Diagnosis Of Eye Research Articles

The Efficacy and Safety of Topical Cyclosporine A and its Generic Equivalency Depores Eye Drops in The Treatment of Dry Eye Disease

Dry eye disease (DED) is a complex condition that can result in significant vision complications. Analyzing systematic reviews of DED treatment contributes to selecting the most effective and safe drug. This review examines the efficacy of cyclosporine A and the generic Depores ophthalmic emulsion cyclosporine 0.05% (cyclosporine 0.05%, Deva Pharmaceuticals, Turkey) in the treatment of DED. A search for scientific information in PubMed, PubMed Central, The Cochrane Library, Google Scholar databases, and the Internet was carried out using keywords: dry eye disease, Cyclosporine A, Ikervis, Restasis, generic cyclosporine 0.05% ophthalmic emulsion, Depores. The literature cited in scientific articles was also reviewed. The analysis of scientific articles allowed us to conclude about the efficacy of the Restasis–Depores generic (cyclosporine 0.05%, Deva Pharmaceuticals, Turkey) for the treatment of patients with DED who have not yet had access to this treatment. Depores is now available in Georgia, bringing a novel treatment option to patients with severe DED. The study revealed a small number of clinical studies evaluating the efficacy and safety of generic cyclosporine 0.05% ophthalmic emulsion. Given the scarcity of research articles on this generic, it is necessary to study the results of its use in the treatment of DED in Georgia, which will help improve the quality of life with a diagnosis of dry eye.

National Experience of Technology-based Eye Care Services (TECS): A Comprehensive Ophthalmology Telemedicine Initiative

Technology-Based Eye Care Services (TECS) is a tele-ophthalmology program operating in the Veterans' Administration since 2015. This study explores characteristics of the national TECS population, evaluates implementation and sustainability of TECS, and analyzes possible associations and effects of demographic characteristics and social determinants of health (SDOH) on being diagnosed with a vision threatening (VT) disease. Implementation and sustainability of TECS from 2015-2022 was examined along with the sociodemographic characteristics of Veterans served through TECS in 2021. Veteran patients seen in TECS nationwide. Characteristics, disease prevalence and diagnoses, implementation success rate, sustainability rate, preliminary analysis of outcomes and disparity. Per quarter from 2015-2022, TECS sites were classified as implementing, active, or sustained. Standard Query Language (SQL) was used to determine sociodemographic data and logistic regression models were used to identify risk factors associated with VT eye diagnosis. 21,712 Veterans, 52.1% rural or highly rural, were served by TECS in 2021. The average age was 64.7 years, with females comprising 10.9% of the population served. From 2015-2022, of the 67 TECS sites initiated, 6 were implementing with 51 of 61 initiated sites still operational in the first quarter (Q1) of 2022 (83.6% success rate).Macular degeneration (AMD) and cataracts were more prevalent in rural and highly rural populations (7.6% and 11.3%, and 48.8% and 55.0%, respectively) vs. urban populations; glaucoma and diabetic retinopathy (DR) had the opposite association. The prevalence of any type of VT eye disease was lowest in the Mountains/Central region (0.54%) and highest in the Southeast region (3.2%) of the US. Rural and highly rural residents were 1.3 and 2.5 times as likely, respectively, to be diagnosed with a VT eye disease than urban residents. Implementation and sustainability of TECS has been promising. The data provides key information that can be utilized to improve the deployment of TECS and similar programs, along with the possible future direction of TECS services. Moreover, experience from one national ocular telehealth program clearly illustrates that telemedicine can address eye care disparities in the Veteran population and may be utilized for other vulnerable groups as well.

Relationship between persistence with topical antiglaucomatous prescription and patient socioeconomic status at a tertiary university hospital in Jerez de la Frontera (Spain).

To study the relationship between socioeconomic status and persistence with topical antiglaucomatous medication. A retrospective epidemiological observational cohort study was conducted with a sample of 1563 patients. The main dependent variable was persistence (medication possession ratio), the independent variable was socioeconomic status (deprivation index). Additional independent variables were used for multivariate analysis: individual health card index, sex, age, pharmacological group, number of eye drops, preservatives, diagnosis and concurrent medications. Bivariate statistical analysis was obtained using non-parametric tests. Logistic regression was used for multivariate analysis. The level of statistical significance was set at p < 0.05. We obtained data showing greater persistence in the groups with a higher socioeconomic level (deprivation index 1 and 2), with medication possession ratio values of 79.97 and 75.30, respectively) as opposed to the groups at lower socioeconomic levels (deprivation index 4 and 5, with medication possession ratio values of 73.75 and 69.85, respectively. Logistic regression corroborated this difference, reaching a significant value (no persistence in deprivation index group 5 versus 1) with OR = 1.62; 95%CI: 1.13-2.31. Additionally, lower persistence was detected in males, under 60 years of age, undergoing treatment with alpha-agonists, and in patients with ocular hypertension. Low socioeconomic status of the patient was significantly associated with decreased persistence with topical antiglaucomatous therapy.

Treatment of dry eyes with lifitegrast 5% before cataract surgery: A prospective trial

Abstract Objective: The objective of the study was to evaluate the impact of dry eye treatment on intraocular lens (IOL) biometry measurements and postoperative refractive outcome. Design: This study involves a prospective interventional study. Participants: Consecutive patients with dry eye disease undergoing cataract surgery were included in the study. Materials and Methods: All participants underwent a comprehensive dry eye assessment including the ocular surface disease index (OSDI) questionnaire, Schirmer’s test without anesthesia, corneal fluorescein staining, and conjunctival lissamine green staining. Optical biometry was performed using swept-source optical coherence tomography (IOL Master® 700, Zeiss), and corneal aberrometry was measured using a scanning-slit aberrometer (OPD SCAN III, Nidek). Diagnosis of dry eye was made according to Dry Eye Workshop II. Patients received 6 weeks of treatment of lifitegrast 5% and preservative-free artificial tear eye drops and had repeat testing at the end of 6 weeks. The change in subjective and objective dry eye tests and biometry measurements and the difference in target and postoperative refraction before and after treatment were compared. Results: Forty eyes of 21 patients were included in the study. Subjectively, OSDI improved from 26.35 ± 6.24 at baseline to 20.97 ± 8.41 after treatment (P = 0.03). Objectively, corneal staining improved from 1.42 ± 1.78 at baseline to 0.39 ± 0.67 after treatment (P = 0.006). No changes were observed in Schirmer’s test without anesthesia, conjunctival staining, or corneal aberrometry (P &gt; 0.05). Repeated biometry after dry eye treatment showed a change in IOL power difference ≥0.5 diopters in 50% (20) of eyes. Mean absolute error was within 0.25D in 87.5% (35) of eyes after treatment compared to 67.5% at baseline (P = 0.05). Conclusion: Dry eye treatment leads to subjective symptom improvement and changes in IOL power calculations and postoperative refractive outcomes. Assessing and treating patients for dry eyes before cataract surgery is important in maximizing refractive outcomes.

Application of Convolutional Gated Recurrent Units U-Net for Distinguishing between Retinitis Pigmentosa and Cone–Rod Dystrophy

Abstract Artificial Intelligence (AI) has gained a prominent role in the medical industry. The rapid development of the computer science field has caused AI to become a meaningful part of modern healthcare. Image-based analysis involving neural networks is a very important part of eye diagnoses. In this study, a new approach using Convolutional Gated Recurrent Units (GRU) U-Net was proposed for the classifying healthy cases and cases with retinitis pigmentosa (RP) and cone–rod dystrophy (CORD). The basis for the classification was the location of pigmentary changes within the retina and fundus autofluorescence (FAF) pattern, as the posterior pole or the periphery of the retina may be affected. The dataset, gathered in the Chair and Department of General and Pediatric Ophthalmology of Medical University in Lublin, consisted of 230 ultra-widefield pseudocolour (UWFP) and ultra-widefield FAF images, obtained using the Optos 200TX device (Optos PLC). The data were divided into three categories: healthy subjects (50 images), patients with CORD (48 images) and patients with RP (132 images). For applying deep learning classification, which rely on a large amount of data, the dataset was artificially enlarged using augmentation involving image manipulations. The final dataset contained 744 images. The proposed Convolutional GRU U-Net network was evaluated taking account of the following measures: accuracy, precision, sensitivity, specificity and F1. The proposed tool achieved high accuracy in a range of 91.00%–97.90%. The developed solution has a great potential in RP diagnoses as a supporting tool.

Radiation-induced eye impairments

The problem of the impact of ionizing radiation on eye structures is one of the most important and topical in radiobiology. Knowledge of tissue radiosensitivity and induced tissue changes in the eye is essential for understanding the nature of radiation damage and the behavior of medical professionals. In this publication, the early and late determined radiation-induced impairments of the eye are presented as a result of radiotherapy or radiation incidents. The risk factors determining post-irradiation eye reactions, pathophysiological mechanisms, clinical picture, diagnosis, prevention, and new approaches in therapy are presented. We found that the typically found radiation-induced eye impairments are those of the eyelids – dermatosis and madarosis, conjunctiva – acute conjunctivitis, varied damage to the lacrimal apparatus, cornea – edema and ulceration, iris – rarely inflammation or neovascularization, sclera – rarely atrophy or necrosis, eye lens – cataract, retina – characteristic retinopathy, and optical nerve – rarely neuropathy. We provide the current consensus on prevention and treatment protocols in radiation-induced eye impairments, though most suggested treatment so far should qualify as experimental.

Machine Learning Models for the Diagnosis of Dry Eyes Using Real-World Clinical Data

Machine Learning Models for the Diagnosis of Dry Eyes Using Real-World Clinical Data

Challenges and prospects in the application of artificial intelligence for ocular disease screening and diagnosis

In recent years, artificial intelligence (AI) technologies have experienced substantial growth across various sectors, with significant strides made particularly in medical AI through advancements such as large models. The application of AI within the field of ophthalmology can enhance the accuracy of eye disease screening and diagnosis. However, the deployment of AI and its large models in ophthalmology still encounters numerous limitations and challenges. This article builds upon the transformative achievements in the medical AI sector and discusses the ongoing challenges faced by AI applications in ophthalmology. It provides forward-looking insights from an ophthalmic perspective regarding the era of large models and anticipates research trends in AI applications in ophthalmology, so as to foster the continuous advancement of AI technologies, thereby significantly promoting eye health.

Automated tear film break-up time measurement for dry eye diagnosis using deep learning

In the realm of ophthalmology, precise measurement of tear film break-up time (TBUT) plays a crucial role in diagnosing dry eye disease (DED). This study aims to introduce an automated approach utilizing artificial intelligence (AI) to mitigate subjectivity and enhance the reliability of TBUT measurement. We employed a dataset of 47 slit lamp videos for development, while a test dataset of 20 slit lamp videos was used for evaluating the proposed approach. The multistep approach for TBUT estimation involves the utilization of a Dual-Task Siamese Network for classifying video frames into tear film breakup or non-breakup categories. Subsequently, a postprocessing step incorporates a Gaussian filter to smooth the instant breakup/non-breakup predictions effectively. Applying a threshold to the smoothed predictions identifies the initiation of tear film breakup. Our proposed method demonstrates on the evaluation dataset a precise breakup/non-breakup classification of video frames, achieving an Area Under the Curve of 0.870. At the video level, we observed a strong Pearson correlation coefficient (r) of 0.81 between TBUT assessments conducted using our approach and the ground truth. These findings underscore the potential of AI-based approaches in quantifying TBUT, presenting a promising avenue for advancing diagnostic methodologies in ophthalmology.

Prevalence of dry eye in patients using topical antiglaucoma medications

Aim: Topical antiglaucoma drugs may have adverse effects on the ocular surface. In this study, our aim was to report the frequency of dry eye and the use of artificial tear drops in patients diagnosed with glaucoma and using topical antiglaucoma drugs. We also evaluated factors affecting this association. Methods: Based on the medical records, we selected patients admitted to the ophthalmology department between 2020 and 2021 who had been diagnosed with glaucoma. In this study, we included patients who were using topical antiglaucoma medications and were older than 40 years of age. Age, gender, type, and number of glaucoma medications used, dry eye diagnosis, and use of artificial tear drops and/or topical cyclosporine were recorded. Results: We found that 346 (27%) of the 1,274 patients using topical antiglaucoma drugs had dry eyes and were using artificial tear drops. Gender (female) and the number of antiglaucoma medications used were associated with an increased risk of dry eye in these patients, while increasing age was not associated with dry eye. Conclusion: Dry eye is common in patients using topical antiglaucoma medications and should be considered in the treatment of glaucoma.

Digital Twin Models for Personalised and Predictive Medicine in Ophthalmology

This article explores the integration of Digital Twins in Systems and Predictive Medicine, focusing on eye diagnosis. By utilizing the Digital Twin models, the proposed framework can support early diagnosis and predict evolution after treatment by providing customized simulation scenarios. Furthermore, a structured architectural framework comprising five levels has been proposed, integrating Digital Twin, Systems Medicine, and Predictive Medicine for managing eye diseases. Based on demographic parameters, statistics were performed to identify potential correlations that may contribute to predispositions to glaucoma. With the aid of a dataset, a neural network was trained with the goal of identifying glaucoma. This comprehensive approach, based on statistical analysis and Machine Learning, is a promising method to enhance diagnostic accuracy and provide personalized treatment approaches.

Tear meniscus height agreement and reproducibility between two corneal topographers and spectral-domain optical coherence tomography

ABSTRACT Clinical relevance Tear meniscus height (TMH) is an important clinical marker in dry eye diagnosis and management. Purpose To evaluate the reproducibility and agreement of TMH measurements in non-clinical participants using the Oculus Keratograph 5 M, Medmont Meridia, and Spectral-domain optical coherence tomography (Spectralis SD-OCT). Methods Fifty-six participants (mean 43.8 ± 22.4 years) were recruited for this cross-sectional study. Image acquisitions were performed on the three devices, sequentially and randomized. The repeatability and reproducibility of inter-observer and inter-device analysis were performed. Repeated measures ANOVA and Bland-Altman Plots were used to evaluate the agreement between devices. Results The mean TMH with the Oculus Keratograph 5 M, Medmont Meridia and Spectralis SD-OCT were 0.29 ± 0.16 mm, 0.24 ± 0.09 mm and 0.27 ± 0.16 mm, respectively. There were no significant inter-observer differences (paired t-tests, p < 0.001). All the devices exhibited good inter-observer reliability (ICC ≥ 0.877), and good repeatability (CV ≤ 16.53%). Inter-device reliability is moderate (ICC = 0.621, p < 0.001). Repeated measures ANOVA revealed that TMH measurements given by the Spectralis SD-OCT are not significantly different from the Oculus Keratograph 5 M (p = 0.19) and the Medmont Meridia (p = 0.38). TMH measurements from Oculus Keratograph 5 M were significantly higher than those from Medmont Meridia (p = 0.02). Correlations between the mean TMH and the difference in the TMH measurements were positive for Oculus Keratograph 5 M and Medmont Meridia (r2 = 0.62, p < 0.001), negative for Medmont Meridia and Spectralis SD-OCT (r2 = -0.59, p < 0.001), and not significant for Oculus Keratograph 5 M and Spectralis SD-OCT (r2 = 0.05, p = 0.74). A strong correlation was found for TMH measured with all devices (r2 = 0.55 to 0.81, p < 0.001). Conclusions The Oculus Keratograph 5 M, Medmont Meridia, and Spectralis SD-OCT provide reliable and reproducible inter-observer TMH measurements. Inter-device reliability is moderate, with a close correlation between Spectralis SD-OCT and the Oculus Keratograph 5 M. Oculus Keratograph 5 M and Medmont Meridia are repeatable devices appropriate for the measurement of TMH, but they are not interchangeable in clinical practice.

VisionDeep-AI: Deep learning-based retinal blood vessels segmentation and multi-class classification framework for eye diagnosis

Eye problems can lead to vision loss and have a significant impact on daily life, underscoring the critical importance of early diagnosis and treatment to prevent further damage and complications. A comprehensive segmentation-classification framework – VisionDeep-AI is developed in the proposed work for retinal vessel segmentation and multi-class classification on given fundus images. A weighted bi-directional feature pyramid network and U-Net backbone architecture-based customized deep-learning model is built to segment blood vessels which enhances feature extraction and multi-scale feature fusion. The architectural design comprises an end-to-end encoder-decoder network featuring six-depth layers with varying resolutions, enabling the extraction of high-level descriptors and lower-level, fine-grained characteristics. Furthermore, a multi-modal deep feature fusion architecture is developed for the multi-class classification of fundus images in four different categories by integrating features from segmented vessel images and raw fundus images, thereby accommodating more diversified information. A thorough analysis of VisionDeep-AI has been done on a comprehensive colour fundus image dataset. To ensure reliable results, data augmentation was done to prevent the over-fitting of the model and to enhance its generalization capability. The segmentation model performed exceptionally well and achieved a high accuracy of 97.73% and a dice coefficient of 89.90% in blood vessel segmentation from fundus images. Furthermore, multi-modal deep feature-fused classification architecture achieved a test accuracy of 81.50%, with a specificity of 93.83%. These findings showcase the robustness, generalizability and efficiency of the proposed VisionDeep-AI framework for fundus image segmentation and retinal disease classification, contributing towards advanced medical technologies and diagnosis precision.

Demographic and Psychiatric Associations With Dry Eye in a Medicare Population.

The purpose of this study was to investigate the impact of demographic characteristics and psychiatric comorbidity on the prevalence of dry eye disease in the American geriatric population. Data were collected from a 2011 nationwide sample of Medicare beneficiaries aged 65 years and older (N = 1,321,000). Age, sex, race/ethnicity, residential area, climate region, and income, along with psychiatric comorbidities including depression and anxiety, were collected. Multivariable logistic regression models were used to assess the relationship between demographic and psychiatric factors and the prevalence of dry eye disease. Among 21,059 patients with clinically significant dry eye, women had higher odds of having dry eye compared with men [odds ratio (OR) 2.03, 95% confidence interval (1.97-2.10)]. Asian and Native American patients had increased odds of having dry eye compared with White patients [OR 1.85 (1.69-2.02) and OR 1.51 (1.19-1.93)], while Black patients were less likely to have dry eye [OR 0.83 (0.79-0.87)]. Patients aged 75 to 84 years and 85+ were more likely to have dry eye compared with those aged 65 to 74 years [OR 1.49 (0.45-1.53) and OR 1.54 (1.48-1.60)]. Having both depression and anxiety were associated with higher odds of having dry eye [OR 2.38 (2.22-2.55)] compared with having depression alone [OR 1.95 (1.86-2.04)] or anxiety alone [OR 2.22 (2.10-2.35)]. Significant racial and regional disparities in dry eye prevalence were found. Psychiatric association with dry eye varied with age, sex, race, and residence region. Further research is needed to comprehend the underlying mechanisms, implications, and to address disparities in the diagnosis and management of dry eye.

New Korean Guidelines for the Diagnosis and Management of Dry Eye Disease.

New Korean guidelines for the diagnosis and management of dry eye disease were developed based on literature reviews by the Korean Dry Eye Guideline Establishment Committee, a previous dry eye guideline by Korean Corneal Disease Study Group, a survey of Korean Dry Eye Society (KDES) members, and KDES consensus meetings. The new definition of dry eye was also proposed by KDES regular members. The new definition by the regular members of the KDES is as follows: "Dry eye is a disease of the ocular surface characterized by tear film abnormalities and ocular symptoms." The combination of ocular symptoms and an unstable tear film (tear breakup time &lt;7 seconds) was considered as essential components for the diagnosis of dry eye. Schirmer test and ocular surface staining were considered adjunctive diagnostic criteria. The treatment guidelines consisted of a simplified stepwise approach according to aqueous deficiency dominant, evaporation dominant, and altered tear distribution subtypes. New Korean guidelines can be used as a simple, valid, and accessible tool for the diagnosis and management of dry eye disease in clinical practice.

Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging.

Retinal blood vessels are the only directly observed blood vessels in the body; changes in them can help effective assess the occurrence and development of ocular and systemic diseases. The specificity and efficiency of retinal vessel quantification technology has improved with the advancement of retinal imaging technologies and artificial intelligence (AI) algorithms; it has garnered attention in clinical research and applications for the diagnosis and treatment of common eye and related systemic diseases. A few articles have reviewed this topic; however, a summary of recent research progress in the field is still needed. This article aimed to provide a comprehensive review of the research and applications of retinal vessel quantification technology in ocular and systemic diseases, which could update clinicians and researchers on the recent progress in this field.

Chinese expert consensus on the diagnosis and treatment of contact lens-associated dry eye (2024)

The number of contact lens wearers in China is increasing rapidly. Long-term contact lens wearing may induce or exacerbate tear film instability, and consequently affect the visual quality, ocular surface safety, and compliance of the wearers. To promote the safety and effectiveness of contact lens fitting, and to improve the visual quality and satisfaction of contact lens wearers, the Society of Contact Lens Safety Monitoring & Vision Health of Chinese Health Association has targeted to develop an expert consensus on the diagnosis and treatment of contact lens-associated dry eye. By referring to relevant literature and summarizing clinical experience, the clinical experts in corneal disease, pediatric ophthalmology and optometry have made repeated discussions to form this consensus, including the definition, pathological mechanisms, influencing factors, evaluation, prevention and treatment of contact lens-associated dry eye, for the reference of optometrists and ophthalmologists.

Noninvasive screening of ocular surface disease in otherwise healthy patients scheduled for cataract surgery.

To evaluate prevalence and characteristics of pathological ocular surface findings in healthy patients undergoing cataract surgery using a noninvasive ocular surface workup and a validated questionnaire. Prospective single-centre study (sub-analysis clinical trial no. NCT05754437). Healthy patients undergoing senile cataract surgery were screened preoperatively by Oculus Keratograph (K5 M; Oculus GmbH, Wetzlar, Germany) for the evaluation of tear meniscus height (TMH), non-invasive keratograph break-up time (NIKBUT), and meibomian gland dropout. Ocular discomfort symptoms were scored by ocular surface disease index (OSDI) questionnaire. 120 eyes of 120 patients (62 females, 58 males; mean age 73.85 years, range 47-91 years) were included. All patients had at least 1 abnormal finding, while 19 (15.8%; 95% CI [0.09-0.22]) had alterations of all parameters. In detail, 39 patients (32.5%; 95% CI [0.24-0.41]) had pathological TMH (mean 0,15 mm [0.03 SD]), 102 (85%; 95% CI [0.79-0.91]) had pathological NIKBUT (mean 3.64 s [2.63 SD]), 117 (97.5%; 95% CI [0.95-1]) had some degree of gland dropout (mean 1.62 [0.70 SD]), 78 patients (65%; 95% CI [0.56-0.74]) had pathological OSDI scores (mean 28.63 [15.08 SD]). Using TFOS DEWS II criteria, 66 patients (55%; 95% CI [0.42-0.60]) resulted affected by dry eye. This quick noninvasive screening documented the high prevalence of pathological ocular surface parameters in patients without risk factors or previous diagnosis of dry eye who are scheduled for cataract surgery.

Utilizing visual symptoms to distinguish dry eye from glaucoma, cataract, and suspect glaucoma patients: a cross-sectional study

BackgroundThe diagnosis of dry eye and other common ophthalmological conditions can be supported using patient reported symptoms, which is increasingly useful in contexts such as telemedicine. We aim to ascertain visual symptoms that differentiate dry eye from cataract, glaucoma, or glaucoma suspects.MethodsAdults with dry eye, glaucoma, cataract, and suspected glaucoma (controls) completed a questionnaire to rate the frequency and severity of 28 visual symptoms. Univariate, followed by multivariable logistic regression with backward stepwise selection (p < 0.05), determined the individual symptoms and set of symptoms best distinguishing dry eye from each of the other conditions.ResultsMean age of 353 patients (94 glaucoma suspect controls, 79 glaucoma, 84 cataract, and 96 dry eye) was 64.1 years (SD = 14.1); 67% were female and 68% White. Dry eye patients reported more frequent light sensitivity (OR = 15.0, 95% CI = 6.3–35.7) and spots in vision (OR = 2.8, 95% CI = 1.2–6.3) compared to glaucoma suspect controls. Compared to glaucoma patients, dry eye patients experienced more frequent light sensitivity (OR = 9.2, 95% CI = 2.0–41.7), but less frequent poor peripheral vision (OR = 0.2, 95% CI = 0.06–0.7), difference in vision between eyes (OR = 0.09, 95% CI = 0.01–0.7), and missing patches of vision (OR = 0.06, 95% CI = 0.009–0.3). Compared to cataract patients, dry eye patients reported more frequent spots in vision (OR = 4.5, 95% CI = 1.5–13.4) and vision variability across the week (OR = 4.7, 95% CI = 1.2–17.7) and were less likely to report worsening vision (OR = 0.1, 95% CI = 0.03–0.4) and blindness (OR = 0.1, 95% CI = 0.02–0.8).ConclusionVisual symptoms may serve as a complementary tool to distinguish dry eye from various ocular conditions, though the symptoms that best distinguish dry eye differ across comparisons. Differentiating how patients visually perceive common eye diseases may be used in a variety of clinical settings to rule out specific conditions.

Association between dry eye and periodontal disease in community-dwelling Japanese adults: data from the Uonuma cohort study

BackgroundWhile research has explored the risk of periodontal disease in various eye conditions, the link between dry eye and periodontal disease remains underexplored, especially in Japanese adults. This study aims to investigate the association between dry eye and periodontal disease in community-dwelling Japanese adults.MethodsThis study is a subset of the Uonuma cohort study, which includes Japanese adults aged 40 years and older residing in the Uonuma area of Niigata Prefecture, Japan. Participants completed a self-administered, paper-based questionnaire. Statistical analyses, including the chi-square test, independent t test, ANOVA test, and logistic regressions, were employed to assess the association of periodontal disease with independent variables.ResultsAmong 36,488 participants (average age 63.3 years, 47.4% men), 39.3% had a history of periodontal disease, and gender differences were statistically significant (p < 0.001). Significant associations were found between periodontal disease and dry eye diagnosis or symptoms. Univariable logistic regression revealed links between periodontal disease and age, gender, living status, alcohol consumption, remaining teeth, bite molar availability, and history of dry eye disease or symptoms. Multiple-adjusted regression found that doctor-diagnosed dry eye was associated with a higher likelihood of periodontal disease (odds ratio, 1.12; 95% confidence interval, 1.03–1.22). Participants who never experienced dryness or foreign body sensation had lower ORs of periodontal disease than those who always experienced such symptoms across all models.ConclusionA significant correlation was found between dry eye and periodontal disease in Japanese adults. Regular check-ups, early detection, and effective management of both conditions are strongly recommended.