The association of dry eye disease signs and symptoms with anxiety and depression: An observational study

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Methods In this observational study, we recruited 63 volunteers, including 51 patients with dry eye disease (DED) and 12 healthy volunteers. Infrared images of the meibomian gland and corneal nerve layer analysis of all patients were assessed. Additionally, the patients completed Hospital Anxiety and Depression Scale (HADS) questionnaire, Ocular Surface Disease Index (OSDI), and dry eye symptom questionnaire. Results HADS-anxiety and HADS-depression scores in the DED group were significantly higher than those in the control group ( t = 5.846, P \(<\) 0.001, and t = 4.006, P \(<\) 0.001, respectively). HADS-anxiety and HADS-depression was significantly correlated with DED symptoms ( P < 0.05). There was a significant positive correlation between the OSDI and HADS ( P < 0.001). There was a significant correlation between HADS-anxiety and mebomian gland area ( r = -0.426, P < 0.001) and corneal nerve density ( r = -0.345, P < 0.001); HADS-depression was found to be correlated with mebomian gland area ( r = -0.517, P < 0.001) and corneal nerve density ( r = -0.242, P = 0.016). The predictive equation for HADS-anxiety is as follows: HADS-anxiety = 0.09989*OSDI + -0.00013*CND + -22.54*MGA + 7.128 ( P < 0.0001). The predictive equation for HADS-depression is as follows: HADS-depression = 0.06743*OSDI + -18.01*MGA + 5.019 ( P < 0.0001). Conclusion Anxiety and depression were significantly correlated with OSDI, CND and MGA in patients with DED. Furthermore, OSDI, CND and MGA have a relatively value for HADS-anxiety and HADS-depression. Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Dry eye disease (DED) is a multifactorial ocular surface disease characterized by loss of tear film homeostasis and ocular symptoms. DED can seriously affects patients’ quality of life and psychological state, among which anxiety and depression are two common mood disorders. Many previous studies[ 1 , 2 ] focused on the relationship between DED and anxiety and depression, exploring the relationship between various evaluation parameters of DED and anxiety as well as depression. It has been demonstrated that anxiety, depression, and DED may some same pathogenesis pathway. Furthermore, anxiety and depression have been shown to be significantly correlated with DED symptoms, but not with signs of DED, such as tear meniscus height (TMH) and tear film break-up time (TBUT). However, with our further understanding of dry eye, in addition to TBUT and TMH, some other signs are used to evaluate DED. Meibomian gland dysfunction (MGD) is common cause of DED. It is also known that the damage of corneal nerves plays an important role in DED. Previous research did not focus on the association between DED signs of meibomian gland and cornea and anxiety and depression. Therefore, in this study, we used Hospital Anxiety and Depression Scale (HADS) to evaluate the psychological state of the patients, and we used corneal nerve density and meibomian gland area to determine the correlation between meibomian glands and corneal nerve parameters and anxiety and depression in patients with DED. METHODS Subjects A total of 51 patients with DED (102 eyes) who represented to the Peking University Third Hospital Department of Ophthalmology, and 12 healthy volunteers (24 eyes) without signs, symptoms, or other ocular problems who responded to our advertisement, were enrolled from June 2020 to December 2020. The diagnostic criteria for DED are as follows: (1) occurrence of any of the following ten symptoms for at least three months: dry eye, burning, foreign body sensation, photophobia, soreness, visual fatigue, tears in the wind, blurred vision, itch, and increased secretion; (2) TBUT \(\le\) 5 s; or (3) TBUT value between 5 to 10 s and corneal fluorescein staining (+). Demographic data of participants were collected using questionnaire. All questionnaires were completed before the examinations and treatments to ensure that the clinical experience did not affect the participants’ answers. All the examinations were performed by the same experienced clinician. Symptoms Assessment The participants were asked to rate their DED symptoms according to the visual analog score, which included 10 questions related to DED symptoms, including dryness, burning, foreign body sensation, photophobia, pain, asthenopia, watering, blurred vision, itching, and increased secretions. Participants were asked to rate each symptom from “not present (score 0)” to “very serious (score 10)”. OSDI Questionnaire[ 3 ] has been widely used to evaluate symptoms in patients with DED. The OSDI includes 12 questions grouped by poor symptoms/visual disturbances, visual function/tasks, and environmental questions. The final OSDI score was calculated using the formula (OSDI score \(\text{=}\) sum of questionnaire scores \(\text{×}\) 25/number of answered questions), accounting for the fact that questions 6–12 are optional. All the subjects finished these two evaluations. Signs Assessment Meibomian gland evaluation Non-contact infrared meibomian imaging is an optical imaging technology used to capture the morphology of the meibomian gland. This technique uses infrared transillumination and requires eyelid ectropion. Tarsal photographs of the two eyelids of each participant were obtained by the same experienced researcher using an Oculus Keratograph 5M (K5M; Oculus GmbH, Wetzlar, Germany). All photographs were obtained in the same room under the same controlled lighting conditions. RGB (red-green-blue) infrared characteristic images were obtained with a resolution of 1360 × 1024 pixels and, exported to Image J software (Wayne Rasband, National Institutes of Health, Bethesda, MD) to analyze the pixel intensity and meibomian gland area. Corneal nerve density An in vivo confocal microscope (IVCM) was used to observe the corneal microstructure. All patients were examined using a digital corneal confocal laser-scanning microscope (HRT II RCM Heidelberg Engineering Inc., Heidelberg, Germany, Rostock Cornea Module) equipped with the built-in software Heidelberg Eye Explorer version 1.5.10.0. Two-dimensional images with a definition of 384 × 384 pixels over an area of 400 µm × 400 µm, lateral spatial resolution of 0.5 µm, and depth resolution of 1–2 µm were captured. For each eye, 30 to 40 images were acquired from the corneal epithelium to the endothelium. For each eye, five images of the corneal sub-basal region were selected by a single masked investigator, and Image J software (Wayne Rasband, National Institutes of Health, Bethesda, MD) was used to trace and measure the corneal nerve density (the total length of all nerve fibers within a frame, µm/mm 2 ). Psychological Status Evaluation HADS[ 4 ] was used to assess patients’ anxiety and depression status. The scale includes 14 questions, with seven concerning anxiety and seven on depression. Each question has four options, corresponding to 0–3 points. After each participant completed in the questionnaire, the scores were added to obtain their anxiety and depression scores. Statistical Analysis GraphPad Prism 9.0.0 and SPSS 26 were used to analyze the data. The demographic data, ophthalmic examination data and HADS of the DED and control groups were compared by the Student’s t-test and χ2 test. The correlation matrix analysis of continuous variables was performed using Pearson’s r test. The correlation analysis of categorical variables was performed using independent sample t-test or ANOVA. P values \(<\) 0.05 were considered statistically significant. RESULTS Demographic characteristics of the participants Demographic characteristics are presented in Table 1 . The study population included 63 participants with 51 having DED and 12 healthy volunteers. There were no significant differences in age, body mass index, or smoking history between the two groups, except for sex ( P = 0.018). HADS was significantly correlated with DED symptoms and OSDI We conducted an independent sample t-test on the HADS-anxiety and HADS-depression scores of the DED and control groups. Both HADS-anxiety and HADS-depression scores were higher in the DED group than in the control group ( t = 5.846, P \(<\) 0.001, and t = 4.006, P \(<\) 0.001, respectively), as shown in Fig. 1 . Table 1 Demographic characteristics of the study population DED group Control group P value Age (years) 51.9 44.8 0.158 BMI (kg/m 2 ) 22.41 23.93 0.170 Sex, n (%) 0.018 Male 9 (17.65%) 6 (50.00%) Female 42 (82.35%) 6 (50.00%) Smoking history (years) 13.65 8.33 0.831 Education level, n (%) 0.433 Primary school or less 6 (11.76%) 1 (8.33%) Middle school 12 (23.53%) 1 (8.33%) College or higher 33 (64.71%) 10 (83.33%) DED, dry eye disease; BMI, body mass index. We conducted a correlation matrix analysis of all continuous variables, the results of which are shown in Fig. 2 and Table 2 . HADS-anxiety was significantly positively correlated with DED symptoms including dryness ( r = 0.322, P = 0.001), foreign body sensation ( r = 0.357, P < 0.001), photophobia ( r = 0.392, P < 0.001), eye strain ( r = 0.287, P = 0.003), watering ( r = 0.268, P = 0.006), and blurred vision ( r = 0.296, P = 0.003). HADS-depression was significantly positively correlated with DED symptoms including dryness ( r = 0.295, P = 0.003), foreign body sensation ( r = 0.414, P \(<\) 0.001), photophobia ( r = 0.411, P = 0.004), eye strain ( r = 0.252, P = 0.011), watering ( r = 0.313, P = 0.001), and blurred vision ( r = 0.235, P = 0.018). In addition, there was a significant positive correlation between the OSDI and HADS-anxiety and HADS-depression ( r = 0.448, P < 0.001, r = 0.407, P < 0.001, respectively). HADS was significantly correlated with meibomian gland area and corneal nerve density There was a significant correlation between HADS-anxiety and mebomian gland area ( r = -0.426, P < 0.001) and corneal nerve density ( r = -0.345, P < 0.001); HADS-depression was found to be correlated with mebomian gland area ( r = -0.517, P < 0.001) and corneal nerve density ( r = -0.242, P = 0.016), as shown in Fig. 2 and Table 2 . Table 2 The correlation matrix analysis of HADS and continuous variables. HADS-anxiety HADS-depression r P value r P value Age 0.305 0.002 ** 0.311 0.001 ** BMI 0.014 0.893 -0.032 0.751 Dryness 0.322 0.001 ** 0.295 0.040 * Burning 0.156 0.118 0.186 0.036 * Foreign body sensation 0.357 *** 0.414 *** Photophobia 0.392 *** 0.411 0.004 ** Pain 0.009 0.926 0.045 0.652 Eye strain 0.287 0.003 ** 0.252 0.030 * Watering 0.268 0.006 ** 0.313 0.014 Blurred vision 0.296 0.003 ** 0.235 0.077 Itching 0.072 0.475 0.183 0.272 Increased secretions 0.119 0.234 0.114 0.234 OSDI 0.458 0.008 ** 0.448 0.001 ** CND -0.345 0.015 * -0.242 0.292 MGA -0.424 0.040 * -0.516 0.008 ** *: P \(<\) 0.05; **: P \(<\) 0.01; ***: P \( 8, patients are more likely to suffer from anxiety or depression. HADS-anxiety or HADS-depression > 8 points are recorded as "1", and < 8 points are recorded as "0". We conducted logistic regression analysis on HADS and OSDI, DED signs, which is shown in Table 3 and Table 4 . The predictive equation for HADS-anxiety is as follows: HADS-anxiety = 0.09989*OSDI + -0.00013*CND + -22.54*MGA + 7.128 ( P < 0.0001). The area under ROC curve is 0.8953. The positive predictive power and the negative predictive power are 83.33% and 79.49%, respectively. The predictive equation for HADS-depression is as follows: HADS-depression = 0.06743*OSDI + -18.01*MGA + 5.019 ( P < 0.0001). The area under ROC curve is 0.8953. The positive predictive power and the negative predictive power are 83.33% and 79.49%, respectively. The area under ROC curve is 0.8481. The positive predictive power and the negative predictive power are 78.18% and 73.68%, respectively. The ROC curve is shown in Fig. 3 . Table 3 classification table of predictive model for HADS-anxiety Predicted 0 Predicted 1 Total % correctly clssified Observed 0 31 9 40 77.50 Observed 1 8 45 53 84.91 Total 39 54 93 81.72 Table 4 classification table of predictive model for HADS-depression Predicted 0 Predicted 1 Total % correctly clssified Observed 0 28 12 40 70.00 Observed 1 10 43 53 81.13 Total 38 55 93 76.34 DISCUSSION In this study, we found that patients with DED had higher HADS-anxiety and HADS-depression scores than those of healthy individuals. In DED group, the HADS-anxiety and HADS-depression scores were significantly positively correlated with OSDI, corneal nerve density and meibomian gland area. In addition, HADS-anxiety and HADS-depression were correlated with the scores of several DED symptoms including dryness, burning, foreign body sensation, photophobia, eye strain, and watering. Previous studies[ 1 , 5 – 7 ] have shown that patients with DED are more anxious and depressed than those without DED, which is consistent with our findings. Li et al.[ 1 ] reported that the Zung Self Rating Anxiety Scales and the Zung Self Rating Depression Scales scores were positively correlated with the OSDI. In a large population-based study, van der Vaart R[ 5 ] found that there were statistically significant associations between DED and depression and anxiety, respectively. However, Mertzanis’s study[ 8 ] demonstrated that there was no difference in psychological health between DED and control groups. Mertzanis et al.’s study used Short Form-36, to evaluate subjects’ psychological status. The Short Form-36 evaluated the following areas of health: physical functioning, role limitations due to physical problems (role-physical), bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems (role-emotional), and mental health. Therefore, it evaluates not only subjects’ anxiety and depression, but also other areas of health, which may be the reason why their results were different from ours. We found that in the DED group, HADS-anxiety and HADS-depression were significantly correlated with several DED symptoms and OSDI. Several previous studies[ 1 , 9 , 10 ] have shown a significant correlation between anxiety and, depression and subjective symptoms of DED. The OSDI is widely used to assess the severity of symptoms in patients with dry eye. DED syndromes such as pain, burning, and photophobia can induce anxiety and depression, which can explain why HADS is significantly associated with OSDI and DED symptom scores. Li et al.[ 1 ] suggested that people with more severe anxiety and depression tend to describe the symptoms of DED more seriously, resulting in higher OSDI scores. Conversely, DED symptoms may increase depression and anxiety symptoms[ 11 ]. Chronic pain can induce anxiety and depression, which could explain our findings. We found that both HADS-anxiety and HADS-depression were significantly correlated with corneal nerve density. Corder et al[ 12 ] identified a distinct neural ensemble in the basolateral amygdala that encodes the negative affective valence of pain. They found that the neural ensemble can be sensitized by peripheral nerve injury, resulting in people being more likely to have negative emotions, such as anxiety, about stimuli. Held[ 13 ] found that peripheral nerve injury was correlated with depression and anxiety, which is similar to our findings. In Held’s study, people with neurological pain had lower pain threshold. As a peripheral nerve, corneal nerves are injured in DED patients, which could cause a lower pain threshold and make these patients feel more anxious. In the DED group, we also found that both HADS-anxiety and HADS-depression were significantly correlated with the meibomian gland area. It is well known that MGD is one of the most common causes of DED, and the reduction in meibomian gland area is one of the causes of MGD. In a multi-center study, Wei[ 14 ] found that the prevalence of depression in the MGD group was significantly higher than that in normal controls, which supports our results. According to the current research, there are several reasons why depression is correlated with the meibomian gland area. First, reduction in meibomian gland area leads to insufficient tear secretion, resulting in tear hyperosmolarity. Studies have shown that tear hyperosmolarity may lead to ocular surface inflammation and nerve damage, resulting in dry eye symptoms. Dry eye symptoms, such as pain and photophobia can cause negative emotional experiences, which can lead to anxiety and depression. Second, Chhadva[ 15 ] reported that compared with individuals without DED, patients with DED have higher levels of serotonin, interleukin-6, and tumor necrosis factor-α in tears and blood. These cytokines can affect the function of the meibomian glands and lipid layer of the tear, which plays an important role in MGD pathogenesis[ 15 – 17 ]. In addition, previous studies[ 16 , 18 – 20 ] have shown that changes in serotonin levels are related to mental disorders, such as anxiety and depression. As reported previously, mental status and meibomian gland function have close relation[ 21 – 24 ], which could explain the correlation between HADS and meibomian gland area. Third, Yu et al.[ 25 ] found that regional homogeneity values of some special brain regions, such as the middle frontal gyrus, were significantly lower in MGD patients than in healthy controls. These abnormalities can result in depression[ 26 ]. Yu’s findings suggest that DED, especially MGD, could induce depression.[ 27 ] In previous studies, no significant correlation was observed between psychological status and clinical signs of DED, such as TBUT and TMH.[ 1 , 28 , 29 ] However, in our study, we used IVCM and Oculus Keratograph 5M to evaluate clinical signs of DED (corneal nerve density and mebomian gland area), which can have a more intuitive and accurate description of corneal and mebomian gland damage than TBUT and TMH. The results showed that there is a significant correlation between DED signs and HADS. Meanwhile, the model showed a good predictive value for HADS. As mentioned before, there may be similar pathogenesis between the damage of corneal nerve, mebomian gland and anxiety, depression. Therefore, it is of good significance to do research on the relationship between DED signs and anxiety, depression in the future. To our knowledge, this is the first study to analyze the relationship between corneal nerve density and, meibomian gland area and anxiety and depression in patients with DED. We found that anxiety and depression are not only related to OSDI, but also to corneal nerve density and meibomian gland area. Besides, our study put forward a predictive model on HADS based on OSDI, CND and MGA, which is of great importance. We provided a reminder for ophthalmologists to realize the complexity of DED and psychological disorders. Examination of corneal nerve density and the meibomian glands can help ophthalmologists identify patients with DED who may have psychological disorders. In addition, owing to the interaction between DED and anxiety and depression, ophthalmologists need to pay attention to the emotional comfort of DED patients in clinical work and ensure that patients receive proper psychotherapy in time. Our study had the following limitations. First, the sample size was small. Large-scale research on this topic is needed in the future. Second, in addition to the HADS, other methods can be employed to measure patients' anxiety and depression. Declarations Ethical approval The study was performed following the Declaration of Helsinki and approved by Peking University Third Hospital’s ethical committee. All participants provided written informed consents to participate and to publish before the study. Participants’ personal information was well protected. Funding There is no funding for this research DISCLOSURES All authors declare that they have no conflict of interest. An Observative Research of the Impact of Intraocular Lens (IOL) Loading Methods on the Adhesion Phenomenon during Cataract Surgery AUTHORS’ CONTRIBUTION Study concept and design (Wang Yiren, Jiang Xiaodan, Li Xuemin); data collection (Wang Yiren, Li Jiaxi); analysis and interpretation (Wang Yiren); writing the manuscript (Wang Yiren); critical reversion of the manuscript (Jiang Xiaodan, Lixuemin); supervision (Jiang Xiaodan, Lixuemin). References Li M, Gong L, Sun X, Chapin WJ: Anxiety and Depression in Patients with Dry Eye Syndrome. Current Eye Research 2011, 36(1):1–7. Wang T-J, Wang I-J, Hu C-C, Lin H-C: Comorbidities of dry eye disease: a nationwide population-based study. Acta Ophthalmologica 2012, 90(7):663–668. Pult H, Wolffsohn JS: The development and evaluation of the new Ocular Surface Disease Index-6. Ocul Surf 2019, 17(4):817–821. Zigmond AS, Snaith RP: The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica 1983, 67(6):361–370. van der Vaart R, Weaver MA, Lefebvre C, Davis RM: The association between dry eye disease and depression and anxiety in a large population-based study. Am J Ophthalmol 2015, 159(3):470–474. Ulusoy MO, Işık-Ulusoy S, Kıvanç SA: Evaluation of dry eye disease in newly diagnosed anxiety and depression patients using anterior segment optical coherence tomography. Eye Vis (Lond) 2019, 6:25–25. Kitazawa M, Sakamoto C, Yoshimura M, Kawashima M, Inoue S, Mimura M, Tsubota K, Negishi K, Kishimoto T: The Relationship of Dry Eye Disease with Depression and Anxiety: A Naturalistic Observational Study. Transl Vis Sci Technol 2018, 7(6):35–35. Mertzanis P, Abetz L, Rajagopalan K, Espindle D, Chalmers R, Snyder C, Caffery B, Edrington T, Simpson T, Nelson JD et al : The relative burden of dry eye in patients' lives: comparisons to a U.S. normative sample. Invest Ophthalmol Vis Sci 2005, 46(1):46–50. Yilmaz U, Gokler ME, Unsal A: Dry eye disease and depression-anxiety-stress: A hospital-based case control study in Turkey. Pak J Med Sci 2015, 31(3):626–631. Bitar MS, Olson DJ, Li M, Davis RM: The Correlation Between Dry Eyes, Anxiety and Depression: The Sicca, Anxiety and Depression Study. Cornea 2019, 38(6). Galor A, Feuer W, Lee DJ, Florez H, Faler AL, Zann KL, Perez VL: Depression, Post-traumatic Stress Disorder, and Dry Eye Syndrome: A Study Utilizing the National United States Veterans Affairs Administrative Database. Am J Ophthalmol 2012, 154(2):340–346.e342. Corder G, Ahanonu B, Grewe BF, Wang D, Schnitzer MJ, Scherrer G: An amygdalar neural ensemble that encodes the unpleasantness of pain. Science 2019, 363(6424):276–281. Held M, Karl F, Vlckova E, Rajdova A, Escolano-Lozano F, Stetter C, Bharti R, Förstner KU, Leinders M, Dušek L et al : Sensory profiles and immune-related expression patterns of patients with and without neuropathic pain after peripheral nerve lesion. Pain 2019, 160(10):2316–2327. Wei Z, Liang J, Cao K, Wang L, Baudouin C, Labbé A, Liang Q: A multi-center study evaluating the correlation between meibomian gland dysfunction and depressive symptoms. Sci Rep 2022, 12(1):443–443. Chhadva P, Lee T, Sarantopoulos CD, Hackam AS, McClellan AL, Felix ER, Levitt RC, Galor A: Human Tear Serotonin Levels Correlate with Symptoms and Signs of Dry Eye. Ophthalmology 2015, 122(8):1675–1680. Mrugacz M, Ostrowska L, Bryl A, Szulc A, Zelazowska-Rutkowska B, Mrugacz G: Pro-inflammatory cytokines associated with clinical severity of dry eye disease of patients with depression. Advances in medical sciences 2017, 62(2):338–344. Sharif NA, Senchyna M: Serotonin receptor subtype mRNA expression in human ocular tissues, determined by RT-PCR. Molecular vision 2006, 12:1040–1047. Ohayon MM, Schatzberg AF: Using chronic pain to predict depressive morbidity in the general population. Arch Gen Psychiatry 2003, 60(1):39–47. Croft PR, Papageorgiou AC, Ferry S, Thomas E, Jayson MI, Silman AJ: Psychologic distress and low back pain. Evidence from a prospective study in the general population. Spine 1995, 20(24):2731–2737. Sarac H, Markeljevic J, Mokrovic G, Erdeljic V, Bozina N, Cicin-Sain L: Platelet serotonin in primary Sjögren's syndrome: level and relation with disease activity. Journal of neuroimmunology 2012, 251(1–2):87–89. Sullivan DA: Tearful relationships? Sex, hormones, the lacrimal gland, and aqueous-deficient dry eye. Ocul Surf 2004, 2(2):92–123. Fernández-Guasti A, Fiedler JL, Herrera L, Handa RJ: Sex, stress, and mood disorders: at the intersection of adrenal and gonadal hormones. Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme 2012, 44(8):607–618. Kiecolt-Glaser JK, Belury MA, Porter K, Beversdorf DQ, Lemeshow S, Glaser R: Depressive symptoms, omega-6:omega-3 fatty acids, and inflammation in older adults. Psychosomatic medicine 2007, 69(3):217–224. Rashid S, Jin Y, Ecoiffier T, Barabino S, Schaumberg DA, Dana MR: Topical omega-3 and omega-6 fatty acids for treatment of dry eye. Arch Ophthalmol 2008, 126(2):219–225. Yu K, Guo Y, Ge QM, Su T, Shi WQ, Zhang LJ, Shu HY, Pan YC, Liang RB, Li QY et al : Altered spontaneous activity in the frontal gyrus in dry eye: a resting-state functional MRI study. Sci Rep 2021, 11(1):12943. Wen W, Wu Y, Chen Y, Gong L, Li M, Chen X, Yan M, Xiao Z, Sun X: Dry eye disease in patients with depressive and anxiety disorders in Shanghai. Cornea 2012, 31(6):686–692. Andrianopoulou A, Zikou AK, Astrakas LG, Gerolymatou N, Xydis V, Voulgari P, Kiortsis DN, Argyropoulou MI: Functional connectivity and microstructural changes of the brain in primary Sjögren syndrome: the relationship with depression. Acta radiologica (Stockholm, Sweden: 1987) 2020, 61(12):1684–1694. Sullivan BD, Crews LA, Messmer EM, Foulks GN, Nichols KK, Baenninger P, Geerling G, Figueiredo F, Lemp MA: Correlations between commonly used objective signs and symptoms for the diagnosis of dry eye disease: clinical implications. Acta Ophthalmologica 2014, 92(2):161–166. Vehof J, Sillevis Smitt-Kamminga N, Nibourg SA, Hammond CJ: Predictors of Discordance between Symptoms and Signs in Dry Eye Disease. Ophthalmology 2017, 124(3):280–286. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4448844","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309636375,"identity":"d662d88b-8801-4a0f-aa65-68fc1a1b9661","order_by":0,"name":"Yiren Wang","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yiren","middleName":"","lastName":"Wang","suffix":""},{"id":309636379,"identity":"8f9ef127-4660-488f-b696-2d36358a43d1","order_by":1,"name":"Xiaodan Jiang","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaodan","middleName":"","lastName":"Jiang","suffix":""},{"id":309636381,"identity":"c779318d-f6ae-41fe-8f21-28c7c8004c74","order_by":2,"name":"Jiaxi Li","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiaxi","middleName":"","lastName":"Li","suffix":""},{"id":309636383,"identity":"af9de06a-efe4-4d9a-8619-125d65d615a4","order_by":3,"name":"Xuemin Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACPgYGxgMMDDZy/AyMDcRpYQNioJY0Y8kGErUcSjQ4QKzD2CSyEw7z5hxIMD5/uO3BDwY7OV1ClrHxnN1wcOa2O3lmNxLbDXsYko3NCFnHxt674cDHbc+KzW4wtknwMBxI3EZQCzPvBqCyw4mb+w+2Sf4hSgvElsOJGxgS26SJswXilzRjiRtALTIGRPiFXyJ342PebcCo7D/+TPJNhZ0cQS1owIA05aNgFIyCUTAKcAAAi4BFsBVddi4AAAAASUVORK5CYII=","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xuemin","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-05-20 11:34:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4448844/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4448844/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57941591,"identity":"d7f87136-18f8-4f0c-84b8-9f9731731888","added_by":"auto","created_at":"2024-06-07 18:58:06","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186913,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of HADS scores between the DED group and control group. A: HADS-anxiety scores between the two groups; B: HADS-depression scores between the two groups.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4448844/v1/3e001b50fb5f164b5ca385b7.jpeg"},{"id":57941589,"identity":"b5869df0-980b-4a9c-b564-5529d94aeff3","added_by":"auto","created_at":"2024-06-07 18:58:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43915,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation matrix analysis of continuable variables. A: the correlation coefficient \u003cem\u003er\u003c/em\u003e of HADS. Green indicates that the two variables are negatively correlated, and red indicates that the two variables are positively correlated.; B: P value for correlation analysis. White indicates that the P \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Onlinefigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4448844/v1/cb8ef840706a264a40f08e37.png"},{"id":57941590,"identity":"4355ef41-3902-4c67-b3c3-093d5d2673d4","added_by":"auto","created_at":"2024-06-07 18:58:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23143,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curve of HADS-anxiety and HADS-depression.\u003c/p\u003e","description":"","filename":"Onlinefigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4448844/v1/5c2017c898e051728343f9f2.png"},{"id":59045779,"identity":"e681a96e-13cf-4e05-ac72-0a94620a9a74","added_by":"auto","created_at":"2024-06-25 18:24:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":864336,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4448844/v1/ac148612-d904-40bc-96e3-9341d13a56ef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association of dry eye disease signs and symptoms with anxiety and depression: An observational study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDry eye disease (DED) is a multifactorial ocular surface disease characterized by loss of tear film homeostasis and ocular symptoms. DED can seriously affects patients\u0026rsquo; quality of life and psychological state, among which anxiety and depression are two common mood disorders. Many previous studies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] focused on the relationship between DED and anxiety and depression, exploring the relationship between various evaluation parameters of DED and anxiety as well as depression. It has been demonstrated that anxiety, depression, and DED may some same pathogenesis pathway. Furthermore, anxiety and depression have been shown to be significantly correlated with DED symptoms, but not with signs of DED, such as tear meniscus height (TMH) and tear film break-up time (TBUT).\u003c/p\u003e \u003cp\u003eHowever, with our further understanding of dry eye, in addition to TBUT and TMH, some other signs are used to evaluate DED. Meibomian gland dysfunction (MGD) is common cause of DED. It is also known that the damage of corneal nerves plays an important role in DED. Previous research did not focus on the association between DED signs of meibomian gland and cornea and anxiety and depression. Therefore, in this study, we used Hospital Anxiety and Depression Scale (HADS) to evaluate the psychological state of the patients, and we used corneal nerve density and meibomian gland area to determine the correlation between meibomian glands and corneal nerve parameters and anxiety and depression in patients with DED.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eA total of 51 patients with DED (102 eyes) who represented to the Peking University Third Hospital Department of Ophthalmology, and 12 healthy volunteers (24 eyes) without signs, symptoms, or other ocular problems who responded to our advertisement, were enrolled from June 2020 to December 2020. The diagnostic criteria for DED are as follows: (1) occurrence of any of the following ten symptoms for at least three months: dry eye, burning, foreign body sensation, photophobia, soreness, visual fatigue, tears in the wind, blurred vision, itch, and increased secretion; (2) TBUT \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\le\\)\u003c/span\u003e\u003c/span\u003e 5 s; or (3) TBUT value between 5 to 10 s and corneal fluorescein staining (+). Demographic data of participants were collected using questionnaire. All questionnaires were completed before the examinations and treatments to ensure that the clinical experience did not affect the participants\u0026rsquo; answers. All the examinations were performed by the same experienced clinician.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eSymptoms Assessment\u003c/h2\u003e \u003cp\u003eThe participants were asked to rate their DED symptoms according to the visual analog score, which included 10 questions related to DED symptoms, including dryness, burning, foreign body sensation, photophobia, pain, asthenopia, watering, blurred vision, itching, and increased secretions. Participants were asked to rate each symptom from \u0026ldquo;not present (score 0)\u0026rdquo; to \u0026ldquo;very serious (score 10)\u0026rdquo;.\u003c/p\u003e \u003cp\u003eOSDI Questionnaire[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] has been widely used to evaluate symptoms in patients with DED. The OSDI includes 12 questions grouped by poor symptoms/visual disturbances, visual function/tasks, and environmental questions. The final OSDI score was calculated using the formula (OSDI score \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{=}\\)\u003c/span\u003e\u003c/span\u003e sum of questionnaire scores \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{\u0026times;}\\)\u003c/span\u003e\u003c/span\u003e 25/number of answered questions), accounting for the fact that questions 6\u0026ndash;12 are optional. All the subjects finished these two evaluations.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSigns Assessment\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eMeibomian gland evaluation\u003c/h2\u003e \u003cp\u003eNon-contact infrared meibomian imaging is an optical imaging technology used to capture the morphology of the meibomian gland. This technique uses infrared transillumination and requires eyelid ectropion. Tarsal photographs of the two eyelids of each participant were obtained by the same experienced researcher using an Oculus Keratograph 5M (K5M; Oculus GmbH, Wetzlar, Germany). All photographs were obtained in the same room under the same controlled lighting conditions. RGB (red-green-blue) infrared characteristic images were obtained with a resolution of 1360 \u0026times; 1024 pixels and, exported to Image J software (Wayne Rasband, National Institutes of Health, Bethesda, MD) to analyze the pixel intensity and meibomian gland area.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCorneal nerve density\u003c/h2\u003e \u003cp\u003eAn in vivo confocal microscope (IVCM) was used to observe the corneal microstructure. All patients were examined using a digital corneal confocal laser-scanning microscope (HRT II RCM Heidelberg Engineering Inc., Heidelberg, Germany, Rostock Cornea Module) equipped with the built-in software Heidelberg Eye Explorer version 1.5.10.0. Two-dimensional images with a definition of 384 \u0026times; 384 pixels over an area of 400 \u0026micro;m \u0026times; 400 \u0026micro;m, lateral spatial resolution of 0.5 \u0026micro;m, and depth resolution of 1\u0026ndash;2 \u0026micro;m were captured. For each eye, 30 to 40 images were acquired from the corneal epithelium to the endothelium. For each eye, five images of the corneal sub-basal region were selected by a single masked investigator, and Image J software (Wayne Rasband, National Institutes of Health, Bethesda, MD) was used to trace and measure the corneal nerve density (the total length of all nerve fibers within a frame, \u0026micro;m/mm\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePsychological Status Evaluation\u003c/h2\u003e \u003cp\u003eHADS[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] was used to assess patients\u0026rsquo; anxiety and depression status. The scale includes 14 questions, with seven concerning anxiety and seven on depression. Each question has four options, corresponding to 0\u0026ndash;3 points. After each participant completed in the questionnaire, the scores were added to obtain their anxiety and depression scores.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eGraphPad Prism 9.0.0 and SPSS 26 were used to analyze the data. The demographic data, ophthalmic examination data and HADS of the DED and control groups were compared by the Student\u0026rsquo;s t-test and \u003cem\u003eχ2\u003c/em\u003e test. The correlation matrix analysis of continuous variables was performed using Pearson\u0026rsquo;s r test. The correlation analysis of categorical variables was performed using independent sample t-test or ANOVA. \u003cem\u003eP\u003c/em\u003e values \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of the participants\u003c/h2\u003e \u003cp\u003eDemographic characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The study population included 63 participants with 51 having DED and 12 healthy volunteers. There were no significant differences in age, body mass index, or smoking history between the two groups, except for sex (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHADS was significantly correlated with DED symptoms and OSDI\u003c/h2\u003e \u003cp\u003eWe conducted an independent sample t-test on the HADS-anxiety and HADS-depression scores of the DED and control groups. Both HADS-anxiety and HADS-depression scores were higher in the DED group than in the control group (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.846, \u003cem\u003eP\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001, and \u003cem\u003et\u003c/em\u003e = 4.006, \u003cem\u003eP\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001, respectively), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDED group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (17.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (50.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (82.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (50.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (11.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (23.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (64.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (83.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDED, dry eye disease; BMI, body mass index.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe conducted a correlation matrix analysis of all continuous variables, the results of which are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. HADS-anxiety was significantly positively correlated with DED symptoms including dryness (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.322, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), foreign body sensation (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.357, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), photophobia (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.392, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), eye strain (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.287, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), watering (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.268, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), and blurred vision (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.296, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). HADS-depression was significantly positively correlated with DED symptoms including dryness (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.295, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), foreign body sensation (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.414, \u003cem\u003eP\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001), photophobia (\u003cem\u003er\u003c/em\u003e = 0.411, \u003cem\u003eP\u003c/em\u003e = 0.004), eye strain (\u003cem\u003er\u003c/em\u003e = 0.252, \u003cem\u003eP\u003c/em\u003e = 0.011), watering (\u003cem\u003er\u003c/em\u003e = 0.313, \u003cem\u003eP\u003c/em\u003e = 0.001), and blurred vision (\u003cem\u003er\u003c/em\u003e = 0.235, \u003cem\u003eP\u003c/em\u003e = 0.018).\u003c/p\u003e \u003cp\u003eIn addition, there was a significant positive correlation between the OSDI and HADS-anxiety and HADS-depression (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.448, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.407, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHADS was significantly correlated with meibomian gland area and corneal nerve density\u003c/h2\u003e \u003cp\u003eThere was a significant correlation between HADS-anxiety and mebomian gland area (\u003cem\u003er\u003c/em\u003e = -0.426, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and corneal nerve density (\u003cem\u003er\u003c/em\u003e = -0.345, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); HADS-depression was found to be correlated with mebomian gland area (\u003cem\u003er\u003c/em\u003e = -0.517, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and corneal nerve density (\u003cem\u003er\u003c/em\u003e = -0.242, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe correlation matrix analysis of HADS and continuous variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHADS-anxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHADS-depression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDryness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForeign body sensation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophobia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEye strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWatering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlurred vision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncreased secretions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e*: P \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.05; **: P \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.01; ***: P \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001.\u003c/p\u003e \u003cp\u003eCND, corneal nerve density; MGA, meibomian gland area.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHADS-anxiety and HADS-depression predictive model based on OSDI, CND and MGA.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIf HADS-anxiety or HADS-depression\u0026thinsp;\u0026gt;\u0026thinsp;8, patients are more likely to suffer from anxiety or depression. HADS-anxiety or HADS-depression\u0026thinsp;\u0026gt;\u0026thinsp;8 points are recorded as \"1\", and \u0026lt;\u0026thinsp;8 points are recorded as \"0\". We conducted logistic regression analysis on HADS and OSDI, DED signs, which is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The predictive equation for HADS-anxiety is as follows: HADS-anxiety\u0026thinsp;=\u0026thinsp;0.09989*OSDI + -0.00013*CND + -22.54*MGA\u0026thinsp;+\u0026thinsp;7.128 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The area under ROC curve is 0.8953. The positive predictive power and the negative predictive power are 83.33% and 79.49%, respectively. The predictive equation for HADS-depression is as follows: HADS-depression\u0026thinsp;=\u0026thinsp;0.06743*OSDI + -18.01*MGA\u0026thinsp;+\u0026thinsp;5.019 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The area under ROC curve is 0.8953. The positive predictive power and the negative predictive power are 83.33% and 79.49%, respectively. The area under ROC curve is 0.8481. The positive predictive power and the negative predictive power are 78.18% and 73.68%, respectively. The ROC curve is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eclassification table of predictive model for HADS-anxiety\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredicted 0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePredicted 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% correctly clssified\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eclassification table of predictive model for HADS-depression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredicted 0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePredicted 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% correctly clssified\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we found that patients with DED had higher HADS-anxiety and HADS-depression scores than those of healthy individuals. In DED group, the HADS-anxiety and HADS-depression scores were significantly positively correlated with OSDI, corneal nerve density and meibomian gland area. In addition, HADS-anxiety and HADS-depression were correlated with the scores of several DED symptoms including dryness, burning, foreign body sensation, photophobia, eye strain, and watering.\u003c/p\u003e \u003cp\u003ePrevious studies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] have shown that patients with DED are more anxious and depressed than those without DED, which is consistent with our findings. Li et al.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] reported that the Zung Self Rating Anxiety Scales and the Zung Self Rating Depression Scales scores were positively correlated with the OSDI. In a large population-based study, van der Vaart R[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] found that there were statistically significant associations between DED and depression and anxiety, respectively. However, Mertzanis\u0026rsquo;s study[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] demonstrated that there was no difference in psychological health between DED and control groups. Mertzanis et al.\u0026rsquo;s study used Short Form-36, to evaluate subjects\u0026rsquo; psychological status. The Short Form-36 evaluated the following areas of health: physical functioning, role limitations due to physical problems (role-physical), bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems (role-emotional), and mental health. Therefore, it evaluates not only subjects\u0026rsquo; anxiety and depression, but also other areas of health, which may be the reason why their results were different from ours.\u003c/p\u003e \u003cp\u003eWe found that in the DED group, HADS-anxiety and HADS-depression were significantly correlated with several DED symptoms and OSDI. Several previous studies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] have shown a significant correlation between anxiety and, depression and subjective symptoms of DED. The OSDI is widely used to assess the severity of symptoms in patients with dry eye. DED syndromes such as pain, burning, and photophobia can induce anxiety and depression, which can explain why HADS is significantly associated with OSDI and DED symptom scores. Li et al.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] suggested that people with more severe anxiety and depression tend to describe the symptoms of DED more seriously, resulting in higher OSDI scores. Conversely, DED symptoms may increase depression and anxiety symptoms[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Chronic pain can induce anxiety and depression, which could explain our findings.\u003c/p\u003e \u003cp\u003eWe found that both HADS-anxiety and HADS-depression were significantly correlated with corneal nerve density. Corder et al[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] identified a distinct neural ensemble in the basolateral amygdala that encodes the negative affective valence of pain. They found that the neural ensemble can be sensitized by peripheral nerve injury, resulting in people being more likely to have negative emotions, such as anxiety, about stimuli. Held[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found that peripheral nerve injury was correlated with depression and anxiety, which is similar to our findings. In Held\u0026rsquo;s study, people with neurological pain had lower pain threshold. As a peripheral nerve, corneal nerves are injured in DED patients, which could cause a lower pain threshold and make these patients feel more anxious.\u003c/p\u003e \u003cp\u003eIn the DED group, we also found that both HADS-anxiety and HADS-depression were significantly correlated with the meibomian gland area. It is well known that MGD is one of the most common causes of DED, and the reduction in meibomian gland area is one of the causes of MGD. In a multi-center study, Wei[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] found that the prevalence of depression in the MGD group was significantly higher than that in normal controls, which supports our results. According to the current research, there are several reasons why depression is correlated with the meibomian gland area. First, reduction in meibomian gland area leads to insufficient tear secretion, resulting in tear hyperosmolarity. Studies have shown that tear hyperosmolarity may lead to ocular surface inflammation and nerve damage, resulting in dry eye symptoms. Dry eye symptoms, such as pain and photophobia can cause negative emotional experiences, which can lead to anxiety and depression. Second, Chhadva[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] reported that compared with individuals without DED, patients with DED have higher levels of serotonin, interleukin-6, and tumor necrosis factor-α in tears and blood. These cytokines can affect the function of the meibomian glands and lipid layer of the tear, which plays an important role in MGD pathogenesis[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In addition, previous studies[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] have shown that changes in serotonin levels are related to mental disorders, such as anxiety and depression. As reported previously, mental status and meibomian gland function have close relation[\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which could explain the correlation between HADS and meibomian gland area. Third, Yu et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found that regional homogeneity values of some special brain regions, such as the middle frontal gyrus, were significantly lower in MGD patients than in healthy controls. These abnormalities can result in depression[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Yu\u0026rsquo;s findings suggest that DED, especially MGD, could induce depression.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn previous studies, no significant correlation was observed between psychological status and clinical signs of DED, such as TBUT and TMH.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] However, in our study, we used IVCM and Oculus Keratograph 5M to evaluate clinical signs of DED (corneal nerve density and mebomian gland area), which can have a more intuitive and accurate description of corneal and mebomian gland damage than TBUT and TMH. The results showed that there is a significant correlation between DED signs and HADS. Meanwhile, the model showed a good predictive value for HADS. As mentioned before, there may be similar pathogenesis between the damage of corneal nerve, mebomian gland and anxiety, depression. Therefore, it is of good significance to do research on the relationship between DED signs and anxiety, depression in the future.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first study to analyze the relationship between corneal nerve density and, meibomian gland area and anxiety and depression in patients with DED. We found that anxiety and depression are not only related to OSDI, but also to corneal nerve density and meibomian gland area. Besides, our study put forward a predictive model on HADS based on OSDI, CND and MGA, which is of great importance. We provided a reminder for ophthalmologists to realize the complexity of DED and psychological disorders. Examination of corneal nerve density and the meibomian glands can help ophthalmologists identify patients with DED who may have psychological disorders. In addition, owing to the interaction between DED and anxiety and depression, ophthalmologists need to pay attention to the emotional comfort of DED patients in clinical work and ensure that patients receive proper psychotherapy in time.\u003c/p\u003e \u003cp\u003eOur study had the following limitations. First, the sample size was small. Large-scale research on this topic is needed in the future. Second, in addition to the HADS, other methods can be employed to measure patients' anxiety and depression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed following the Declaration of Helsinki and approved by Peking University Third Hospital\u0026rsquo;s ethical committee. All participants provided written informed consents to participate and to publish before the study. Participants\u0026rsquo; personal information was well protected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no funding for this research\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDISCLOSURES\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAn Observative Research of the Impact of Intraocular Lens (IOL) Loading Methods on the Adhesion Phenomenon during Cataract Surgery\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS\u0026rsquo; CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design (Wang Yiren, Jiang Xiaodan, Li Xuemin); data collection (Wang Yiren, Li Jiaxi); analysis and interpretation (Wang Yiren); writing the manuscript (Wang Yiren); critical reversion of the manuscript (Jiang Xiaodan, Lixuemin); supervision (Jiang Xiaodan, Lixuemin).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi M, Gong L, Sun X, Chapin WJ: Anxiety and Depression in Patients with Dry Eye Syndrome. Current Eye Research 2011, 36(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang T-J, Wang I-J, Hu C-C, Lin H-C: Comorbidities of dry eye disease: a nationwide population-based study. Acta Ophthalmologica 2012, 90(7):663\u0026ndash;668.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePult H, Wolffsohn JS: The development and evaluation of the new Ocular Surface Disease Index-6. Ocul Surf 2019, 17(4):817\u0026ndash;821.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZigmond AS, Snaith RP: The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica 1983, 67(6):361\u0026ndash;370.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Vaart R, Weaver MA, Lefebvre C, Davis RM: The association between dry eye disease and depression and anxiety in a large population-based study. Am J Ophthalmol 2015, 159(3):470\u0026ndash;474.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUlusoy MO, Işık-Ulusoy S, Kıvan\u0026ccedil; SA: Evaluation of dry eye disease in newly diagnosed anxiety and depression patients using anterior segment optical coherence tomography. Eye Vis (Lond) 2019, 6:25\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitazawa M, Sakamoto C, Yoshimura M, Kawashima M, Inoue S, Mimura M, Tsubota K, Negishi K, Kishimoto T: The Relationship of Dry Eye Disease with Depression and Anxiety: A Naturalistic Observational Study. Transl Vis Sci Technol 2018, 7(6):35\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMertzanis P, Abetz L, Rajagopalan K, Espindle D, Chalmers R, Snyder C, Caffery B, Edrington T, Simpson T, Nelson JD \u003cem\u003eet al\u003c/em\u003e: The relative burden of dry eye in patients' lives: comparisons to a U.S. normative sample. Invest Ophthalmol Vis Sci 2005, 46(1):46\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYilmaz U, Gokler ME, Unsal A: Dry eye disease and depression-anxiety-stress: A hospital-based case control study in Turkey. Pak J Med Sci 2015, 31(3):626\u0026ndash;631.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBitar MS, Olson DJ, Li M, Davis RM: The Correlation Between Dry Eyes, Anxiety and Depression: The Sicca, Anxiety and Depression Study. Cornea 2019, 38(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGalor A, Feuer W, Lee DJ, Florez H, Faler AL, Zann KL, Perez VL: Depression, Post-traumatic Stress Disorder, and Dry Eye Syndrome: A Study Utilizing the National United States Veterans Affairs Administrative Database. Am J Ophthalmol 2012, 154(2):340\u0026ndash;346.e342.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorder G, Ahanonu B, Grewe BF, Wang D, Schnitzer MJ, Scherrer G: An amygdalar neural ensemble that encodes the unpleasantness of pain. Science 2019, 363(6424):276\u0026ndash;281.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeld M, Karl F, Vlckova E, Rajdova A, Escolano-Lozano F, Stetter C, Bharti R, F\u0026ouml;rstner KU, Leinders M, Dušek L \u003cem\u003eet al\u003c/em\u003e: Sensory profiles and immune-related expression patterns of patients with and without neuropathic pain after peripheral nerve lesion. Pain 2019, 160(10):2316\u0026ndash;2327.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei Z, Liang J, Cao K, Wang L, Baudouin C, Labb\u0026eacute; A, Liang Q: A multi-center study evaluating the correlation between meibomian gland dysfunction and depressive symptoms. Sci Rep 2022, 12(1):443\u0026ndash;443.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChhadva P, Lee T, Sarantopoulos CD, Hackam AS, McClellan AL, Felix ER, Levitt RC, Galor A: Human Tear Serotonin Levels Correlate with Symptoms and Signs of Dry Eye. Ophthalmology 2015, 122(8):1675\u0026ndash;1680.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMrugacz M, Ostrowska L, Bryl A, Szulc A, Zelazowska-Rutkowska B, Mrugacz G: Pro-inflammatory cytokines associated with clinical severity of dry eye disease of patients with depression. Advances in medical sciences 2017, 62(2):338\u0026ndash;344.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharif NA, Senchyna M: Serotonin receptor subtype mRNA expression in human ocular tissues, determined by RT-PCR. Molecular vision 2006, 12:1040\u0026ndash;1047.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOhayon MM, Schatzberg AF: Using chronic pain to predict depressive morbidity in the general population. Arch Gen Psychiatry 2003, 60(1):39\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCroft PR, Papageorgiou AC, Ferry S, Thomas E, Jayson MI, Silman AJ: Psychologic distress and low back pain. Evidence from a prospective study in the general population. Spine 1995, 20(24):2731\u0026ndash;2737.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarac H, Markeljevic J, Mokrovic G, Erdeljic V, Bozina N, Cicin-Sain L: Platelet serotonin in primary Sj\u0026ouml;gren's syndrome: level and relation with disease activity. Journal of neuroimmunology 2012, 251(1\u0026ndash;2):87\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSullivan DA: Tearful relationships? Sex, hormones, the lacrimal gland, and aqueous-deficient dry eye. Ocul Surf 2004, 2(2):92\u0026ndash;123.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez-Guasti A, Fiedler JL, Herrera L, Handa RJ: Sex, stress, and mood disorders: at the intersection of adrenal and gonadal hormones. \u003cem\u003eHormone and metabolic research\u0026thinsp;=\u0026thinsp;Hormon- und Stoffwechselforschung\u0026thinsp;=\u0026thinsp;Hormones et metabolisme\u003c/em\u003e 2012, 44(8):607\u0026ndash;618.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKiecolt-Glaser JK, Belury MA, Porter K, Beversdorf DQ, Lemeshow S, Glaser R: Depressive symptoms, omega-6:omega-3 fatty acids, and inflammation in older adults. Psychosomatic medicine 2007, 69(3):217\u0026ndash;224.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRashid S, Jin Y, Ecoiffier T, Barabino S, Schaumberg DA, Dana MR: Topical omega-3 and omega-6 fatty acids for treatment of dry eye. Arch Ophthalmol 2008, 126(2):219\u0026ndash;225.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu K, Guo Y, Ge QM, Su T, Shi WQ, Zhang LJ, Shu HY, Pan YC, Liang RB, Li QY \u003cem\u003eet al\u003c/em\u003e: Altered spontaneous activity in the frontal gyrus in dry eye: a resting-state functional MRI study. Sci Rep 2021, 11(1):12943.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWen W, Wu Y, Chen Y, Gong L, Li M, Chen X, Yan M, Xiao Z, Sun X: Dry eye disease in patients with depressive and anxiety disorders in Shanghai. Cornea 2012, 31(6):686\u0026ndash;692.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrianopoulou A, Zikou AK, Astrakas LG, Gerolymatou N, Xydis V, Voulgari P, Kiortsis DN, Argyropoulou MI: Functional connectivity and microstructural changes of the brain in primary Sj\u0026ouml;gren syndrome: the relationship with depression. Acta radiologica (Stockholm, Sweden: 1987) 2020, 61(12):1684\u0026ndash;1694.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSullivan BD, Crews LA, Messmer EM, Foulks GN, Nichols KK, Baenninger P, Geerling G, Figueiredo F, Lemp MA: Correlations between commonly used objective signs and symptoms for the diagnosis of dry eye disease: clinical implications. Acta Ophthalmologica 2014, 92(2):161\u0026ndash;166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVehof J, Sillevis Smitt-Kamminga N, Nibourg SA, Hammond CJ: Predictors of Discordance between Symptoms and Signs in Dry Eye Disease. Ophthalmology 2017, 124(3):280\u0026ndash;286.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4448844/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4448844/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to determine the relationship between dry eye-related symptoms and signs with anxiety and depression.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this observational study, we recruited 63 volunteers, including 51 patients with dry eye disease (DED) and 12 healthy volunteers. Infrared images of the meibomian gland and corneal nerve layer analysis of all patients were assessed. Additionally, the patients completed Hospital Anxiety and Depression Scale (HADS) questionnaire, Ocular Surface Disease Index (OSDI), and dry eye symptom questionnaire.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHADS-anxiety and HADS-depression scores in the DED group were significantly higher than those in the control group (\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.846, \u003cem\u003eP\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001, and \u003cem\u003et\u003c/em\u003e = 4.006, \u003cem\u003eP\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001, respectively). HADS-anxiety and HADS-depression was significantly correlated with DED symptoms (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). There was a significant positive correlation between the OSDI and HADS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There was a significant correlation between HADS-anxiety and mebomian gland area (\u003cem\u003er\u003c/em\u003e = -0.426, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and corneal nerve density (\u003cem\u003er\u003c/em\u003e = -0.345, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); HADS-depression was found to be correlated with mebomian gland area (\u003cem\u003er\u003c/em\u003e = -0.517, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and corneal nerve density (\u003cem\u003er\u003c/em\u003e = -0.242, \u003cem\u003eP\u003c/em\u003e = 0.016). The predictive equation for HADS-anxiety is as follows: HADS-anxiety = 0.09989*OSDI + -0.00013*CND + -22.54*MGA + 7.128 (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001). The predictive equation for HADS-depression is as follows: HADS-depression = 0.06743*OSDI + -18.01*MGA + 5.019 (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAnxiety and depression were significantly correlated with OSDI, CND and MGA in patients with DED. Furthermore, OSDI, CND and MGA have a relatively value for HADS-anxiety and HADS-depression.\u003c/p\u003e","manuscriptTitle":"The association of dry eye disease signs and symptoms with anxiety and depression: An observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 18:57:58","doi":"10.21203/rs.3.rs-4448844/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"640c7592-6001-4130-b34e-f07c79f27416","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-25T18:16:43+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-07 18:57:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4448844","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4448844","identity":"rs-4448844","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}