curve of 0.915. The positive and negative predictive values for DEQS ≥ 15.0 points were 93.6% and 69.9%, respectively. DEQS cutoff values of 15.0, 20.0, and 26.8 points could be accepted for severity classification of DED subjective symptoms in clinical use and represent mild, moderate, and severe DED, respectively. Conclusively, the optimal cutoff values of DEQS enable DED detection and subjective symptom severity classification.

Human ocular thelaziasis with genetic analysis in Niigata Prefecture, Japan: A case report on an emerging zoonosis.

Purpose: We report the clinical findings and molecular identification of ocular Thelazia callipaeda from Niigata Prefecture in the Hokuriku area of Japan during winter. Observations: A 77-year-old male visited an ophthalmology clinic in Niigata Prefecture in January 2022 after a 2-week-duration of a conjunctival injection in the left eye and foreign body sensation. Slit-lamp microscopy revealed 11 active nematodes in the left conjunctival sac. Morphological characteristics included longer female body length than male, buccal cavity lacking teeth and lips, and serrated striations along the body surface. The specimens were determined to be T. callipaeda. Genetic analysis of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene revealed an h9 haplotype. Conclusions and Importance: T. callipaeda infection, especially the h9 haplotype, commonly occurs in western Japan owing to its higher incidence in warmer climates, suggesting the origin of the case. Here, we report a human case of Thelaziasis diagnosed in a cold region of Japan (the Hokuriku area) during winter. This human case of T. callipaeda infection from a cold, previously unassociated region, raises concerns about the potential geographical widening of its distribution, and further investigation may be warranted to prevent its spread.

Effect of Resident Involvement in Ophthalmic Surgery on Patient Outcomes: A Systematic Review and Meta-analysis.

PURPOSE: To determine the effect of resident- vs attending-led surgeries on patient outcomes in ophthalmic surgery. DESIGN: Systematic review and meta-analysis. METHODS: Two independent authors searched PubMed, EMBASE, and Cochrane Library from inception to March 2022. Categorical data from studies were pooled to report odds ratio (OR) and 95% CIs. Continuous data were analyzed to yield standardized mean difference (SMD) and 95% CIs. Propensity-matched studies were analyzed separately. Study quality was assessed using the Newcastle-Ottawa Scale. RESULTS: Twenty-four studies were included in this meta-analysis. Seventeen of the 20 outcomes had no significant differences between the 2 cohorts. Notably, many critical cataract surgery-related outcomes showed no significant differences, including posterior capsular tear, lens fragment retainment, and retinal detachment. Among propensity-scored studies, the resident-led surgeries had longer operative duration (SMD 0.81, 95% CI 0.29, 1.33; 3 studies [260 patients], I2 = 74%) and had an increased risk of an unplanned return to the operating room (OR 2.58, 95% CI 1.31, 5.06; 4 studies [342 patients], I2 = 0%). Among 2 non-propensity-scored, resident-led surgeries had increased incidence of choroidal detachment or choroidal effusion (OR 2.28, 95% 1.02, 5.09; 2 studies [401 patients], I2 = 19%). No significant difference was found for ocular hypotony. Significant heterogeneity existed among propensity-scored studies. CONCLUSIONS: Resident-led surgeries appear overall safe, effective, and comparable to attending-led surgeries with respect to commonly encountered perioperative complications. Specific differences in outcomes exhibit significant heterogeneity and small sample sizes, and may be of unclear or equivocal clinical significance.

Clinical utility of maximum blink interval measured by smartphone application DryEyeRhythm to support dry eye disease diagnosis.

The coronavirus disease (COVID-19) pandemic has emphasized the paucity of non-contact and non-invasive methods for the objective evaluation of dry eye disease (DED). However, robust evidence to support the implementation of mHealth- and app-based biometrics for clinical use is lacking. This study aimed to evaluate the reliability and validity of app-based maximum blink interval (MBI) measurements using DryEyeRhythm and equivalent traditional techniques in providing an accessible and convenient diagnosis. In this single-center, prospective, cross-sectional, observational study, 83 participants, including 57 with DED, had measurements recorded including slit-lamp-based, app-based, and visually confirmed MBI. Internal consistency and reliability were assessed using Cronbach's alpha and intraclass correlation coefficients. Discriminant and concurrent validity were assessed by comparing the MBIs from the DED and non-DED groups and Pearson's tests for each platform pair. Bland-Altman analysis was performed to assess the agreement between platforms. App-based MBI showed good Cronbach's alpha coefficient, intraclass correlation coefficient, and Pearson correlation coefficient values, compared with visually confirmed MBI. The DED group had significantly shorter app-based MBIs, compared with the non-DED group. Bland-Altman analysis revealed minimal biases between the app-based and visually confirmed MBIs. Our findings indicate that DryEyeRhythm is a reliable and valid tool that can be used for non-invasive and non-contact collection of MBI measurements, which can assist in accessible DED detection and management.

The minimal clinically important difference of app-based electronic patient-reported outcomes for hay fever.

BACKGROUND: Hay fever is a common allergic disease, with an estimated worldwide prevalence of 14.4% and a variety of symptoms. This study assessed the minimal clinically important difference (MCID) of nasal symptom score (NSS), non-nasal symptom score (NNSS), and total symptoms score (TSS) for app-based hay-fever monitoring. METHODS: MCIDs were calculated based on the data from a previous large-scale, crowdsourced, cross-sectional study using AllerSearch, an in-house smartphone application. MCIDs were determined with anchor-based and distribution-based methods. The face scale score of the Japanese Allergic Conjunctival Disease Standard Quality of Life Questionnaire Domain III and the daily stress level due to hay fever were used as anchors for determining MCIDs. The MCID estimates were summarized as MCID ranges. RESULTS: A total of 7590 participants were included in the analysis (mean age: 35.3 years, 57.1% women). The anchor-based method produced a range of MCID values (median, interquartile range) for NSS (2.0, 1.5-2.1), NNSS (1.0, 0.9-1.2), and TSS (2.9, 2.4-3.3). The distribution-based method produced two MCIDs (based on half a standard deviation, based on a standard error of measurement) for NSS (2.0, 1.8), NNSS (1.3, 1.2), and TSS (3.0, 2.3). The final suggested MCID ranges for NSS, NNSS, and TSS were 1.8-2.1, 1.2-1.3, and 2.4-3.3, respectively. CONCLUSIONS: MCID ranges for app-based hay-fever symptom assessment were obtained from the data collected through a smartphone application, AllerSearch. These estimates may be useful for monitoring the subjective symptoms of Japanese patients with hay fever through mobile platforms.

P4 Medicine for Heterogeneity of Dry Eye: A Mobile Health-based Digital Cohort Study.

During the 5th Science, Technology, and Innovation Basic Plan, the Japanese government proposed a novel societal concept -Society 5.0- that promoted a healthcare system characterized by its capability to provide unintrusive, predictive, longitudinal care through the integration of cyber and physical space. The role of Society 5.0 in managing our quality of vision will become more important in the modern digitalized and aging society, both of which are known risk factors for developing dry eye. Dry eye is the most common ocular surface disease encountered in Japan with symptoms including increased dryness, eye discomfort, and decreased visual acuity. Owing to its complexity, implementation of P4 (predictive, preventive, personalized, participatory) medicine in managing dry eye requires a comprehensive understanding of its pathology, as well as a strategy to visualize and stratify its risk factors. Using DryEyeRhythm®, a mobile health (mHealth) smartphone software (app), we established a route to collect holistic medical big data on dry eye, such as the subjective symptoms and lifestyle data for each individual. The studies to date aided in determining the risk factors for severe dry eye, the association between major depressive disorder and dry eye exacerbation, eye drop treatment adherence, app-based stratification algorithms based on symptomology, blink detection biosensoring as a dry eye-related digital phenotype, and effectiveness of app-based dry eye diagnosis support compared to traditional methods. These results contribute to elucidating disease pathophysiology and promoting preventive and effective measures to counteract dry eye through mHealth.

Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study.

BACKGROUND/OBJECTIVE: To test the feasibility of a dry eye disease (DED) symptom stratification algorithm previously established for the general population among patients visiting ophthalmologists. SUBJECT/METHODS: This retrospective cross-sectional study was conducted between December 2015 and October 2021 at a university hospital in Japan; participants who underwent a comprehensive DED examination and completed the Japanese version of the Ocular Surface Disease Index (J-OSDI) were included. Patients diagnosed with DED were stratified into seven clusters using a previously established symptom-based stratification algorithm for DED. Characteristics of the patients in stratified clusters were compared. RESULTS: In total, 426 participants were included (median age [interquartile range]; 63 [48-72] years; 357 (83.8%) women). Among them, 291 (68.3%) participants were diagnosed with DED and successfully stratified into seven clusters. The J-OSDI total score was highest in cluster 1 (61.4 [52.2-75.0]), followed by cluster 5 (44.1 [38.8-47.9]). The tear film breakup time was the shortest in cluster 1 (1.5 [1.1-2.1]), followed by cluster 3 (1.6 [1.0-2.5]). The J-OSDI total scores from the stratified clusters in this study and those from the clusters identified in the previous study showed a significant correlation (r = 0.991, P < 0.001). CONCLUSIONS: The patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.

Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study.

BACKGROUND: Dry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartphone app, namely, the DEA01, has been developed as a noninvasive, noncontact, and remote screening device, in the context of an ongoing paradigm shift in the health care system, to facilitate a diagnosis of DED. OBJECTIVE: This study aimed to evaluate the capabilities of the DEA01 smartphone app to facilitate a DED diagnosis. METHODS: In this multicenter, open-label, prospective, and cross-sectional study, the test method will involve using the DEA01 smartphone app to collect and evaluate DED symptoms, based on the Japanese version of the Ocular Surface Disease Index (J-OSDI), and to measure the maximum blink interval (MBI). The standard method will then involve a paper-based J-OSDI evaluation of subjective symptoms of DED and tear film breakup time (TFBUT) measurement in an in-person encounter. We will allocate 220 patients to DED and non-DED groups, based on the standard method. The primary outcome will be the sensitivity and specificity of the DED diagnosis according to the test method. Secondary outcomes will be the validity and reliability of the test method. The concordance rate, positive and negative predictive values, and the likelihood ratio between the test and standard methods will be assessed. The area under the curve of the test method will be evaluated using a receiver operating characteristic curve. The internal consistency of the app-based J-OSDI and the correlation between the app-based J-OSDI and paper-based J-OSDI will be assessed. A DED diagnosis cutoff value for the app-based MBI will be determined using a receiver operating characteristic curve. The app-based MBI will be assessed to determine a correlation between a slit lamp-based MBI and TFBUT. Adverse events and DEA01 failure data will be collected. Operability and usability will be assessed using a 5-point Likert scale questionnaire. RESULTS: Patient enrollment will start in February 2023 and end in July 2023. The findings will be analyzed in August 2023, and the results will be reported from March 2024 onward. CONCLUSIONS: This study may have implications in identifying a noninvasive, noncontact route to facilitate a diagnosis of DED. The DEA01 may enable a comprehensive diagnostic evaluation within a telemedicine setting and facilitate early intervention for undiagnosed patients with DED confronting health care access barriers. TRIAL REGISTRATION: Japan Registry of Clinical Trials jRCTs032220524; https://jrct.niph.go.jp/latest-detail/jRCTs032220524. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45218.

Changing Medical Paradigm on Inflammatory Eye Disease: Technology and Its Implications for P4 Medicine.

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Prevalence and Characteristics of Dry Eye Disease After Cataract Surgery: A Systematic Review and Meta-Analysis.

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.

DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye.

PURPOSE: Undiagnosed or inadequately treated dry eye disease (DED) decreases the quality of life. We aimed to investigate the reliability, validity, and feasibility of the DryEyeRhythm smartphone application (app) for the diagnosis assistance of DED. METHODS: This prospective, cross-sectional, observational, single-center study recruited 82 participants (42 with DED) aged ≥20 years (July 2020-May 2021). Patients with a history of eyelid disorder, ptosis, mental disease, Parkinson's disease, or any other disease affecting blinking were excluded. Participants underwent DED examinations, including the Japanese version of the Ocular Surface Disease Index (J-OSDI) and maximum blink interval (MBI). We analyzed their app-based J-OSDI and MBI results. Internal consistency reliability and concurrent validity were evaluated using Cronbach's alpha coefficients and Pearson's test, respectively. The discriminant validity of the app-based DED diagnosis was assessed by comparing the results of the clinical-based J-OSDI and MBI. The app feasibility and screening performance were evaluated using the precision rate and receiver operating characteristic curve analysis. RESULTS: The app-based J-OSDI showed good internal consistency (Cronbach's α = 0.874). The app-based J-OSDI and MBI were positively correlated with their clinical-based counterparts (r = 0.891 and r = 0.329, respectively). Discriminant validity of the app-based J-OSDI and MBI yielded significantly higher total scores for the DED cohort (8.6 ± 9.3 vs. 28.4 ± 14.9, P < 0.001; 19.0 ± 11.1 vs. 13.2 ± 9.3, P < 0.001). The app's positive and negative predictive values were 91.3% and 69.1%, respectively. The area under the curve (95% confidence interval) was 0.910 (0.846-0.973) with concurrent use of the app-based J-OSDI and MBI. CONCLUSIONS: DryEyeRhythm app is a novel, non-invasive, reliable, and valid instrument for assessing DED.