Optimizing Surgical Timing in Idiopathic Epiretinal Membrane: Identifying Cutoffs for Preoperative Visual Acuity and Metamorphopsia

Optimizing Surgical Timing in Idiopathic Epiretinal Membrane: Identifying Cutoffs for Preoperative Visual Acuity and Metamorphopsia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing Surgical Timing in Idiopathic Epiretinal Membrane: Identifying Cutoffs for Preoperative Visual Acuity and Metamorphopsia Qi Zhang, Jing Yang, Jinlian Zhan, Xia Huang, Qingxiu Wu, Lin Lu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7903871/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To identify prognostic factors for postoperative visual acuity (VA) and metamorphopsia outcomes in patients with idiopathic epiretinal membrane (iERM) and to establish clinically meaningful cutoff values to guide surgical timing. Methods: This retrospective study analyzed 72 eyes from 66 patients who underwent pars plana vitrectomy with membrane peeling. Preoperative and 12-month postoperative best-corrected VA (BCVA), metamorphopsia score (META-score), and optical coherence tomography (OCT) biomarkers were evaluated using multivariate regression and receiver operating characteristic (ROC) curve analyses. Results: At 12 months, both BCVA and META-score significantly improved (both P < 0.001). Multivariate analysis identified preoperative BCVA (β = 0.719, P < 0.001), presence of ectopic inner foveal layer (EIFL) (P = 0.046), iERM stage (P = 0.020), and ganglion cell-inner plexiform layer (GCL-IPL) thickness (P = 0.007) as independent predictors of postoperative BCVA. The preoperative META-score was the sole predictor for postoperative metamorphopsia (β = 0.480, P 0.5 LogMAR (AUC = 0.850) and a META-score > 2.74 (AUC = 0.990). Conclusion: Preoperative functional status (BCVA and META-score) are the primary determinants of surgical outcomes. Inner retinal biomarkers, particularly GCL-IPL thickness, provide independent predictive value. The established cutoffs (BCVA > 0.5 LogMAR; META-score > 2.74) offer objective, data-driven guidance for surgical decision-making and managing patient expectations. Idiopathic epiretinal membrane (iERM) Best-corrected visual acuity (BCVA) Metamorphopsia Optical coherence tomography (OCT) Prognostic factor Figures Figure 1 Figure 2 Introduction Idiopathic epiretinal membrane (iERM) is a common macular disorder characterized by the proliferation of fibrocellular tissue at the vitreoretinal interface[ 1 ]. The resulting traction leads to retinal thickening and distortion, causing significant visual disturbances, most notably a decline in visual acuity and the presence of metamorphopsia. Pars plana vitrectomy (PPV) with membrane peeling is the standard surgical treatment, often leading to favorable anatomical restoration[ 2 ]. However, functional outcomes are notoriously variable[ 3 ]. Despite a technically successful surgery, many patients experience incomplete recovery, with persistent metamorphopsia being a primary source of postoperative dissatisfaction even when visual acuity improves[ 2 ]. This clinical dilemma underscores the urgent need to better predict which patients will benefit most from surgery and to define the optimal timing for intervention. Over the years, numerous studies have identified potential prognostic factors. Worse preoperative best-corrected visual acuity (BCVA), older age, and longer symptom duration are established clinical predictors[ 4 ]. Concurrently, advances in optical coherence tomography (OCT) have revealed structural biomarkers associated with poorer outcomes, such as disruption of the ellipsoid zone (EZ), the presence of an ectopic inner foveal layer (EIFL), and disorganization of the retinal inner layers (DRIL)[ 5 ]. Despite this progress, a critical gap remains in translating these findings into clear clinical guidance. While many individual predictors have been identified, their relative importance and interplay—particularly the role of inner retinal integrity biomarkers like ganglion cell-inner plexiform layer (GCL-IPL) thickness[ 6 , 7 ]—require further clarification. Furthermore, few studies have simultaneously evaluated predictors for both visual acuity and metamorphopsia, which represent distinct and critical aspects of visual function. Most importantly, the lack of data-driven, quantitative thresholds means the decision on when to operate often relies on surgeon experience rather than on objective, evidence-based criteria. Therefore, this study aims to address these gaps by comprehensively analyzing a suite of functional and structural biomarkers. Our objectives were twofold: first, to identify the most significant preoperative predictors for both postoperative BCVA and metamorphopsia; and second, to establish clinically meaningful cutoff values that can help standardize surgical indications, improve patient counseling, and ultimately, optimize functional outcomes. Methods Study Design and Participants This retrospective cohort study was conducted at the Zhongshan Ophthalmic Center and included 72 eyes from 66 patients diagnosed with idiopathic epiretinal membrane (iERM) between May 2022 and January 2024. The study was approved by the Institutional Ethics Committee of Zhongshan Ophthalmic Center (2023KYPJ357) and adhered to the tenets of the Declaration of Helsinki. All participants provided written informed consent. Inclusion criteria were: (1) a diagnosis of iERM confirmed by a retinal specialist; (2) an axial length between 22.00 mm and 25.00 mm; and (3) a minimum postoperative follow-up of 12 months. Exclusion criteria included secondary ERM from other retinal pathologies, glaucoma, high myopia (spherical equivalent ≤ -6.00 D or axial length > 26.0 mm), retinal vascular diseases, a history of uveitis or prior vitreoretinal surgery, and uncontrolled systemic diseases. Surgical Procedure All surgical procedures were performed by a single experienced surgeon (L.L.). Each eye underwent a standard 25-gauge pars plana vitrectomy (PPV) with peeling of both the ERM and the internal limiting membrane (ILM), aided by indocyanine green staining. For patients over 55 with concurrent early-stage cataracts, combined phacoemulsification and intraocular lens implantation were performed. No intraoperative complications were recorded in any case. Clinical and Functional Assessment All patients underwent comprehensive ophthalmic examinations preoperatively and at the 12-month postoperative follow-up. Best-corrected visual acuity (BCVA) was measured using a Snellen chart and converted to the logarithm of the minimum angle of resolution (logMAR) for statistical analysis. Metamorphopsia was quantitatively assessed using the METAVISION system, a previously validated method developed by our group for the standardized measurement of visual distortion[ 8 ]. OCT/OCTA Analysis Image acquisition was performed using a swept-source OCT/OCTA system (VG200; SVision Imaging, Luoyang, China). High-definition macular cube scans and 6×6 mm OCTA scans centered on the fovea were obtained for each eye at both baseline and the 12-month follow-up. Image analysis was conducted by two independent, masked retinal specialists (Q.Z. and X.J.Z.), with any discrepancies resolved by a third senior specialist. Quantitative Structural Analysis: Using the instrument's built-in analysis software and calipers, the following parameters were measured from the macular cube scans: central foveal thickness (CFT), retinal nerve fiber layer (RNFL) thickness, ganglion cell-inner plexiform layer (GCL-IPL) thickness, inner nuclear layer (INL) thickness, and outer foveal layer (OFL) thickness. Quantitative Vascular Analysis: The foveal avascular zone area (FAZa) and perimeter (FAZp) were automatically measured within the superficial vascular plexus on the 6×6 mm OCTA scans using the device’s proprietary software. Qualitative Feature Assessment: The presence or absence of foveoschisis, ectopic inner foveal layer (EIFL), disorganization of the retinal inner layers (DRIL), and ellipsoid zone (EZ) disruption were qualitatively assessed. The iERM stage was classified according to the Govetto staging system[ 9 ]. Statistical Analysis All statistical analyses were performed using SPSS version 26.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were presented as mean ± standard deviation. Paired t-tests were used to compare pre- and postoperative functional and anatomical parameters. Pearson or Spearman correlation coefficients were used to assess correlations between variables. Multiple linear regression analyses were performed to identify independent preoperative predictors of postoperative outcomes and functional improvement. The predictive value of selected parameters was evaluated using the area under the receiver operating characteristic curve (AUC)[ 10 ]. The optimal cutoff value was determined using the maximum Youden index. A P-value < 0.05 was considered statistically significant. Results Baseline Characteristics The study included 72 eyes from 66 patients (21 male, 45 female) with a mean age of 63.77 ± 6.33 years. The mean axial length was 23.65 ± 0.23 mm. According to the Govetto staging system, the distribution was as follows: 6 eyes (8.3%) were stage 1, 18 (25.0%) were stage 2, 36 (50.0%) were stage 3, and 12 (16.7%) were stage 4. Detailed baseline demographics and clinical characteristics are summarized in Table 1 . Table 1 Baseline clinical characteristics of patients with iERM Age (years) 63.77 ± 6.33 Male/Female 21/45 BCVA (LogMAR) 0.59 ± 0.24 META-score 1.61 ± 1.30 Axial length (mm) 23.65 ± 0.23 Foveoschisis, n (%) 8 (11.1) Ectopic inner foveal layers (EIEL), n (%) 46 (63.8) Disorganization of the retinal inner layers (DRIL), n (%) 14 (19.4) Ellipsoid zone (EZ) disruption, n (%) 4 (5.5) iERM stage, n (%) Stage 1 6 (8.3) Stage 2 18 (25.0) Stage 3 36 (50.0) Stage 4 12 (16.7) BCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; iERM: idiopathic epiretinal membrane. Correlations Between Preoperative Anatomy and Baseline Visual Function We first sought to identify the structural determinants of baseline visual impairment. Preoperatively, ectopic inner foveal layer (EIFL) was present in 46 eyes (63.8%), disorganization of the retinal inner layers (DRIL) in 14 eyes (19.4%), foveoschisis in 8 eyes (11.1%), and ellipsoid zone (EZ) disruption in 4 eyes (5.5%). Multivariate regression analysis revealed that the presence of EIFL (β = 0.065, P = 0.027) and DRIL (β = 0.213, P = 0.011) were independently associated with worse preoperative BCVA. Furthermore, a smaller foveal avascular zone perimeter (FAZp) was significantly associated with a more severe preoperative metamorphopsia score (META-score) (β = − 0.886, P = 0.008) (Table 2 ). Table 2 The factors associated with preoperative visual function BCVA at baseline META-score at baseline Univariate Multivariate Univariate Multivariate r P β P r P β P BCVA at baseline 0.283 0.017 0.660 0.986 META-score at baseline 0.283 0.017 0.024 0.328 Foveoschisis 0.189 0.114 0.211 0.078 EIFL 0.411 <0.001 0.065 0.027 0.432 <0.001 0.159 0.443 DRIL 0.495 <0.001 0.213 0.011 0.308 0.009 -0.033 0.073 EZ disruption -0.115 0.339 -0.185 0.123 iERM stage 0.417 <0.001 -0.016 0.738 0.354 0.002 -0.460 0.063 CFT (µm) 0.390 <0.001 <0.001 0.967 0.409 <0.001 0.002 0.380 GCL-IPL thickness (µm) 0.340 0.004 <0.001 0.653 0.327 0.005 0.001 0.646 INL thickness (µm) 0.027 0.821 0.052 0.669 OFT (µm) 0.084 0.486 -0.019 0.874 FAZa (mm 2 ) -0.262 0.027 0.716 0.092 -0.754 <0.001 1.649 0.470 FAZp (mm) -0.271 0.022 -0.070 0.276 -0.761 <0.001 -0.886 0.008 BCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. P values were calculated using univariate and multivariate regression analysis. Surgical Outcomes: Functional and Anatomical Changes at 12 Months Following surgery, patients demonstrated significant functional and anatomical improvements at the 12-month follow-up (Fig. 1 ). Mean BCVA improved from 0.59 ± 0.24 to 0.34 ± 0.23 logMAR (P < 0.001), and the mean META-score decreased from 1.61 ± 1.30 to 0.50 ± 0.69 (P < 0.001). The CFT, GCL-IPL thickness, INL thickness and OFT thickness were 519.90 ± 96.42µm, 185.60 ± 85.51µm, 111.20 ± 35.54µm and 257.10 ± 40.09µm preoperatively, respectively. At 12 months postoperatively, these measurements were 403.60 ± 82.04µm, 100.50 ± 35.98µm, 62.93 ± 26.43µm and 240.20 ± 47.73µm (P < 0.001, P < 0.001, P < 0.001 and P = 0.029, respectively). No significant changes were observed in average FAZa (0.13 ± 0.18 vs 0.18 ± 0.29, P = 0.145) and FAZp (1.28 ± 1.30 vs 1.32 ± 1.77, P = 0.787) in the 6 × 6 mm² region. Preoperative Predictors of 12-Month Postoperative Outcomes To identify independent predictors of final 12-month outcomes, we performed multivariate regression analysis. Worse preoperative BCVA was the strongest predictor of worse postoperative BCVA (β = 0.719, P < 0.001). Additionally, the presence of EIFL (β = 0.116, P = 0.046), a lower iERM stage (β = -0.095, P = 0.020), and a thicker preoperative GCL-IPL (β = 0.0008, P = 0.007) were all independently associated with better postoperative BCVA. For metamorphopsia, a worse preoperative META-score was the sole significant predictor of a worse postoperative META-score (β = 0.480, P < 0.001) (Table 3 ). Table 3 Preoperative factors associated with final visual function outcomes BCVA at 12 months META-score at 12 months Univariate Multivariate Univariate Multivariate r P β P r P β P Sex 0.135 0.262 0.076 0.526 Age <0.001 0.998 0.039 0.744 BCVA at baseline 0.691 <0.001 0.719 <0.001 0.279 0.019 0.141 0.490 META-score at baseline 0.248 0.037 -0.027 0.193 0.931 <0.001 0.480 <0.001 Forvealschisis -0.031 0.799 0.155 0.196 EIFL 0.344 0.003 0.116 0.046 0.382 0.001 -0.161 0.142 DRIL 0.285 0.016 -0.101 0.166 0.248 0.037 -0.121 0.391 EZ disruption 0.084 0.485 -0.244 0.040 -0.227 0.278 iERM stage 0.248 0.037 -0.095 0.020 0.321 0.006 -0.025 0.775 CFT (µm) 0.200 0.095 0.322 0.006 0.0006 0.276 GCL-IPL thickness (µm) 0.325 0.006 0.0008 0.007 0.220 0.066 INL thickness (µm) 0.020 0.867 -0.023 0.849 OFT (µm) -0.007 0.955 -0.115 0.340 FAZa (mm 2 ) -0.259 0.029 -0.0005 0.999 -0.704 <0.001 0.758 0.292 FAZp (mm) -0.261 0.028 -0.029 0.598 -0.714 <0.001 -0.100 0.347 BCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. P values were calculated using univariate and multivariate regression analysis. We next analyzed predictors for the magnitude of functional improvement. A worse preoperative BCVA was significantly associated with a greater magnitude of BCVA improvement (β = 0.193, P = 0.025). Similarly, a worse preoperative META-score (β = 0.520, P < 0.001) and a thinner preoperative GCL-IPL thickness (β = − 0.002, P = 0.004) were associated with a greater degree of improvement in the META-score (Table 4 ). Table 4 Preoperative factors associated with visual function improvements at 12 months BCVA improvements at 12 months META-score improvements at 12 months Univariate Multivariate Univariate Multivariate r P β P r P β P Sex 0.025 0.838 0.017 0.887 Age 0.076 0.531 -0.009 0.939 BCVA at baseline 0.350 0.003 0.193 0.025 0.268 0.024 -0.135 0.480 META-score at baseline 0.041 0.737 0.961 <0.001 0.520 <0.001 Foveoschisis 0.336 0.004 0.148 0.064 0.211 0.077 EIEL 0.059 0.624 0.415 <0.001 0.148 0.149 DRIL 0.317 0.007 0.031 0.678 0.294 0.013 0.230 0.077 EZ disruption -0.196 0.102 -0.185 0.123 iERM stage 0.236 0.048 0.017 0.574 0.337 0.004 -0.005 0.947 CFT (µm) 0.269 0.023 -0.0001 0.670 0.382 0.001 0.001 0.100 GCL-IPL thickness (µm) 0.046 0.702 0.275 0.020 -0.002 0.004 INL thickness (µm) -0.041 0.737 0.090 0.458 OFT (µm) 0.092 0.445 0.012 0.921 FAZa (mm 2 ) -0.037 0.760 -0.693 <0.001 -0.381 0.555 FAZp (mm) 0.046 0.702 -0.702 <0.001 0.061 0.531 BCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. P values were calculated using univariate and multivariate regression analysis. Predictive Value and Optimal Cutoffs for Clinical Outcomes To translate these findings into a clinical tool, receiver operating characteristic (ROC) curve analysis was performed. For predicting a poor postoperative visual outcome (defined as 12-month BCVA > 0.5 LogMAR), a preoperative BCVA of 0.5 LogMAR was identified as the optimal cutoff, yielding an area under the curve (AUC) of 0.850 with a sensitivity of 1.000 and specificity of 0.735. For predicting a poor metamorphopsia outcome (defined as 12-month META-score > 1.0), a preoperative META-score of 2.74 was the optimal cutoff, demonstrating outstanding predictive ability (AUC = 0.990, sensitivity = 1.000, specificity = 0.962) (Fig. 2 ). Discussion In this study, we evaluated a comprehensive set of preoperative factors to predict functional outcomes following surgery for idiopathic epiretinal membrane (iERM). While our results confirm that preoperative BCVA and metamorphopsia score are powerful predictors of their respective postoperative outcomes[ 11 – 13 ], our analysis provides three key contributions: first, we highlight the independent prognostic significance of inner retinal integrity, specifically GCL-IPL thickness, for final visual acuity; second, we establish a link between perifoveal vascular architecture (FAZp) and baseline metamorphopsia; and most importantly, we translate these models into clinically actionable cutoff values to aid surgical timing. A novel finding of our study is the role of GCL-IPL thickness as an independent predictor for postoperative BCVA. While previous research has often focused on outer retinal damage, such as EZ disruption[ 11 , 13 ], our findings align with an emerging understanding that inner retinal structures are critically involved in iERM pathophysiology[ 11 , 14 – 16 ]. A thicker preoperative GCL-IPL may indicate better neuronal health and less chronic tractional injury, thereby signifying a greater potential for functional recovery. This finding, combined with the prognostic value of EIFL and DRIL[ 17 , 18 ], emphasizes that a comprehensive assessment of the entire retinal profile, not just the photoreceptor layer, is essential for accurate prognostication. Regarding metamorphopsia, our use of a standardized quantitative system (METAVISION)[ 8 ] allowed for a nuanced analysis. We found that the preoperative FAZ perimeter was negatively correlated with baseline metamorphopsia severity, suggesting that the mechanical distortion of the inner retinal layers is a key structural correlate of this symptom[ 7 , 19 ]. This aligns with other reports that metamorphopsia is primarily driven by inner retinal alterations, such as Müller cell deformation, rather than outer retinal pathology[ 20 – 22 ]. Critically, the strongest predictor of postoperative metamorphopsia was its preoperative severity[ 23 ]. This implies that while surgery can alleviate traction, it may not fully reverse the underlying neural or structural adaptations that cause persistent distortion, reinforcing the argument for earlier surgical intervention before severe and potentially irreversible changes occur. Perhaps the most clinically significant contribution of this study is the establishment of quantitative thresholds for predicting suboptimal outcomes. While current surgical indications consider visual acuity and metamorphopsia[ 5 ], standardized functional thresholds remain undefined and often rely on a surgeon’s subjective experience[ 24 ]. Our ROC analysis identified a preoperative BCVA of 0.5 LogMAR and a metamorphopsia score of 2.74 as critical cutoffs. These values move beyond general prognostic factors to provide tangible, evidence-based guidance. For a clinician, this means a patient with a BCVA worse than 0.5 LogMAR can be counseled that while improvement is likely, the chance of achieving excellent final vision is diminished. Similarly, a META-score exceeding 2.74 suggests a high risk of persistent, symptomatic postoperative metamorphopsia. This information is invaluable for managing patient expectations and collaboratively deciding on the optimal timing for surgery. This study has several limitations. Its retrospective nature is an inherent constraint. Furthermore, the small number of eyes (n = 4) with EZ disruption precluded a meaningful analysis of the outer retina's prognostic role. Lastly,while our metamorphopsia assessment was quantitative, other functional metrics like contrast sensitivity were not evaluated. Future prospective studies with larger cohorts are needed to validate these cutoff values and further explore the complex interplay between retinal structures in determining final visual outcomes. In conclusion, our study confirms that preoperative visual function is the cornerstone of prognostication in iERM surgery. We demonstrate, however, that inner retinal biomarkers, particularly GCL-IPL thickness, provide significant, independent predictive information. By establishing clear, data-driven cutoff values for both visual acuity (0.5 LogMAR) and metamorphopsia (2.74 META-score), this research offers clinicians practical tools to refine surgical indications, enhance patient counseling, and ultimately optimize the functional outcomes of iERM surgery. Declarations Financial Disclosure The sponsor or funding organization had no role in the design or conduct of this research. All authors have no financial or conflicting interests to disclose. Funding: This research was supported by the Innovative Clinical Technique of Guangzhou (2024P-GX02), the National Natural Science Foundation of China (82471085, 8250041798), Guangdong Basic Research Center of Excellence for Major Blinding Eye Diseases Prevention and Treatment (2024-PIZC-004). Author Contribution Qi Zhang, Jing Yang and Jinlian Zhan：Conceptualization, Methodology, Formal Analysis, Writing – Original Draft（ Equal contribution）.Xia Huang and Qingxiu Wu：Data Curation.Lin Lu: Supervision, Resources, Writing – Review & Editing.Xiujuan Zhao: Supervision, Project Administration, Writing – Review & Editing. References Bianchi L, Altera A, Barone V, Bonente D, Bacci T, De Benedetto E, Bini L, Tosi GM, Galvagni F, Bertelli E (2022) Untangling the Extracellular Matrix of Idiopathic Epiretinal Membrane: A Path Winding among Structure, Interactomics and Translational Medicine. Cells 11. 10.3390/cells11162531 Fung AT, Galvin J, Tran T (2021) Epiretinal membrane: A review. 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Acta Ophthalmol 93:203–212. 10.1111/aos.12537 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7903871","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":538355368,"identity":"4279b9d6-91a3-4edb-b28c-e74a905cb17e","order_by":0,"name":"Qi Zhang","email":"","orcid":"","institution":"Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Zhang","suffix":""},{"id":538355369,"identity":"049de851-275d-4d6d-8deb-a679c399b949","order_by":1,"name":"Jing Yang","email":"","orcid":"","institution":"Sun Yat-sen 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16:22:09","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111006,"visible":true,"origin":"","legend":"","description":"","filename":"cef15d5cd67d4bb99ce5ee2c87a0b09d1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7903871/v1/3b15bbead5ce6db6a395e1dd.xml"},{"id":95063735,"identity":"9e420aa5-64d2-47d3-85a5-5a33f8fd4125","added_by":"auto","created_at":"2025-11-04 01:18:50","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":122569,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7903871/v1/7427d6e2eb6669e5c0632bf3.html"},{"id":95063726,"identity":"c6a4890e-909a-47b4-b962-4bc7f8b5dc69","added_by":"auto","created_at":"2025-11-04 01:18:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":81342,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative Preoperative and 12-Month Postoperative OCT Images Across iERM Stages\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis panel displays OCT B-scans from patients representative of each iERM stage (Stage 1 to 4). The upper row shows the preoperative status, and the lower row shows the corresponding anatomical outcome 12 months after surgery. Pre- and postoperative best-corrected visual acuity (BCVA) and metamorphopsia (META) scores are listed for each case to illustrate the associated functional changes.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7903871/v1/548767785f4bc0b156bb8005.jpg"},{"id":95223104,"identity":"14b07340-fab0-411a-93c3-22a679e21871","added_by":"auto","created_at":"2025-11-05 16:21:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41282,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver Operating Characteristic (ROC) Curves for Predicting Suboptimal Postoperative Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) ROC curve analysis using preoperative BCVA to predict a poor visual acuity outcome (defined as 12-month BCVA \u0026gt; 0.5 LogMAR). The optimal cutoff was 0.5 LogMAR (AUC = 0.850). (B) ROC curve analysis using preoperative META-score to predict a poor metamorphopsia outcome (defined as 12-month META-score \u0026gt; 1.0). The optimal cutoff was 2.74 (AUC = 0.990).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7903871/v1/fde8b0a9c2dffb940c32a342.jpg"},{"id":98628531,"identity":"96393fbd-cf7c-4f76-98c0-12a41fc1c4bd","added_by":"auto","created_at":"2025-12-19 17:11:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1242998,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7903871/v1/31ee3960-6ce3-488f-88f0-6d3479bf7aca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing Surgical Timing in Idiopathic Epiretinal Membrane: Identifying Cutoffs for Preoperative Visual Acuity and Metamorphopsia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIdiopathic epiretinal membrane (iERM) is a common macular disorder characterized by the proliferation of fibrocellular tissue at the vitreoretinal interface[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The resulting traction leads to retinal thickening and distortion, causing significant visual disturbances, most notably a decline in visual acuity and the presence of metamorphopsia.\u003c/p\u003e\u003cp\u003ePars plana vitrectomy (PPV) with membrane peeling is the standard surgical treatment, often leading to favorable anatomical restoration[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, functional outcomes are notoriously variable[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite a technically successful surgery, many patients experience incomplete recovery, with persistent metamorphopsia being a primary source of postoperative dissatisfaction even when visual acuity improves[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This clinical dilemma underscores the urgent need to better predict which patients will benefit most from surgery and to define the optimal timing for intervention.\u003c/p\u003e\u003cp\u003eOver the years, numerous studies have identified potential prognostic factors. Worse preoperative best-corrected visual acuity (BCVA), older age, and longer symptom duration are established clinical predictors[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Concurrently, advances in optical coherence tomography (OCT) have revealed structural biomarkers associated with poorer outcomes, such as disruption of the ellipsoid zone (EZ), the presence of an ectopic inner foveal layer (EIFL), and disorganization of the retinal inner layers (DRIL)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite this progress, a critical gap remains in translating these findings into clear clinical guidance. While many individual predictors have been identified, their relative importance and interplay\u0026mdash;particularly the role of inner retinal integrity biomarkers like ganglion cell-inner plexiform layer (GCL-IPL) thickness[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u0026mdash;require further clarification. Furthermore, few studies have simultaneously evaluated predictors for both visual acuity and metamorphopsia, which represent distinct and critical aspects of visual function. Most importantly, the lack of data-driven, quantitative thresholds means the decision on when to operate often relies on surgeon experience rather than on objective, evidence-based criteria.\u003c/p\u003e\u003cp\u003eTherefore, this study aims to address these gaps by comprehensively analyzing a suite of functional and structural biomarkers. Our objectives were twofold: first, to identify the most significant preoperative predictors for both postoperative BCVA and metamorphopsia; and second, to establish clinically meaningful cutoff values that can help standardize surgical indications, improve patient counseling, and ultimately, optimize functional outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study was conducted at the Zhongshan Ophthalmic Center and included 72 eyes from 66 patients diagnosed with idiopathic epiretinal membrane (iERM) between May 2022 and January 2024. The study was approved by the Institutional Ethics Committee of Zhongshan Ophthalmic Center (2023KYPJ357) and adhered to the tenets of the Declaration of Helsinki. All participants provided written informed consent.\u003c/p\u003e\u003cp\u003eInclusion criteria were: (1) a diagnosis of iERM confirmed by a retinal specialist; (2) an axial length between 22.00 mm and 25.00 mm; and (3) a minimum postoperative follow-up of 12 months. Exclusion criteria included secondary ERM from other retinal pathologies, glaucoma, high myopia (spherical equivalent \u0026le; -6.00 D or axial length\u0026thinsp;\u0026gt;\u0026thinsp;26.0 mm), retinal vascular diseases, a history of uveitis or prior vitreoretinal surgery, and uncontrolled systemic diseases.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSurgical Procedure\u003c/h3\u003e\n\u003cp\u003eAll surgical procedures were performed by a single experienced surgeon (L.L.). Each eye underwent a standard 25-gauge pars plana vitrectomy (PPV) with peeling of both the ERM and the internal limiting membrane (ILM), aided by indocyanine green staining. For patients over 55 with concurrent early-stage cataracts, combined phacoemulsification and intraocular lens implantation were performed. No intraoperative complications were recorded in any case.\u003c/p\u003e\n\u003ch3\u003eClinical and Functional Assessment\u003c/h3\u003e\n\u003cp\u003eAll patients underwent comprehensive ophthalmic examinations preoperatively and at the 12-month postoperative follow-up. Best-corrected visual acuity (BCVA) was measured using a Snellen chart and converted to the logarithm of the minimum angle of resolution (logMAR) for statistical analysis. Metamorphopsia was quantitatively assessed using the METAVISION system, a previously validated method developed by our group for the standardized measurement of visual distortion[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOCT/OCTA Analysis\u003c/h3\u003e\n\u003cp\u003eImage acquisition was performed using a swept-source OCT/OCTA system (VG200; SVision Imaging, Luoyang, China). High-definition macular cube scans and 6\u0026times;6 mm OCTA scans centered on the fovea were obtained for each eye at both baseline and the 12-month follow-up.\u003c/p\u003e\u003cp\u003eImage analysis was conducted by two independent, masked retinal specialists (Q.Z. and X.J.Z.), with any discrepancies resolved by a third senior specialist.\u003c/p\u003e\u003cp\u003eQuantitative Structural Analysis: Using the instrument's built-in analysis software and calipers, the following parameters were measured from the macular cube scans: central foveal thickness (CFT), retinal nerve fiber layer (RNFL) thickness, ganglion cell-inner plexiform layer (GCL-IPL) thickness, inner nuclear layer (INL) thickness, and outer foveal layer (OFL) thickness.\u003c/p\u003e\u003cp\u003eQuantitative Vascular Analysis: The foveal avascular zone area (FAZa) and perimeter (FAZp) were automatically measured within the superficial vascular plexus on the 6\u0026times;6 mm OCTA scans using the device\u0026rsquo;s proprietary software.\u003c/p\u003e\u003cp\u003eQualitative Feature Assessment: The presence or absence of foveoschisis, ectopic inner foveal layer (EIFL), disorganization of the retinal inner layers (DRIL), and ellipsoid zone (EZ) disruption were qualitatively assessed. The iERM stage was classified according to the Govetto staging system[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were performed using SPSS version 26.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Paired t-tests were used to compare pre- and postoperative functional and anatomical parameters. Pearson or Spearman correlation coefficients were used to assess correlations between variables. Multiple linear regression analyses were performed to identify independent preoperative predictors of postoperative outcomes and functional improvement. The predictive value of selected parameters was evaluated using the area under the receiver operating characteristic curve (AUC)[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The optimal cutoff value was determined using the maximum Youden index. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eBaseline Characteristics\u003c/h2\u003e\u003cp\u003eThe study included 72 eyes from 66 patients (21 male, 45 female) with a mean age of 63.77\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33 years. The mean axial length was 23.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23 mm. According to the Govetto staging system, the distribution was as follows: 6 eyes (8.3%) were stage 1, 18 (25.0%) were stage 2, 36 (50.0%) were stage 3, and 12 (16.7%) were stage 4. Detailed baseline demographics and clinical characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" 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\u003eBaseline clinical characteristics of patients with iERM\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.77\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale/Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21/45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCVA (LogMAR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMETA-score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxial length (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFoveoschisis, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (11.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEctopic inner foveal layers (EIEL), n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (63.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisorganization of the retinal inner layers (DRIL), n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (19.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEllipsoid zone (EZ) disruption, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (5.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eiERM stage, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (8.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (25.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36 (50.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (16.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eBCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; iERM: idiopathic epiretinal membrane.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCorrelations Between Preoperative Anatomy and Baseline Visual Function\u003c/h3\u003e\n\u003cp\u003eWe first sought to identify the structural determinants of baseline visual impairment. Preoperatively, ectopic inner foveal layer (EIFL) was present in 46 eyes (63.8%), disorganization of the retinal inner layers (DRIL) in 14 eyes (19.4%), foveoschisis in 8 eyes (11.1%), and ellipsoid zone (EZ) disruption in 4 eyes (5.5%). Multivariate regression analysis revealed that the presence of EIFL (β\u0026thinsp;=\u0026thinsp;0.065, P\u0026thinsp;=\u0026thinsp;0.027) and DRIL (β\u0026thinsp;=\u0026thinsp;0.213, P\u0026thinsp;=\u0026thinsp;0.011) were independently associated with worse preoperative BCVA. Furthermore, a smaller foveal avascular zone perimeter (FAZp) was significantly associated with a more severe preoperative metamorphopsia score (META-score) (β = \u0026minus;\u0026thinsp;0.886, P\u0026thinsp;=\u0026thinsp;0.008) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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 factors associated with preoperative visual function\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eBCVA at baseline\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eMETA-score at baseline\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCVA at baseline\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.986\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMETA-score at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.328\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFoveoschisis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEZ disruption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eiERM stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.738\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.460\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.380\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCL-IPL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.646\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZa (mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.470\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZp (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.761\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eBCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. \u003cem\u003eP\u003c/em\u003e values were calculated using univariate and multivariate regression analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSurgical Outcomes: Functional and Anatomical Changes at 12 Months\u003c/h2\u003e\u003cp\u003eFollowing surgery, patients demonstrated significant functional and anatomical improvements at the 12-month follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mean BCVA improved from 0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24 to 0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23 logMAR (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the mean META-score decreased from 1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30 to 0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eThe CFT, GCL-IPL thickness, INL thickness and OFT thickness were 519.90\u0026thinsp;\u0026plusmn;\u0026thinsp;96.42\u0026micro;m, 185.60\u0026thinsp;\u0026plusmn;\u0026thinsp;85.51\u0026micro;m, 111.20\u0026thinsp;\u0026plusmn;\u0026thinsp;35.54\u0026micro;m and 257.10\u0026thinsp;\u0026plusmn;\u0026thinsp;40.09\u0026micro;m preoperatively, respectively. At 12 months postoperatively, these measurements were 403.60\u0026thinsp;\u0026plusmn;\u0026thinsp;82.04\u0026micro;m, 100.50\u0026thinsp;\u0026plusmn;\u0026thinsp;35.98\u0026micro;m, 62.93\u0026thinsp;\u0026plusmn;\u0026thinsp;26.43\u0026micro;m and 240.20\u0026thinsp;\u0026plusmn;\u0026thinsp;47.73\u0026micro;m (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and P\u0026thinsp;=\u0026thinsp;0.029, respectively). No significant changes were observed in average FAZa (0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 vs 0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29, P\u0026thinsp;=\u0026thinsp;0.145) and FAZp (1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30 vs 1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77, P\u0026thinsp;=\u0026thinsp;0.787) in the 6 \u0026times; 6 mm\u0026sup2; region.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePreoperative Predictors of 12-Month Postoperative Outcomes\u003c/h2\u003e\u003cp\u003eTo identify independent predictors of final 12-month outcomes, we performed multivariate regression analysis. Worse preoperative BCVA was the strongest predictor of worse postoperative BCVA (β\u0026thinsp;=\u0026thinsp;0.719, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, the presence of EIFL (β\u0026thinsp;=\u0026thinsp;0.116, P\u0026thinsp;=\u0026thinsp;0.046), a lower iERM stage (β = -0.095, P\u0026thinsp;=\u0026thinsp;0.020), and a thicker preoperative GCL-IPL (β\u0026thinsp;=\u0026thinsp;0.0008, P\u0026thinsp;=\u0026thinsp;0.007) were all independently associated with better postoperative BCVA. For metamorphopsia, a worse preoperative META-score was the sole significant predictor of a worse postoperative META-score (β\u0026thinsp;=\u0026thinsp;0.480, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" 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\u003ePreoperative factors associated with final visual function outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eBCVA at 12 months\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eMETA-score at 12 months\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCVA at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.490\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMETA-score at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForvealschisis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIFL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.391\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEZ disruption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eiERM stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.775\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.0006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCL-IPL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZa (mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.259\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.704\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.292\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZp (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eBCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. \u003cem\u003eP\u003c/em\u003e values were calculated using univariate and multivariate regression analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWe next analyzed predictors for the magnitude of functional improvement. A worse preoperative BCVA was significantly associated with a greater magnitude of BCVA improvement (β\u0026thinsp;=\u0026thinsp;0.193, P\u0026thinsp;=\u0026thinsp;0.025). Similarly, a worse preoperative META-score (β\u0026thinsp;=\u0026thinsp;0.520, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a thinner preoperative GCL-IPL thickness (β = \u0026minus;\u0026thinsp;0.002, P\u0026thinsp;=\u0026thinsp;0.004) were associated with a greater degree of improvement in the META-score (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\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\u003ePreoperative factors associated with visual function improvements at 12 months\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eBCVA improvements at 12 months\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eMETA-score improvements at 12 months\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eUnivariate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eMultivariate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.939\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBCVA at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.350\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.480\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMETA-score at baseline\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.737\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.520\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFoveoschisis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEIEL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.415\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.149\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRIL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEZ disruption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eiERM stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCL-IPL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINL thickness (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.737\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOFT (\u0026micro;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZa (mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.555\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFAZp (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eBCVA: best-corrected visual acuity; META-score: the metamorphopsia score using METAVISION system; EIFL: ectopic inner foveal layers; DRIL: disorganization of the retinal inner layers; EZ: ellipsoid zone; iERM: idiopathic epiretinal membrane; CFT: central foveal thickness; GCL-IPL: ganglion cell-inner plexiform layer; INL: inner nuclear layer; OFT: outer foveal thickness; FAZa: foveal avascular zone area; FAZp: foveal avascular zone perimeter. \u003cem\u003eP\u003c/em\u003e values were calculated using univariate and multivariate regression analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePredictive Value and Optimal Cutoffs for Clinical Outcomes\u003c/h2\u003e\u003cp\u003eTo translate these findings into a clinical tool, receiver operating characteristic (ROC) curve analysis was performed. For predicting a poor postoperative visual outcome (defined as 12-month BCVA\u0026thinsp;\u0026gt;\u0026thinsp;0.5 LogMAR), a preoperative BCVA of 0.5 LogMAR was identified as the optimal cutoff, yielding an area under the curve (AUC) of 0.850 with a sensitivity of 1.000 and specificity of 0.735. For predicting a poor metamorphopsia outcome (defined as 12-month META-score\u0026thinsp;\u0026gt;\u0026thinsp;1.0), a preoperative META-score of 2.74 was the optimal cutoff, demonstrating outstanding predictive ability (AUC\u0026thinsp;=\u0026thinsp;0.990, sensitivity\u0026thinsp;=\u0026thinsp;1.000, specificity\u0026thinsp;=\u0026thinsp;0.962) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we evaluated a comprehensive set of preoperative factors to predict functional outcomes following surgery for idiopathic epiretinal membrane (iERM). While our results confirm that preoperative BCVA and metamorphopsia score are powerful predictors of their respective postoperative outcomes[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], our analysis provides three key contributions: first, we highlight the independent prognostic significance of inner retinal integrity, specifically GCL-IPL thickness, for final visual acuity; second, we establish a link between perifoveal vascular architecture (FAZp) and baseline metamorphopsia; and most importantly, we translate these models into clinically actionable cutoff values to aid surgical timing.\u003c/p\u003e\u003cp\u003eA novel finding of our study is the role of GCL-IPL thickness as an independent predictor for postoperative BCVA. While previous research has often focused on outer retinal damage, such as EZ disruption[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], our findings align with an emerging understanding that inner retinal structures are critically involved in iERM pathophysiology[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A thicker preoperative GCL-IPL may indicate better neuronal health and less chronic tractional injury, thereby signifying a greater potential for functional recovery. This finding, combined with the prognostic value of EIFL and DRIL[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], emphasizes that a comprehensive assessment of the entire retinal profile, not just the photoreceptor layer, is essential for accurate prognostication.\u003c/p\u003e\u003cp\u003eRegarding metamorphopsia, our use of a standardized quantitative system (METAVISION)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] allowed for a nuanced analysis. We found that the preoperative FAZ perimeter was negatively correlated with baseline metamorphopsia severity, suggesting that the mechanical distortion of the inner retinal layers is a key structural correlate of this symptom[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This aligns with other reports that metamorphopsia is primarily driven by inner retinal alterations, such as M\u0026uuml;ller cell deformation, rather than outer retinal pathology[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Critically, the strongest predictor of postoperative metamorphopsia was its preoperative severity[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This implies that while surgery can alleviate traction, it may not fully reverse the underlying neural or structural adaptations that cause persistent distortion, reinforcing the argument for earlier surgical intervention before severe and potentially irreversible changes occur.\u003c/p\u003e\u003cp\u003ePerhaps the most clinically significant contribution of this study is the establishment of quantitative thresholds for predicting suboptimal outcomes. While current surgical indications consider visual acuity and metamorphopsia[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], standardized functional thresholds remain undefined and often rely on a surgeon\u0026rsquo;s subjective experience[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our ROC analysis identified a preoperative BCVA of 0.5 LogMAR and a metamorphopsia score of 2.74 as critical cutoffs. These values move beyond general prognostic factors to provide tangible, evidence-based guidance. For a clinician, this means a patient with a BCVA worse than 0.5 LogMAR can be counseled that while improvement is likely, the chance of achieving excellent final vision is diminished. Similarly, a META-score exceeding 2.74 suggests a high risk of persistent, symptomatic postoperative metamorphopsia. This information is invaluable for managing patient expectations and collaboratively deciding on the optimal timing for surgery.\u003c/p\u003e\u003cp\u003eThis study has several limitations. Its retrospective nature is an inherent constraint. Furthermore, the small number of eyes (n\u0026thinsp;=\u0026thinsp;4) with EZ disruption precluded a meaningful analysis of the outer retina's prognostic role. Lastly,while our metamorphopsia assessment was quantitative, other functional metrics like contrast sensitivity were not evaluated. Future prospective studies with larger cohorts are needed to validate these cutoff values and further explore the complex interplay between retinal structures in determining final visual outcomes.\u003c/p\u003e\u003cp\u003eIn conclusion, our study confirms that preoperative visual function is the cornerstone of prognostication in iERM surgery. We demonstrate, however, that inner retinal biomarkers, particularly GCL-IPL thickness, provide significant, independent predictive information. By establishing clear, data-driven cutoff values for both visual acuity (0.5 LogMAR) and metamorphopsia (2.74 META-score), this research offers clinicians practical tools to refine surgical indications, enhance patient counseling, and ultimately optimize the functional outcomes of iERM surgery.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eFinancial Disclosure\u003c/h2\u003e\u003cp\u003eThe sponsor or funding organization had no role in the design or conduct of this research. All authors have no financial or conflicting interests to disclose.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis research was supported by the Innovative Clinical Technique of Guangzhou (2024P-GX02), the National Natural Science Foundation of China (82471085, 8250041798), Guangdong Basic Research Center of Excellence for Major Blinding Eye Diseases Prevention and Treatment (2024-PIZC-004).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eQi Zhang, Jing Yang and Jinlian Zhan：Conceptualization, Methodology, Formal Analysis, Writing \u0026ndash; Original Draft（ Equal contribution）.Xia Huang and Qingxiu Wu：Data Curation.Lin Lu: Supervision, Resources, Writing \u0026ndash; Review \u0026amp; Editing.Xiujuan Zhao: Supervision, Project Administration, Writing \u0026ndash; Review \u0026amp; Editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBianchi L, Altera A, Barone V, Bonente D, Bacci T, De Benedetto E, Bini L, Tosi GM, Galvagni F, Bertelli E (2022) Untangling the Extracellular Matrix of Idiopathic Epiretinal Membrane: A Path Winding among Structure, Interactomics and Translational Medicine. 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Acta Ophthalmol 93:203\u0026ndash;212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/aos.12537\u003c/span\u003e\u003cspan address=\"10.1111/aos.12537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\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":"Idiopathic epiretinal membrane (iERM), Best-corrected visual acuity (BCVA), Metamorphopsia, Optical coherence tomography (OCT), Prognostic factor","lastPublishedDoi":"10.21203/rs.3.rs-7903871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7903871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003eTo identify prognostic factors for postoperative visual acuity (VA) and metamorphopsia outcomes in patients with idiopathic epiretinal membrane (iERM) and to establish clinically meaningful cutoff values to guide surgical timing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThis retrospective study analyzed 72 eyes from 66 patients who underwent pars plana vitrectomy with membrane peeling. Preoperative and 12-month postoperative best-corrected VA (BCVA), metamorphopsia score (META-score), and optical coherence tomography (OCT) biomarkers were evaluated using multivariate regression and receiver operating characteristic (ROC) curve analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eAt 12 months, both BCVA and META-score significantly improved (both P \u0026lt; 0.001). Multivariate analysis identified preoperative BCVA (β = 0.719, P \u0026lt; 0.001), presence of ectopic inner foveal layer (EIFL) (P = 0.046), iERM stage (P = 0.020), and ganglion cell-inner plexiform layer (GCL-IPL) thickness (P = 0.007) as independent predictors of postoperative BCVA. The preoperative META-score was the sole predictor for postoperative metamorphopsia (β = 0.480, P \u0026lt; 0.001). ROC analysis identified optimal cutoffs for predicting poor outcomes: a preoperative \u003cstrong\u003eBCVA \u0026gt; 0.5 LogMAR\u003c/strong\u003e (AUC = 0.850) and a \u003cstrong\u003eMETA-score \u0026gt; 2.74\u003c/strong\u003e (AUC = 0.990).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003ePreoperative functional status (BCVA and META-score) are the primary determinants of surgical outcomes. Inner retinal biomarkers, particularly GCL-IPL thickness, provide independent predictive value. The established cutoffs (BCVA \u0026gt; 0.5 LogMAR; META-score \u0026gt; 2.74) offer objective, data-driven guidance for surgical decision-making and managing patient expectations.\u003c/p\u003e","manuscriptTitle":"Optimizing Surgical Timing in Idiopathic Epiretinal Membrane: Identifying Cutoffs for Preoperative Visual Acuity and Metamorphopsia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-04 01:18:45","doi":"10.21203/rs.3.rs-7903871/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":"f2ee8bc3-72cd-4d34-b4c1-84da404c80a2","owner":[],"postedDate":"November 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-19T13:23:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-04 01:18:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7903871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7903871","identity":"rs-7903871","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}