Surgical prognosis in epiretinal membrane: A 5-year longitudinal study of OCT biomarkers and visual acuity at a high-complexity referral center

Surgical prognosis in epiretinal membrane: A 5-year longitudinal study of OCT biomarkers and visual acuity at a high-complexity referral center | 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 Surgical prognosis in epiretinal membrane: A 5-year longitudinal study of OCT biomarkers and visual acuity at a high-complexity referral center Piero Barrera Arshavin, Álvaro Bofill Ramírez, Antonia Bayo Burgos, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8371594/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: To determine the functional and anatomical outcomes at 12 months after pars plana vitrectomy (PPV) for epiretinal membrane (ERM) and the independent prognostic value of preoperative biomarkers in optical coherence tomography (OCT). Methods: Five-year analytical study of 340 eyes with ERM in stages (Govetto G2–4). Best-corrected visual acuity (BCVA) logMAR and OCT were evaluated at baseline, 1, 3, 6, and 12 months. The primary objective was to determine the change in BCVA at 12 months (ΔlogMAR 12 m – baseline). Univariate tests, ANCOVA, longitudinal mixed linear models, and logistic regression were applied for gain ≥0.2 logMAR. The models were adjusted for baseline VA, age, sex, aetiology, surgical technique, and analysis of biomarkers in OCT. Results: Baseline VA was 0.54±0.44 logMAR; distribution according to G2 (n=166), G3 (n=146), G4 (n=28). VA improved significantly at 12 months (Wilcoxon p<0.001), equivalent to 11–12 ETDRS letters. Secondary ERMs showed greater unadjusted gain than idiopathic ones, but aetiology was not an independent predictor after adjustment. The surgical technique was not independently associated with VA at 12 months (β=+0.031 logMAR; 95% CI; p=0.408) or with responder status (OR 1.18; 95% CI; p=0.625). By severity, advanced stages had worse baseline VA and greater absolute gains (Kruskal–Wallis H=7.61; p=0.0223), although with lower final VA compared to lesser stages. Baseline VA was the dominant predictor in all models (β=−0.766; 95% CI; p<0.001). Among preoperative biomarkers, COST line disruption independently increased the probability of response (OR=2.08; 95% CI; p=0.013). DRIL, EZ disruption, and central bouquet alterations did not reach significance after adjustment. Mixed models confirmed early improvement, maintained up to 12 months. Kaplan–Meier showed faster time to response in advanced stages. Conclusions: PPV by ERM achieves significant improvement at 12 months. Baseline VA is the main determinant of prognosis. According to Govetto's classification, the greatest gain occurs in advanced stages, but with lower final VA. The COST line emerges as the only preoperative biomarker with independent prognostic value for achieving ≥0.2 logMAR; the others provide limited utility when baseline VA is considered. Trial registration: Not applicable. Epiretinal Membrane Vitrectomy Optical Coherence Tomography Biomarkers Visual Acuity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction ERM is a common macular pathology characterised by avascular fibrocellular proliferation on the surface of the internal limiting membrane (ILM) 1 . In most cases, it may be idiopathic or secondary to various pathologies, such as diabetic retinopathy (DR), retinal vascular occlusions (RVO), uveitis, trauma, retinal detachment (RD) or following cataract surgery 2 , 3 . Idiopathic ERM usually occur in older adults and are a major cause of visual impairment in this age group 4 , with posterior vitreous detachment (PVD) playing a major pathogenic role, as reported in most series 5 . Epidemiological studies have reported an overall prevalence of ERM of 6–11%, increasing with age to 15% in people over 70 years of age 4 , 5 , 6 . Clinically, patients report decreased VA, metamorphopsia, aniseikonia and, less frequently, monocular diplopia or binocular interference, with an impact on visual function and quality of life 7 , 8 . OCT has optimised diagnosis, improving the stratification and follow-up of ERM 9 . Structurally, it is visualised as a hyperreflective band over the ILM, with associated signs of traction such as radial folds, increased central macular thickness (CMT), cystoid macular oedema and alterations in the outer layers, disruption of the ellipsoid zone 10 , 11 , 12 . In 2017, Govetto et al. 13 proposed an OCT classification into four stages (G1 to G4) based on the loss of foveal depression and the presence of the ectopic internal foveal layer (EIFL), a structure that reflects a reorganization and establishment of a bridge of the inner layers over the fovea 14 . This correlates with clinical and anatomical findings, which in different series describe worse VA as the stage increases 15 , 16 . As a result, various structural biomarkers with prognostic value in ERM surgery have been proposed, such as CMT, ellipsoid zone (EZ) integrity, central bouquet traction of the outer retina (OR) manifested by the most characteristic sign of cotton ball, and the presence of disorganisation of the inner retinal layers (DRIL) 17 , 18 . Although none of these parameters has been shown to be a universal biomarker, evaluation in conjunction with classification systems such as that proposed by Govetto et al. has demonstrated greater accuracy in estimating postoperative functional potential 13 , 19 , 20 . In this context, most publications come from European, North American, and Asian cohorts, with a scarcity of data on Latin American populations, where demographic characteristics could influence clinical presentation and surgical outcomes. Therefore, it is necessary to develop local studies that evaluate postoperative anatomical and functional outcomes in our setting, determining the prognostic value of structural biomarkers, applying state-of-the-art surgical techniques. Materials and Methods Study design This was a retrospective, analytical, longitudinal cohort study at the Fundación Oftalmológica Los Andes (FOLA) in Santiago, Chile, which included patients who underwent surgery between 1 January 2020 and 30 April 2025. Follow-up was conducted at baseline and then 1, 3, 6 and 12 months after surgery. The design and writing of the study manuscript followed the STROBE guidelines 21 . Objective Determine, in a cohort of eyes with MER operated on over a 5-year period at a high-complexity centre, the magnitude of change in AVMC and the behaviour of structural biomarkers through OCT according to Govetto's classification 13 primarily the presence of EIFL, EZ integrity, DRIL, COST line, and central bouquet findings from preoperatively to 12 months postoperatively. As secondary objectives, the functional and anatomical response was compared between idiopathic and secondary MER, and between surgical techniques, PPV alone vs. PPV combined with phacoemulsification (PPV/PHACO), estimating the preoperative prognostic value of these biomarkers on VA using adjusted multivariable models. Inclusion and exclusion criteria are detailed in Table 1 and analysed using a selection diagram; Fig. 1 . Table 1 Inclusion and exclusion criteria Category Criterion Inclusion Phakic or pseudophakic eyes with idiopathic or secondary ERM (diabetic, post-cataract surgery, retinal vein occlusion, uveitis, trauma, previous retinal detachment). PPV surgery (23G/25G) with ERM peeling ± ILM peeling; subgroups according to PPV or PPV/PHACO technique and lens status. Good quality preoperative and postoperative Spectralis macular OCT (signal ≥ 7/10 or Q ≥ 25 dB), without critical artefacts. Follow-up ≥ 12 months with clinical evaluations and OCT at approximately 1, 3, 6 and 12 months. BCVA measured with ETDRS and converted to logMAR, recorded preoperatively and at 1, 3, 6 and 12 months. ERM in G2–4 at the time of surgery. For secondary ERM: controlled underlying disease Exclusion Active primary maculopathies unrelated to ERM that confound the outcome (active AMD, dystrophies). Untreated AMD or active proliferative retinopathy; extensive ischaemic RVO or with active neovascularisation; active uveitis. Progressive optic neuropathy (advanced glaucoma). VR surgery other than ERM in the previous 3 months. Poor-quality OCT, media opacities that prevent quality imaging. Loss of follow-up for less than 6 months or incomplete or missing critical data. ERM stage 1 at the time of surgery. ERM = epiretinal membrane; PPV = pars plana vitrectomy; ILM = internal limiting membrane; VR: vitreoretinal; OCT = optical coherence tomography; BCVA = best-corrected visual acuity; ETDRS = Early Treatment Diabetic Retinopathy Study; logMAR = logarithm of the minimum angle of resolution; AMD = age-related macular degeneration; RVO = retinal vein occlusion. OCT = optical coherence tomography. Functional assessment BCVA was measured with ETDRS letters under standardised conditions and at a fixed distance of 6 metres. The results were converted to the logMAR scale for statistical analysis. In cases of very low vision, conversions to logMAR were applied: finger counting (FC) = 2.0; hand motion (HM) = 2.3; light perception (LP) = 2.7; no light perception (NLP) = 3.0. Follow-up included preoperative assessment and check-ups at 1, 3, 6, and 12 months. The probability of being a "respond" was considered when the gain was greater than or equal to 0.2 logMAR (ΔlogMAR 12 m – baseline), which is related to a change of 2 lines of letters according to the Snellen chart and has been used as a threshold value in the literature to define significant functional changes in VA. OCT image acquisition The images were obtained with SD-OCT Spectralis (Heidelberg Engineering, Germany), following a standardised and reproducible protocol between controls. Macular cubes with fields of 20°× 20° (6×6 mm) or 30°× 25° (8.8×7.3 mm) fields, with 49–97 B-scans. Automatic segmentation (ILM–BM) was used, and each volume was manually inspected to detect foveal segmentation errors. Qualitative analysis and operational definition of biomarkers The analysis was performed by two ophthalmologists specialising in the retina, who were responsible for classifying the severity of ERM and identifying OCT biomarkers, tabulating data without access to the patient's clinical information. EIFL was defined using Govetto's 2017 classification 13 , recorded as a category from the apparent internal limit of the EIFL to the interface with the outer layers in the centre of the fovea. G2 is defined as the loss of normal foveal depression, with some thickening of the outer nuclear layer (ONL), but without the formation of a continuous band of inner layer tissue in the fovea, and no EIFL. About G3, it is defined by the absence of foveal depression and the presence of a well-defined EIFL, with a continuous hypo/hyperreflective band corresponding to the inner nuclear layer (INL) plus the inner plexiform layer (IPL) crossing the foveal centre, although with the inner retinal layers still well defined, measurable between 50 and 250 µm centrally. Finally, G4 corresponds to advanced and thick ERM; EIFL is prominently present in the fovea, but with loss of normal laminar architecture, with internal layers appearing markedly disorganised. DRIL was defined as loss of distinguishable boundaries between the retinal nerve fibre layer (RNFL), the ganglion cell layer complex and the inner plexiform layer (GCIPL), the INL and the outer plexiform layer (OPL) in a 1 mm segment centred on the fovea; It was recorded according to severity as mild, moderate or severe, identified on the horizontal axis of the central B-scan. EZ integrity was classified as intact or disrupted around the foveal centre, as a dichotomous variable for statistical analysis purposes. COST (cone outer segment tips) line was recorded as present, defined as a continuous line, or absent/discontinuous on the foveal axis. Central bouquet (external foveal complex) was recorded as the presence of the cotton ball sign, as a rounded hyperreflective lesion in the outer foveal layers, foveolar detachment and acquired vitelliform lesion, in the presence of subfoveal hyperreflective material with underlying shadow, also being evaluated dichotomously as present or absent. Of the quantitative parameters, the CMT is obtained in the central 1 mm ETDRS circle measured in microns (µm) at the foveal level. Statistical analysis Continuous variables were described as mean with standard deviation (SD) or median (interquartile range, IQR), as appropriate, after verifying the normality of distributions using the Shapiro–Wilk test and the homogeneity of variances using Levene's test. Categorical variables, such as sex, laterality, ERM aetiology, Govetto stage, presence of EIFL, DRIL, EZ, COST, and central bouquet, were summarised as absolute frequencies and percentages. For univariate comparisons of continuous variables between more than two groups, one-way ANOVA with Bonferroni-adjusted post hoc tests was used; when the assumptions of normality and/or variances were not met, the Kruskal–Wallis test with Dunn's multiple comparisons and Benjamini–Hochberg multiplicity correction for multiple comparisons was applied. The comparison of proportions was performed using Pearson's χ², employing Yates' correction or Fisher's exact test when the expected values were small. The analysis of the dependent variable in our study was defined as the change in VA represented as Δ logMAR arithmetic difference between postoperative VA minus preoperative VA at 12 months; this was analysed with a paired Student's t-test or, in the case of non-normality, with the Wilcoxon test for related samples. The difference in means was determined with 95% confidence intervals (CI) and Cohen's dz effect size. Longitudinal follow-up of VA at 1, 3, 6, and 12 months. Fixed effects included time, aetiology, surgical technique, and biomarkers, in addition to the interaction terms time by group. All models were adjusted for clinical covariates and baseline BCVA in logMAR; the influence of the surgeon was evaluated in sensitivity analyses as a fixed factor or additional random term. Differences between groups in functional response were estimated using an ANCOVA approach, analysing the postoperative logMAR value at 12 months as the dependent variable, with groups separated by aetiology or surgical technique as the factor and adjusted for baseline BCVA and preoperative biomarkers; this is equivalent to contrast of change under assumptions, reducing bias due to regression to the mean. The prognostic value of biomarkers was examined using multiple linear regression with Δ logMAR as the dependent variable and, exploratively, with logistic regression for the probability of being a "respond" with 95% CIs. The discrimination of EIFL, COST, EZ, and DRIL was evaluated with ROC curves, obtaining the area under the curve (AUC). For ordinal variables such as EIFL stage reversal, a proportional odds ratio (OR) model was used. Within the time-to-event analysis, a time-to-response variable was constructed at 1, 3, 6, and 12 months, corresponding to the first follow-up at which response was achieved; non-responders were excluded at their last available follow-up. Overall Kaplan–Meier (KM) curves were estimated and stratified by Govetto stage, aetiology, and surgical technique, with log-rank comparison. Cox proportional hazards models were adjusted exploratorily; the proportional hazards assumption was verified with Schoenfeld residuals when appropriate. A two-sided p-value < 0.05 was considered significant. All analyses were performed using jamovi v2.6 22 and R v4.4 23 . A priori sample size calculation This was based on the primary variable. The paired t-test formula was used to detect a conservative mean improvement of 0.10 logMAR, with a standard deviation of the difference of 0.25, bilateral significance level α = 0.05, and power 1 − β = 0.80. Results Demographics The study cohort had a mean age of 73.4 ± 9.4 years with a median of 74 (IQR 69–80; range 17–93) and a proportion of women of 58.5% (199/340). Baseline BCVA was 0.54 ± 0.44 logMAR, median 0.45 (IQR 0.30–0.60; range − 0.16 to 3.00). Laterality was quantitatively similar, with 50.3% (171/340) in the right eye and 49.7% (169/340) in the left eye. The aetiology corresponded mostly to idiopathic ERM in 82.9% (282/340) versus secondary in 17.1% (58/340). According to Govetto's preoperative classification, G2 and G3 predominated with 48.8% and 42.9% respectively, and to a lesser extent G4 with 8.2%. The distribution of baseline OCT biomarkers and summarised categorical variables can be seen in Table 2 . Table 2 Baseline categorical characteristics of the cohort (n = 340 eyes) Variable Category n % Sex F 199 58.5 M 141 41.5 Laterality OD 171 50.3 OS 169 49.7 ERM aetiology Idiopathic 282 82.9 Secondary 58 17.1 Govetto 2 166 48.8 3 146 42.9 4 28 8.2 Surgical technique PPV + PHACO 256 75.3 PPV 84 24.7 EIFL Present 155 45.6 Absent 185 54.4 DRIL No 209 61.5 Mild (Mi) 54 15.9 Moderate (Mo) 52 15.3 Severe (S) 25 7.4 EZ Disruption 198 58.2 Integrity 142 41.8 COST Disruption 204 60.0 Full 136 40 Central bouquet NO 163 48.1 CBS 130 38.4 VIT 47 13.9 ERM: epiretinal membrane; OD: right eye; OS: left eye; PPV: pars plana vitrectomy; PHACO: phacoemulsification; DRIL: disorganisation of the retinal inner layers (none or absence, mild, moderate, severe); EZ: ellipsoid zone; COST: cone outer segment tips; Central bouquet: NO (no alterations), CBS: cotton ball sign, VIT: acquired vitelliform. Overall functional analysis The primary objective of the study compared the change in BCVA, represented as ΔlogMAR = 12m − baseline, showing an overall improvement with a mean of − 0.29 ± 0.42 and a median of − 0.23 (IQR − 0.42 to − 0.08; range − 2.37 to 1.08). Given that the distribution of differences did not meet Shapiro–Wilk normality p < 0.001, the Wilcoxon rank test was used, which confirmed a statistically significant improvement (W = 6422; p < 0.001). The effect size estimated as a biserial correlation of ranks was r = 0.78, consistent with a high clinical impact. In practical terms, the median of − 0.23 logMAR approximates a gain of approximately 11–12 ETDRS letters at 12 months. Figure 2 shows the behaviour of overall BCVA, and according to covariates, through longitudinal follow-up. When breaking down the visual results by aetiology, idiopathic ERMs (n = 282), representing 82.94%, when analysing BCVA, show a median of − 0.22 (IQR − 0.39 to − 0.08; mean − 0.24), while in secondary ERM (n = 58), representing 17.06%, it was − 0.27 (IQR − 0.82 to − 0.13; mean − 0.49). The Mann–Whitney comparison was statistically significant (U = 6694.5; p = 0.0296); Fig. 3 . However, when adjusting for covariates in an ANCOVA model with ΔlogMAR at 12 months as the dependent variable and including baseline BCVA in logMAR, age, sex, aetiology and surgical technique, it is noteworthy that baseline BCVA was the most decisive predictor (β = −0.766; 95% CI − 0.834 to − 0.697; p < 0.001). Analysis according to surgical technique Of the 340 eyes, 256 (75.3%) underwent PPV + PHACO surgery and 84 (24.7%) underwent PPV surgery. Baseline BCVA was better in the PPV + PHACO group (mean 0.503 ± 0.360 logMAR; median 0.42) than in the PPV alone group (mean 0.672 ± 0.600; median 0.45); Fig. 4 . Functional improvement at 12 months was − 0.266 ± 0.362 in PPV + PHACO and − 0.348 ± 0.558 in PPV alone; the difference between techniques in ΔlogMAR was not significant (Mann–Whitney W = 10,244.5; p = 0.517). The proportion of responders was 53.9% in VPP + PHACO and 59.5% in PPV, with no significant differences in the comparison of proportions. In the ANCOVA with 12-month BCVA as the adjusted dependent variable, the coefficient for PPV versus PPV + PHACO was β = +0.031 logMAR (95% CI − 0.043 to 0.106; p = 0.408). In the logistic regression for "respond" the adjusted OR for PPV versus PPV + PHACO was 1.18 (95% CI 0.59–2.36; p = 0.625). In both models, baseline VA remained the dominant predictor of functional outcome (p < 0.001). Analysis according to Govetto stage 13 According to the OCT classification, the medians for “ΔlogMAR 12 m – baseline” were, in G2: −0.2 (IQR − 0.380 to 0.000; n = 166), G3: −0.225 (− 0.408 to − 0.100; n = 146) and G4: −0.370 (− 0.628 to − 0.210; n = 28). This overall difference between stages was significant; Kruskal–Wallis H = 7.61; p = 0.0223; ε² = 0.0168 and, after correction for multiplicity according to the Benjamini–Hochberg method, a greater improvement was found in G4 compared to G2 and G3, with a p FDR = 0.0265 and p FDR = 0.0338, respectively, with no differences between G2 and 3, p FDR = 0.290; Fig. 5 . These findings are statistically significant and consistent with a response rate associated with structural severity: the higher the G2 to 4, the greater the postoperative visual gain. However, when comparing the final BCVA, the more advanced the disease, the lower the BCVA. Therefore, the BCVA at each Govetto stage was consistent with the functional change, as detailed quantitatively, where in G2, the baseline BCVA was 0.519 ± 0.458, BCVA at 12 months was 0.256 ± 0.280, Δ mean − 0.263 (SD 0.465). Meanwhile, in G3, the baseline BCVA was 0.553 ± 0.423, at 12 months 0.268 ± 0.278, mean Δ − 0.285 (SD 0.369). Finally, in G4, baseline BCVA was 0.933 ± 0.514, at 12 months 0.345 ± 0.342, mean Δ − 0.588 (SD 0.467); Table 3 . Table 3 Results by Govetto stage, preoperatively. Variable G2 (n = 166) G3 (n = 146) G4 (n = 28) p BCVA, mean ± SD — Baseline 0.519 ± 0.458 0.553 ± 0.423 0.933 ± 0.514 4.3×10⁻⁵¹ BCVA, mean ± SD — 12 months 0.256 ± 0.280 0.268 ± 0.278 0.345 ± 0.342 0.311¹ ΔlogMAR (12 m – baseline), mean ± SD −0.263 ± 0.465 −0.285 ± 0.369 −0.588 ± 0.467 0.0223² ¹ One-way ANOVA between stages; calculation based on means, SD and n per group. ² Kruskal–Wallis test between stages. Analysis according to biomarkers About structural biomarkers, the measured basal CMT showed a mean of 457.5 ± 81.4 µm (median 449.5 µm; IQR 399.5–504). The association of basal CMT with structural severity was highly significant. Increasing medians were observed between the different stages, 423 µm in G2, 482 µm in G3 and 514 µm in G4, with overall heterogeneity by Kruskal–Wallis (H = 41.80; p = 4.4×10⁻⁹) and a positive Spearman correlation of moderate magnitude between Govetto stage and CMT (p = 0.346; p = 5.14×10⁻¹¹), which robustly confirms that macular thickening increases as the stage progresses. However, it did not correlate directly with final BCVA in the multivariate analysis (p = − 0.09; p = 0.10), Fig. 6 . In the cohort, preoperative EIFL was present in 45.6% of eyes (155/340). This biomarker was associated with greater structural severity at baseline OCT and showed a relationship according to Govetto stage, concentrating in G3-4 (p = 0.568; p = 2.0×10⁻³⁰) and with central macular thickness (p = 0.272; p = 3.6×10⁻⁷). In the 12-month analysis, resolved EIFL was associated with better BCVA in eyes that had this biomarker preoperatively and achieved longitudinal follow-up (n = 77; 69 with resolution and 8 with persistence). In the ANCOVA with 12-month BCVA as the multivariate-adjusted dependent variable, the effect of resolved EIFL was favourable but not significant (β= −0.161 logMAR; 95% CI − 0.720 to 0.397; p = 0.571). Consistently, in the binomial model for the probability of being a "respond" there was a trend toward a greater respond with resolved EIFL (OR 5.22; 95% CI 0.24–115.6), but it did not reach statistical significance (p = 0.296); Table 4 . Table 4 Prognostic value of biomarkers (preoperative) on response at 12 months Preoperative biomarker Adjusted association with "respond"¹ Univariate discrimination (ROC)² COST OR = 2.08 (95% CI 1.17–3.70); p = 0.013 AUC = 0.57 EIFL NS* AUC = 0.53 DRIL NS* AUC = 0.53 EZ NS* AUC = 0.52 Central bouquet NS* AUC = 0.56 Basal BCVA Dominant predictor in all models; p 1 indicates a higher probability of being a responder. 2 Univariate ROC curves by preoperative biomarker. AUC interpreted as isolated discrimination of the marker. *NS: not significant after adjustment. At 12 months, baseline disruption of the COST line in OCT behaved as an independent predictor of visual response, if it regained its continuity postoperatively. In the binary model for "respond" starting with a disrupted COST line was associated with approximately a 2-fold increased likelihood of responding (OR = 2.08; 95% CI 1.17–3.70; p = 0.013), after adjusting for baseline VA, clinical and anatomical covariates. Consistently, in the models with continuous VA, eyes that showed COST resolution achieved better VA at 12 months than those without recovery, with the effect remaining after multivariable adjustment. EZ, DRIL, and central bouquet, when analysing pre- versus post-operative and prognostic value of "respond". In the unadjusted analysis, postoperative restoration of the three biomarkers was associated with better VA at 12 months, while their persistence was associated with worse VA. However, when adjusted for baseline VA and clinical covariates, none showed an independent association in either the ANCOVA of VA at 12 months as dependent or in the binary regression for "respond" with p ≥ 0.05 in all cases. Their individual discriminatory capacity was limited, EZ with AUC: 0.515, DRIL with AUC: 0.525, and central bouquet with AUC: 0.56; Fig. 7 . Survival analysis In the mixed linear models, a significant time effect was observed on BCVA, with early improvement that was maintained up to 12 months (p < 0.001). Baseline BCVA was 0.54 ± 0.44 logMAR and at 12 months approximately 0.26 logMAR, consistent with the averages by technique; PPV + PHACO 0.237 ± 0.242; PPV 0.324 ± 0.377. The overall change at 12 months was − 0.29 ± 0.42 logMAR (median − 0.23; Wilcoxon p < 0.001). In the entire cohort, the median time to response was close to 3 months. By severity according to Govetto stage, the medians were 3 months (G2, n = 166), 3 months (G3, n = 146) and 1 month (G4, n = 28). At 12 months, the probability of not responding was 30.1% (G2), 24.7% (G3) and 10.7% (G4), equivalent to cumulative response rates of 69.9%, 75.3% and 89.3%, respectively. In the univariate Cox model, compared with G2, G4 had a higher response risk rate (HR = 1.67; p = 0.021), with no differences for G3 (HR = 1.15; p = 0.302). By aetiology, the medians were 3 versus 3 months and 12-month survival was 27.7% for the idiopathic group versus 19.0% for the secondary group, with no differences in the hazard ratio (HR = 1.13; p = 0.466). By technique, the medians were 3 months for the PPV + PHACO technique and 3 (3–6) months for PPV; 12-month survival rates were 27.3% vs 22.6%, respectively; HR = 0.97; p = 0.858. The overall proportional hazards test was significant with p = 0.012; in the comparison by technique; consequently, these HRs should be interpreted with caution. (Fig. 8 , 9 , 10 ) Finally, in the sensitivity analysis, the inclusion of the surgeon as a fixed factor or as a random term did not modify the results, whether considered as univariate or multivariate. Discussion Our demographic results are consistent with series published in the literature, which highlight advanced age, with a mean of approximately 73 years, and a slight predominance of females. Meta-analyses indicate that advanced age and female sex are significant risk factors for developing ERM 1 . In the quantitative analysis, the data from our study variable confirm that PPV with ERM peeling produces a significant functional improvement, with a mean BCVA improved from 0.54 to 0.26 logMAR (median − 0.23), equivalent to a gain of around 11–12 ETDRS letters, corresponding to a gain of about 2 lines, with this improvement maintained for up to 12 months (Wilcoxon p < 0.001). This finding is consistent with previously published studies reporting clinically relevant improvements in VA after ERM surgery. De Clerck et al. reported an improvement in BCVA from 0.5 to 0.8 measured using Snellen charts up to one year after surgery in the idiopathic ERM group 24 , and Kunavisarut et al. reported an increase in ETDRS of 51 to 65 letters at 6 months post-surgery 25 . In addition, other series detail in their results an improvement of around 70–77% of patients gaining at least two lines after membrane peeling 26 and Wong et al. reported a mean improvement of 0.31 logMAR (approximately 3 lines) with 83% of eyes improving ≥ 2 lines 27 . The effect size was large in our study (r = 0.78), reinforcing the clinical impact of surgery. In the adjusted multivariate analysis, baseline BCVA stands out as the dominant predictor of postoperative gain. We found that eyes with worse baseline or initial BCVA gained more, as reported by other authors 28 , 29 , who observed that 69.4% of patients improved their BCVA in the long term, with patients with worse initial BCVA gaining more; Wong et al. reported a direct correlation between pre- and post-operative BCVA, with quantitatively worse initial BCVA improving more after peeling 27 , 30 . About aetiology, we observed that secondary ERMs had worse preoperative vision and the greatest absolute gain on the logMAR scale, with a median of − 0.27 versus − 0.22 in idiopathic cases (p = 0.03). This coincides with studies by Kang et al., who found that test with secondary ERM had worse baseline BCVA but achieved greater postoperative visual improvement, albeit with a higher recurrence rate (20% versus 4.9%) 31 . Similarly, Norton et al. found that eyes with secondary ERM had lower preoperative VA and improved significantly after surgery but had a higher incidence of postoperative cystoid macular oedema 32 . However, when we adjusted for covariates, including baseline VA, age, sex, and surgical technique, the aetiology lost independent significance (p = 0.171). The adjusted means of final gain were − 0.290 for idiopathic ERM and − 0.235 for secondary ERM, suggesting that the apparent advantage of secondary ERM is largely explained by their worse initial VA. This finding emphasises, as already noted, that initial visual acuity is key to the expected improvement. In terms of surgical technique, we found no significant differences in visual outcome between PPV + PHACO and PPV alone, with ΔlogMAR = − 0.27 vs − 0.35 (p = 0.517). Recent studies report similar findings. Dermer et al. compared combined versus deferred surgery in ERM and found no significant differences in VA gain or anatomical parameters between the two groups 33 . Our data are consistent with this conclusion and suggest that the combined approach does not alter adjusted visual improvement. Furthermore, the proportion of "respond" was comparable, with 54% for the combined surgery group versus 60% for PPV alone. Other groups have observed that combined surgery with an experienced anterior and posterior segment surgeon produces predictable refractive and visual outcomes like sequential surgeries 32 , 33 . In the ANCOVA analysis and even in multivariable logistic regression, the surgical technique variable showed no independent effect on final VA (p > 0.4) or on the probability of responding (OR = 1.18; p = 0.625), reflecting that, after controlling for it, the attributable difference is marginal. The Govetto classification, according to G2 to 4, was associated with the postoperative outcome. As other authors have shown, eyes in more advanced stages have worse preoperative VA but greater absolute gain. In our cohort, the medians obtained in ΔlogMAR were − 0.20, − 0.225, and − 0.370 in G2, 3, and 4, respectively. The Kruskal-Wallis test confirmed overall differences (p = 0.022) and adjusted post-hoc analysis indicated that G4 had superior gain compared to G2 and 3 (pFDR = 0.03). This pattern coincides with the observation by De Clerck et al. 24 in Retina 2025, where only eyes in G4 maintained significantly worse VA in the long term, demonstrating that structural severity predicts the outcome. Similarly, Govetto et al. 13 reported that, in OCT classification, BCVA progressively decreases from stage 1 to stage 4, emphasising that greater structural damage implies a worse prognosis. In summary, our findings suggest that, although advanced ERMs gain more letters, given their lower functional ceiling, their final BCVA remains lower. This highlights the importance of early detection; operating before very advanced stages could optimise long-term functional outcome. Regarding preoperative OCT biomarkers, several have been linked to visual prognosis as the main functional variable. In our cohort, the presence of EIFL was observed in 45.6% of eyes and was correlated with more severe stages (p = 0.57). In anatomical-functional terms, the biomarkers evaluated reflect the degree, type of traction and foveal microstructural damage induced by ERM. EIFL represents the ectopia of internal layers, mainly GCL and IPL, towards the centre of the fovea, secondary to tangential traction and the glial response of Müller cells; its presence is associated with loss of foveal depression, reduction of the foveal avascular zone (FAZ) and poorer visual function due to misalignment of the central photoreceptors. The literature establishes that EIFL is a marker of advanced damage. Govetto et al. 13 identified EIFL in approximately 33% of their cases and associated it with significant visual loss, incorporating it into their classification scheme. In line with this, Govetto found in 2019 that eyes with preoperative EIFL had worse pre- and postoperative VA (p < 0.001) 15 . In our analysis, the resolution of postoperative EIFL tended to be associated with better functional outcome (OR = 5.2 for responding ≥ 2 lines), but without reaching significance (p = 0.296), possibly due to the limited number of cases with this biomarker at the end of follow-up. The integrity of the outer layers is key to sharp vision. The COST line reflects the coupling of the cone tips with the RPE; its basal interruption usually indicates damage or misalignment of the outer segments and predicts more limited visual recovery if it persists. Classic and subsequent studies have shown that COST integrity correlates with postoperative VA in ERM and other maculopathies, while its prolonged loss is associated with worse outcomes 34 . Notably, we identified COST line disruption as the only preoperative biomarker with an independent effect on functional outcome. Shimozono et al. demonstrated that COST line integrity is a useful prognostic factor after MER surgery 33 . Our findings reinforce this concept, as recovery from COST disruption at diagnosis almost doubled the odds of responding adequately after surgery (OR = 2.08; p = 0.013). The EZ represents the integrity of the inner segments or mitochondrial bands of the cones; its postoperative restoration suggests metabolic and phototransduction recovery, but in our series, it had no independent effect after controlling for baseline VA and covariates. The literature is heterogeneous, as some studies find that interrupted EZ and DRIL are associated with worse VA and may have value in multivariate models, while others show modest discriminatory power in the short term. As for the inner layers, DRIL summarises the disorganisation of the boundaries between INL, IPL and GCL; its persistence translates into synaptic alteration and abnormal intraretinal conduction. Although in our study DRIL was not an independent predictor, specific ERM series have described associations with VA that may depend on stage, time of evolution and duration of EZ collapse. Similarly, alterations in the central foveal bouquet, which shows traction on the Müller fibre bundle and foveal cones, whose signs of central traction have been linked to poorer foveal morphology and metamorphopsia symptoms; their normalisation after peeling may accompany recovery, but their isolated prognostic power is limited 35 . In fact, MacCumber et al. 35 reported that CMT and DRIL did not correlate significantly with visual gain, although the DRIL sample size was small, which is equivalent to that obtained in our experience. After surgery, none of the postoperative structural biomarkers at one year showed a significant association with final adjusted VA. The Kaplan–Meier curves show that the functional response already described as ≥ 0.2 logMAR occurs early, with a median of close to 3 months. Therefore, the expected improvement in the first 12 weeks and the surgical opportunity should consider that, although advanced stages respond earlier, they reach lower functional ceilings, favouring intervention before progression. For this reason, our repeated measures models confirmed that most visual recovery occurs early. The study by Creuzot-Garcher et al. observed that VA improvement and foveal thickness reduction occur mainly in the first 6 months, with little additional gain beyond that point 36 . In fact, Romano et al. reported that the greatest increase in VA occurred 1 month post-surgery (p < 0.001) 37 , and in our cohort we see a similar pattern of stabilisation after 1 to 3 months. This suggests that initial follow-up should be close and that VA remains at a plateau until one year. This study provides a large cohort of patients in real-world practice, with serial follow-up and standardised anatomical characterisation. However, the retrospective design limits generalisation and may leave room for confusion regarding indications; the dichotomous definition of "respond" simplifies the continuous response; interobserver variability of biomarkers was not quantified. Nevertheless, the findings offer solid and clinically useful evidence. Conclusions Finally, our results support international findings, where ERM surgery with PPV significantly improves BCVA, especially in patients with poorer initial acuity. The difference between idiopathic and secondary ERM disappears when adjusted for baseline AV, as does the choice of simultaneous versus deferred PHACO. The structural stage according to Govetto predicts the degree of gain, although not the final absolute VA value. OCT biomarkers such as the COST line and the presence of EIFL are consistent with a poorer visual prognosis. Overall, these results reinforce current guidelines and help to put our findings into clinical context in comparison with the international literature. Abbreviations AMD Age-related macular degeneration BCVA Best-corrected visual acuity BM Bruch’s membrane CBS Cotton ball sign CI Confidence interval CMT Central macular thickness COST Cone outer segment tips DRIL Disorganisation of the retinal inner layers EZ Ellipsoid zone ETDRS Early Treatment Diabetic Retinopathy Study FC Finger counting GCIPL Ganglion cell layer–inner plexiform layer complex HM Hand motion ILM Internal limiting membrane INL Inner nuclear layer IPL Inner plexiform layer IQR Interquartile range logMAR Logarithm of the minimum angle of resolution LP Light perception NLP No light perception OCT Optical coherence tomography OD Right eye ONL Outer nuclear layer OPL Outer plexiform layer OR Odds ratio OS Left eye PHACO Phacoemulsification PPV Pars plana vitrectomy RNFL Retinal nerve fibre layer RVO Retinal vein occlusion SD Standard deviation SD-OCT Spectral-domain optical coherence tomography STROBE Strengthening the Reporting of Observational Studies in Epidemiology VR Vitreoretinal VIT Acquired vitelliform (lesion) Declarations Ethics approval and consent to participate . This study was conducted in accordance with the tenets of the Declaration of Helsinki 22 . The study protocol was reviewed and approved by the ethics committee of FOLA, Santiago, Chile. Given the retrospective, observational design and the use of de-identified clinical data, the requirement for written informed consent to participate was waived by the ethics committee. Competing interests . The authors declare that they have no competing interests. Funding. This research received no external funding. Author Contribution PBA conceived and designed the study. PBA, ABR, ABB, EUI and JCO collected the data. PBA performed the statistical analysis and interpreted the results. JIVD, MJRF, LFL, JMLA, SZS, JOR and EPA contributed to patient management/surgical care and provided critical clinical input. PBA drafted the manuscript. ABR, ABB, EUI, JCO, JIVD, MJRF, LFL, JMLA, SZS, JOR and EPA critically revised the manuscript for important intellectual content. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 14 Feb, 2026 Reviews received at journal 13 Feb, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviews received at journal 11 Jan, 2026 Reviewers agreed at journal 27 Dec, 2025 Reviewers invited by journal 22 Dec, 2025 Editor assigned by journal 21 Dec, 2025 Submission checks completed at journal 18 Dec, 2025 First submitted to journal 15 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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01:04:59","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156936,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/524b38ee0609ed3b97b7a84d.html"},{"id":99192702,"identity":"c1c15020-1bbb-4847-a01c-0d363073171e","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21818,"visible":true,"origin":"","legend":"\u003cp\u003eSTROBE flow chart of cohort selection\u003c/p\u003e\n\u003cp\u003eOCT = optical coherence tomography.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/678b7b7fa74efca5d1746804.jpg"},{"id":99192699,"identity":"f8ea46ea-3a63-4406-8223-2d986a243b39","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":108672,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A, B, C). \u003c/strong\u003eEvolution of MCVA after PPV by ERM.\u003c/p\u003e\n\u003cp\u003eEvolution of BCVA in logMAR. \u003cstrong\u003e(A) \u003c/strong\u003eOverall curve at 12 months. \u003cstrong\u003e(B) \u003c/strong\u003eCurves stratified by \u003cstrong\u003eGovetto\u003c/strong\u003estage and \u003cstrong\u003esurgical technique\u003c/strong\u003e. \u003cstrong\u003e(C) \u003c/strong\u003eCurves according to \u003cstrong\u003eaetiology \u003c/strong\u003eand technique.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/fa1714960aa600e6de98ff0f.jpg"},{"id":99192697,"identity":"3efa7559-87cf-459e-8c31-8f06087ec2ee","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10754,"visible":true,"origin":"","legend":"\u003cp\u003eChange in BCVA at 12 months according to ERM aetiology\u003c/p\u003e\n\u003cp\u003eBoxplots of AVMC “ΔlogMAR = 12 m – baseline” by aetiology. The box shows IQR, the centre line the median, the whiskers 1.5×IQR; the dots are individual eyes and the black square the mean. Negative values indicate visual improvement. Mann–Whitney U=6694.5; p=0.0296); after ANCOVA adjustment (F=1.88; p=0.171).\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/5ab5bec80fde8290529396ab.jpg"},{"id":99319264,"identity":"d5f5ad96-d86a-4755-ab55-84982e1f7fa1","added_by":"auto","created_at":"2025-12-31 16:36:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":11129,"visible":true,"origin":"","legend":"\u003cp\u003eChange in BCVA at 12 months according to surgical technique\u003c/p\u003e\n\u003cp\u003eBoxplots of BCVA “ΔlogMAR = 12 m – baseline” according to surgical technique. The box shows the IQR, the centre line the median, the whiskers 1.5×IQR; the dots are individual eyes, and the black square is the mean. Mann–Whitney W=10,244.5; p=0.517). In adjusted models (β=+0.031 logMAR; 95% CI −0.043 to 0.106; p=0.408), and probability of being a responder (OR=1.18; 95% CI 0.59–2.36; p=0.625).\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/40585a14c48ca9579faceb19.jpg"},{"id":99192700,"identity":"9a4f761d-dded-4c30-a52f-05d65d883ad0","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":11908,"visible":true,"origin":"","legend":"\u003cp\u003eVisual change at 12 months according to Govetto stage\u003c/p\u003e\n\u003cp\u003eBoxplots of BCVA “ΔlogMAR = 12 m – baseline” stratified by \u003cstrong\u003eGovetto: 2 (n=166)\u003c/strong\u003e,\u003cstrong\u003e 3 (n=146) \u003c/strong\u003eand\u003cstrong\u003e 4 (n=28).\u003c/strong\u003e The centre line indicates the \u003cstrong\u003emedian\u003c/strong\u003e, the box the \u003cstrong\u003eIQR, \u003c/strong\u003ethe whiskers\u003cstrong\u003e 1.5×IQR\u003c/strong\u003e; \u003cstrong\u003eblack square \u003c/strong\u003ethe \u003cstrong\u003emean\u003c/strong\u003e; grey dots = \u003cstrong\u003eindividual observations\u003c/strong\u003e. Negative values represent\u003cstrong\u003e greater visual gain\u003c/strong\u003e. Comparisons between groups were evaluated using \u003cstrong\u003eKruskal–Wallis (\u003c/strong\u003eH = 7.61; p = 0.0223; ε² = 0.0168)\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/ac4e582be1946e4bfe2b6edc.jpg"},{"id":99192705,"identity":"b1bbf9f7-61ea-4f4a-84af-a3e65871d486","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12416,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBaseline CMT according to Govetto stage.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBoxplots represent the median and interquartile range (IQR); whiskers, 1.5×IQR; black square, mean; and dots, individual eyes. A progressive increase in CMT is observed with severity: medians 423 µm (E2), 482 µm (E3), and 514 µm (E4). Overall differences by Kruskal–Wallis: H = 41.80, p = 4.4×10⁻⁹.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/bb8c8e4d155a312de2f2b177.jpg"},{"id":99317755,"identity":"19633abf-d111-4d7d-a920-92976b382ce5","added_by":"auto","created_at":"2025-12-31 16:30:41","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":16768,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of preoperative biomarkers to predict “respond”.\u003c/p\u003e\n\u003cp\u003eUnivariate ROC curves for the probability of being a \"responder\". AUC (p-value): \u003cstrong\u003eCOST\u003c/strong\u003e 0.568 (p=0.005); \u003cstrong\u003eEIFL\u003c/strong\u003e 0.526 (p=0.347); \u003cstrong\u003eDRIL\u003c/strong\u003e 0.525 (p=0.308); \u003cstrong\u003eEZ\u003c/strong\u003e 0.515 (p=0.310); \u003cstrong\u003eCENTRAL BOUQUET\u003c/strong\u003e 0.515 (p=0.539). Only COST showed a modestly superior discriminatory capacity compared to random.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/2b01a1a7e3bd2da5ce45032c.jpg"},{"id":99192710,"identity":"e0a93cc7-6e25-4891-9481-6bd5573ec768","added_by":"auto","created_at":"2025-12-30 01:04:58","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":22603,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier of \"time to response\" according to ERM aetiology\u003c/p\u003e\n\u003cp\u003eCumulative incidence of response (ΔAV ≥0.2 logMAR) according to aetiology. There were no significant differences between idiopathic (n=282) and secondary (n=58) according to the log-rank test (p=0.37). At 12 months, the cumulative incidence of response was 72% in idiopathic and 81% in secondary. The Cox model confirmed the absence of differences (HR=1.13; 95% CI; p=0.466).\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/2a45d915ee9d6ea3795bce42.jpg"},{"id":99316865,"identity":"ef3ed914-5f8f-44c0-8b96-9255540a0409","added_by":"auto","created_at":"2025-12-31 16:29:22","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":26083,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves of \"time to response\" according to Govetto stage\u003c/p\u003e\n\u003cp\u003eCumulative response rate (ΔAV ≥0.2 logMAR) according to Govetto stage. There were no significant overall differences by log-rank test (p=0.059). At 12 months, the cumulative response rate was 69.9% in G2 (n=166), 75.3% in G3 (n=146) and 89.3% in G4 (n=28). In the univariate Cox model, G4 showed a higher instantaneous response rate vs G2 (HR=1.67; p=0.021), with no differences for G3 (HR=1.15; p=0.302).\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/92ac955d0947b841aad03aeb.jpg"},{"id":99192721,"identity":"9548454a-c0fe-4110-83fd-c1c002107110","added_by":"auto","created_at":"2025-12-30 01:04:59","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":23953,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves of time to response according to surgical technique\u003c/p\u003e\n\u003cp\u003eCumulative incidence of response (Δ AV ≥0.2 logMAR) according to surgical technique. No differences were observed between PPV+PHACO (n=256) and PPV (n=84) by log-rank test (p=0.86). At 12 months, the cumulative incidence of response was 73% and 77%, respectively. The Cox model confirmed the absence of differences (HR=0.97; 95% CI; p=0.858).\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/9a26b5de5c0f3974cbd73284.jpg"},{"id":99323725,"identity":"61f09a85-7d12-4495-ae1a-cae024756e8e","added_by":"auto","created_at":"2025-12-31 16:46:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1429828,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8371594/v1/febfc823-d5fa-4672-a641-2f6c76f3ec3c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Surgical prognosis in epiretinal membrane: A 5-year longitudinal study of OCT biomarkers and visual acuity at a high-complexity referral center","fulltext":[{"header":"Introduction","content":"\u003cp\u003eERM is a common macular pathology characterised by avascular fibrocellular proliferation on the surface of the internal limiting membrane (ILM)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In most cases, it may be idiopathic or secondary to various pathologies, such as diabetic retinopathy (DR), retinal vascular occlusions (RVO), uveitis, trauma, retinal detachment (RD) or following cataract surgery\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIdiopathic ERM usually occur in older adults and are a major cause of visual impairment in this age group\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, with posterior vitreous detachment (PVD) playing a major pathogenic role, as reported in most series\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEpidemiological studies have reported an overall prevalence of ERM of 6\u0026ndash;11%, increasing with age to 15% in people over 70 years of age\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Clinically, patients report decreased VA, metamorphopsia, aniseikonia and, less frequently, monocular diplopia or binocular interference, with an impact on visual function and quality of life\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOCT has optimised diagnosis, improving the stratification and follow-up of ERM\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Structurally, it is visualised as a hyperreflective band over the ILM, with associated signs of traction such as radial folds, increased central macular thickness (CMT), cystoid macular oedema and alterations in the outer layers, disruption of the ellipsoid zone \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In 2017, Govetto et al.\u003csup\u003e13\u003c/sup\u003e proposed an OCT classification into four stages (G1 to G4) based on the loss of foveal depression and the presence of the ectopic internal foveal layer (EIFL), a structure that reflects a reorganization and establishment of a bridge of the inner layers over the fovea\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. This correlates with clinical and anatomical findings, which in different series describe worse VA as the stage increases\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs a result, various structural biomarkers with prognostic value in ERM surgery have been proposed, such as CMT, ellipsoid zone (EZ) integrity, central bouquet traction of the outer retina (OR) manifested by the most characteristic sign of cotton ball, and the presence of disorganisation of the inner retinal layers (DRIL)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough none of these parameters has been shown to be a universal biomarker, evaluation in conjunction with classification systems such as that proposed by Govetto et al. has demonstrated greater accuracy in estimating postoperative functional potential\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this context, most publications come from European, North American, and Asian cohorts, with a scarcity of data on Latin American populations, where demographic characteristics could influence clinical presentation and surgical outcomes.\u003c/p\u003e \u003cp\u003eTherefore, it is necessary to develop local studies that evaluate postoperative anatomical and functional outcomes in our setting, determining the prognostic value of structural biomarkers, applying state-of-the-art surgical techniques.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a retrospective, analytical, longitudinal cohort study at the Fundaci\u0026oacute;n Oftalmol\u0026oacute;gica Los Andes (FOLA) in Santiago, Chile, which included patients who underwent surgery between 1 January 2020 and 30 April 2025. Follow-up was conducted at baseline and then 1, 3, 6 and 12 months after surgery.\u003c/p\u003e \u003cp\u003eThe design and writing of the study manuscript followed the STROBE guidelines\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eObjective\u003c/h3\u003e\n\u003cp\u003eDetermine, in a cohort of eyes with MER operated on over a 5-year period at a high-complexity centre, the magnitude of change in AVMC and the behaviour of structural biomarkers through OCT according to Govetto's classification\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e primarily the presence of EIFL, EZ integrity, DRIL, COST line, and central bouquet findings from preoperatively to 12 months postoperatively. As secondary objectives, the functional and anatomical response was compared between idiopathic and secondary MER, and between surgical techniques, PPV alone vs. PPV combined with phacoemulsification (PPV/PHACO), estimating the preoperative prognostic value of these biomarkers on VA using adjusted multivariable models.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInclusion and exclusion criteria\u003c/b\u003e are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and analysed using a selection diagram; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInclusion and exclusion criteria\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\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCriterion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInclusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhakic or pseudophakic eyes with idiopathic or secondary ERM (diabetic, post-cataract surgery, retinal vein occlusion, uveitis, trauma, previous retinal detachment).\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\u003ePPV surgery (23G/25G) with ERM peeling\u0026thinsp;\u0026plusmn;\u0026thinsp;ILM peeling; subgroups according to PPV or PPV/PHACO technique and lens status.\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\u003eGood quality preoperative and postoperative Spectralis macular OCT (signal\u0026thinsp;\u0026ge;\u0026thinsp;7/10 or Q\u0026thinsp;\u0026ge;\u0026thinsp;25 dB), without critical artefacts.\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\u003eFollow-up \u0026ge;\u0026thinsp;12 months with clinical evaluations and OCT at approximately 1, 3, 6 and 12 months.\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\u003eBCVA measured with ETDRS and converted to logMAR, recorded preoperatively and at 1, 3, 6 and 12 months.\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\u003eERM in G2\u0026ndash;4 at the time of surgery.\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\u003eFor secondary ERM: controlled underlying disease\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExclusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive primary maculopathies unrelated to ERM that confound the outcome (active AMD, dystrophies).\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\u003eUntreated AMD or active proliferative retinopathy; extensive ischaemic RVO or with active neovascularisation; active uveitis.\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\u003eProgressive optic neuropathy (advanced glaucoma).\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\u003eVR surgery other than ERM in the previous 3 months.\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\u003ePoor-quality OCT, media opacities that prevent quality imaging.\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\u003eLoss of follow-up for less than 6 months or incomplete or missing critical data.\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\u003eERM stage 1 at the time of surgery.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eERM\u0026thinsp;=\u0026thinsp;epiretinal membrane; PPV\u0026thinsp;=\u0026thinsp;pars plana vitrectomy; ILM\u0026thinsp;=\u0026thinsp;internal limiting membrane; VR: vitreoretinal; OCT\u0026thinsp;=\u0026thinsp;optical coherence tomography; BCVA\u0026thinsp;=\u0026thinsp;best-corrected visual acuity; ETDRS\u0026thinsp;=\u0026thinsp;Early Treatment Diabetic Retinopathy Study; logMAR\u0026thinsp;=\u0026thinsp;logarithm of the minimum angle of resolution; AMD\u0026thinsp;=\u0026thinsp;age-related macular degeneration; RVO\u0026thinsp;=\u0026thinsp;retinal vein occlusion.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eOCT\u0026thinsp;=\u0026thinsp;optical coherence tomography.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eFunctional assessment\u003c/h3\u003e\n\u003cp\u003eBCVA was measured with ETDRS letters under standardised conditions and at a fixed distance of 6 metres. The results were converted to the logMAR scale for statistical analysis. In cases of very low vision, conversions to logMAR were applied: finger counting (FC)\u0026thinsp;=\u0026thinsp;2.0; hand motion (HM)\u0026thinsp;=\u0026thinsp;2.3; light perception (LP)\u0026thinsp;=\u0026thinsp;2.7; no light perception (NLP)\u0026thinsp;=\u0026thinsp;3.0. Follow-up included preoperative assessment and check-ups at 1, 3, 6, and 12 months.\u003c/p\u003e \u003cp\u003eThe probability of being a \"respond\" was considered when the gain was greater than or equal to 0.2 logMAR (ΔlogMAR 12 m \u0026ndash; baseline), which is related to a change of 2 lines of letters according to the Snellen chart and has been used as a threshold value in the literature to define significant functional changes in VA.\u003c/p\u003e\n\u003ch3\u003eOCT image acquisition\u003c/h3\u003e\n\u003cp\u003eThe images were obtained with SD-OCT Spectralis (Heidelberg Engineering, Germany), following a standardised and reproducible protocol between controls. Macular cubes with fields of 20\u0026deg;\u0026times; 20\u0026deg; (6\u0026times;6 mm) or 30\u0026deg;\u0026times; 25\u0026deg; (8.8\u0026times;7.3 mm) fields, with 49\u0026ndash;97 B-scans. Automatic segmentation (ILM\u0026ndash;BM) was used, and each volume was manually inspected to detect foveal segmentation errors.\u003c/p\u003e\n\u003ch3\u003eQualitative analysis and operational definition of biomarkers\u003c/h3\u003e\n\u003cp\u003eThe analysis was performed by two ophthalmologists specialising in the retina, who were responsible for classifying the severity of ERM and identifying OCT biomarkers, tabulating data without access to the patient's clinical information.\u003c/p\u003e \u003cp\u003eEIFL was defined using Govetto's 2017 classification\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, recorded as a category from the apparent internal limit of the EIFL to the interface with the outer layers in the centre of the fovea.\u003c/p\u003e \u003cp\u003eG2 is defined as the loss of normal foveal depression, with some thickening of the outer nuclear layer (ONL), but without the formation of a continuous band of inner layer tissue in the fovea, and no EIFL. About G3, it is defined by the absence of foveal depression and the presence of a well-defined EIFL, with a continuous hypo/hyperreflective band corresponding to the inner nuclear layer (INL) plus the inner plexiform layer (IPL) crossing the foveal centre, although with the inner retinal layers still well defined, measurable between 50 and 250 \u0026micro;m centrally. Finally, G4 corresponds to advanced and thick ERM; EIFL is prominently present in the fovea, but with loss of normal laminar architecture, with internal layers appearing markedly disorganised. DRIL was defined as loss of distinguishable boundaries between the retinal nerve fibre layer (RNFL), the ganglion cell layer complex and the inner plexiform layer (GCIPL), the INL and the outer plexiform layer (OPL) in a 1 mm segment centred on the fovea; It was recorded according to severity as mild, moderate or severe, identified on the horizontal axis of the central B-scan. EZ integrity was classified as intact or disrupted around the foveal centre, as a dichotomous variable for statistical analysis purposes. COST (cone outer segment tips) line was recorded as present, defined as a continuous line, or absent/discontinuous on the foveal axis. Central bouquet (external foveal complex) was recorded as the presence of the cotton ball sign, as a rounded hyperreflective lesion in the outer foveal layers, foveolar detachment and acquired vitelliform lesion, in the presence of subfoveal hyperreflective material with underlying shadow, also being evaluated dichotomously as present or absent.\u003c/p\u003e \u003cp\u003eOf the quantitative parameters, the CMT is obtained in the central 1 mm ETDRS circle measured in microns (\u0026micro;m) at the foveal level.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were described as mean with standard deviation (SD) or median (interquartile range, IQR), as appropriate, after verifying the normality of distributions using the Shapiro\u0026ndash;Wilk test and the homogeneity of variances using Levene's test. Categorical variables, such as sex, laterality, ERM aetiology, Govetto stage, presence of EIFL, DRIL, EZ, COST, and central bouquet, were summarised as absolute frequencies and percentages. For univariate comparisons of continuous variables between more than two groups, one-way ANOVA with Bonferroni-adjusted post hoc tests was used; when the assumptions of normality and/or variances were not met, the Kruskal\u0026ndash;Wallis test with Dunn's multiple comparisons and Benjamini\u0026ndash;Hochberg multiplicity correction for multiple comparisons was applied. The comparison of proportions was performed using Pearson's χ\u0026sup2;, employing Yates' correction or Fisher's exact test when the expected values were small.\u003c/p\u003e \u003cp\u003eThe analysis of the dependent variable in our study was defined as the change in VA represented as Δ logMAR arithmetic difference between postoperative VA minus preoperative VA at 12 months; this was analysed with a paired Student's t-test or, in the case of non-normality, with the Wilcoxon test for related samples. The difference in means was determined with 95% confidence intervals (CI) and Cohen's dz effect size. Longitudinal follow-up of VA at 1, 3, 6, and 12 months. Fixed effects included time, aetiology, surgical technique, and biomarkers, in addition to the interaction terms time by group. All models were adjusted for clinical covariates and baseline BCVA in logMAR; the influence of the surgeon was evaluated in sensitivity analyses as a fixed factor or additional random term.\u003c/p\u003e \u003cp\u003eDifferences between groups in functional response were estimated using an ANCOVA approach, analysing the postoperative logMAR value at 12 months as the dependent variable, with groups separated by aetiology or surgical technique as the factor and adjusted for baseline BCVA and preoperative biomarkers; this is equivalent to contrast of change under assumptions, reducing bias due to regression to the mean. The prognostic value of biomarkers was examined using multiple linear regression with Δ logMAR as the dependent variable and, exploratively, with logistic regression for the probability of being a \"respond\" with 95% CIs. The discrimination of EIFL, COST, EZ, and DRIL was evaluated with ROC curves, obtaining the area under the curve (AUC). For ordinal variables such as EIFL stage reversal, a proportional odds ratio (OR) model was used.\u003c/p\u003e \u003cp\u003eWithin the time-to-event analysis, a time-to-response variable was constructed at 1, 3, 6, and 12 months, corresponding to the first follow-up at which response was achieved; non-responders were excluded at their last available follow-up. Overall Kaplan\u0026ndash;Meier (KM) curves were estimated and stratified by Govetto stage, aetiology, and surgical technique, with log-rank comparison. Cox proportional hazards models were adjusted exploratorily; the proportional hazards assumption was verified with Schoenfeld residuals when appropriate.\u003c/p\u003e \u003cp\u003eA two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. All analyses were performed using jamovi v2.6\u003csup\u003e22\u003c/sup\u003eand R v4.4\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eA priori sample size calculation\u003c/h3\u003e\n\u003cp\u003eThis was based on the primary variable. The paired t-test formula was used to detect a conservative mean improvement of 0.10 logMAR, with a standard deviation of the difference of 0.25, bilateral significance level α\u0026thinsp;=\u0026thinsp;0.05, and power 1\u0026thinsp;\u0026minus;\u0026thinsp;β\u0026thinsp;=\u0026thinsp;0.80.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographics\u003c/h2\u003e\n \u003cp\u003eThe study cohort had a mean age of 73.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4 years with a median of 74 (IQR 69\u0026ndash;80; range 17\u0026ndash;93) and a proportion of women of 58.5% (199/340). Baseline BCVA was 0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 logMAR, median 0.45 (IQR 0.30\u0026ndash;0.60; range \u0026minus;\u0026thinsp;0.16 to 3.00). Laterality was quantitatively similar, with 50.3% (171/340) in the right eye and 49.7% (169/340) in the left eye. The aetiology corresponded mostly to idiopathic ERM in 82.9% (282/340) versus secondary in 17.1% (58/340).\u003c/p\u003e\n \u003cp\u003eAccording to Govetto\u0026apos;s preoperative classification, G2 and G3 predominated with 48.8% and 42.9% respectively, and to a lesser extent G4 with 8.2%. The distribution of baseline OCT biomarkers and summarised categorical variables can be seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline categorical characteristics of the cohort (n\u0026thinsp;=\u0026thinsp;340 eyes)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLaterality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eERM aetiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdiopathic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGovetto\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgical technique\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPV\u0026thinsp;+\u0026thinsp;PHACO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEIFL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDRIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild (Mi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate (Mo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSevere (S)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisruption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntegrity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisruption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFull\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral bouquet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eERM: epiretinal membrane; OD: right eye; OS: left eye; PPV: pars plana vitrectomy; PHACO: phacoemulsification; DRIL: disorganisation of the retinal inner layers (none or absence, mild, moderate, severe); EZ: ellipsoid zone; COST: cone outer segment tips; Central bouquet: NO (no alterations), CBS: cotton ball sign, VIT: acquired vitelliform.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eOverall functional analysis\u003c/h2\u003e\n \u003cp\u003eThe primary objective of the study compared the change in BCVA, represented as \u0026Delta;logMAR\u0026thinsp;=\u0026thinsp;12m\u0026thinsp;\u0026minus;\u0026thinsp;baseline, showing an overall improvement with a mean of \u0026minus;\u0026thinsp;0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 and a median of \u0026minus;\u0026thinsp;0.23 (IQR \u0026minus;\u0026thinsp;0.42 to \u0026minus;\u0026thinsp;0.08; range \u0026minus;\u0026thinsp;2.37 to 1.08). Given that the distribution of differences did not meet Shapiro\u0026ndash;Wilk normality p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, the Wilcoxon rank test was used, which confirmed a statistically significant improvement (W\u0026thinsp;=\u0026thinsp;6422; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The effect size estimated as a biserial correlation of ranks was r\u0026thinsp;=\u0026thinsp;0.78, consistent with a high clinical impact. In practical terms, the median of \u0026minus;\u0026thinsp;0.23 logMAR approximates a gain of approximately 11\u0026ndash;12 ETDRS letters at 12 months. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the behaviour of overall BCVA, and according to covariates, through longitudinal follow-up.\u003c/p\u003e\n \u003cp\u003eWhen breaking down the visual results by aetiology, idiopathic ERMs (n\u0026thinsp;=\u0026thinsp;282), representing 82.94%, when analysing BCVA, show a median of \u0026minus;\u0026thinsp;0.22 (IQR \u0026minus;\u0026thinsp;0.39 to \u0026minus;\u0026thinsp;0.08; mean \u0026minus;\u0026thinsp;0.24), while in secondary ERM (n\u0026thinsp;=\u0026thinsp;58), representing 17.06%, it was \u0026minus;\u0026thinsp;0.27 (IQR \u0026minus;\u0026thinsp;0.82 to \u0026minus;\u0026thinsp;0.13; mean \u0026minus;\u0026thinsp;0.49). The Mann\u0026ndash;Whitney comparison was statistically significant (U\u0026thinsp;=\u0026thinsp;6694.5; p\u0026thinsp;=\u0026thinsp;0.0296); Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. However, when adjusting for covariates in an ANCOVA model with \u0026Delta;logMAR at 12 months as the dependent variable and including baseline BCVA in logMAR, age, sex, aetiology and surgical technique, it is noteworthy that baseline BCVA was the most decisive predictor (\u0026beta; = \u0026minus;0.766; 95% CI \u0026minus;\u0026thinsp;0.834 to \u0026minus;\u0026thinsp;0.697; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis according to surgical technique\u003c/h2\u003e\n \u003cp\u003eOf the 340 eyes, 256 (75.3%) underwent PPV\u0026thinsp;+\u0026thinsp;PHACO surgery and 84 (24.7%) underwent PPV surgery. Baseline BCVA was better in the PPV\u0026thinsp;+\u0026thinsp;PHACO group (mean 0.503\u0026thinsp;\u0026plusmn;\u0026thinsp;0.360 logMAR; median 0.42) than in the PPV alone group (mean 0.672\u0026thinsp;\u0026plusmn;\u0026thinsp;0.600; median 0.45); Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eFunctional improvement at 12 months was \u0026minus;\u0026thinsp;0.266\u0026thinsp;\u0026plusmn;\u0026thinsp;0.362 in PPV\u0026thinsp;+\u0026thinsp;PHACO and \u0026minus;\u0026thinsp;0.348\u0026thinsp;\u0026plusmn;\u0026thinsp;0.558 in PPV alone; the difference between techniques in \u0026Delta;logMAR was not significant (Mann\u0026ndash;Whitney W\u0026thinsp;=\u0026thinsp;10,244.5; p\u0026thinsp;=\u0026thinsp;0.517). The proportion of responders was 53.9% in VPP\u0026thinsp;+\u0026thinsp;PHACO and 59.5% in PPV, with no significant differences in the comparison of proportions.\u003c/p\u003e\n \u003cp\u003eIn the ANCOVA with 12-month BCVA as the adjusted dependent variable, the coefficient for PPV versus PPV\u0026thinsp;+\u0026thinsp;PHACO was \u0026beta; = +0.031 logMAR (95% CI \u0026minus;\u0026thinsp;0.043 to 0.106; p\u0026thinsp;=\u0026thinsp;0.408). In the logistic regression for \u0026quot;respond\u0026quot; the adjusted OR for PPV versus PPV\u0026thinsp;+\u0026thinsp;PHACO was 1.18 (95% CI 0.59\u0026ndash;2.36; p\u0026thinsp;=\u0026thinsp;0.625). In both models, baseline VA remained the dominant predictor of functional outcome (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis according to Govetto stage\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/h2\u003e\n \u003cp\u003eAccording to the OCT classification, the medians for \u0026ldquo;\u0026Delta;logMAR 12 m \u0026ndash; baseline\u0026rdquo; were, in G2: \u0026minus;0.2 (IQR \u0026minus;\u0026thinsp;0.380 to 0.000; n\u0026thinsp;=\u0026thinsp;166), G3: \u0026minus;0.225 (\u0026minus;\u0026thinsp;0.408 to \u0026minus;\u0026thinsp;0.100; n\u0026thinsp;=\u0026thinsp;146) and G4: \u0026minus;0.370 (\u0026minus;\u0026thinsp;0.628 to \u0026minus;\u0026thinsp;0.210; n\u0026thinsp;=\u0026thinsp;28). This overall difference between stages was significant; Kruskal\u0026ndash;Wallis H\u0026thinsp;=\u0026thinsp;7.61; p\u0026thinsp;=\u0026thinsp;0.0223; \u0026epsilon;\u0026sup2; = 0.0168 and, after correction for multiplicity according to the Benjamini\u0026ndash;Hochberg method, a greater improvement was found in G4 compared to G2 and G3, with a p FDR\u0026thinsp;=\u0026thinsp;0.0265 and p FDR\u0026thinsp;=\u0026thinsp;0.0338, respectively, with no differences between G2 and 3, p FDR\u0026thinsp;=\u0026thinsp;0.290; Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThese findings are statistically significant and consistent with a response rate associated with structural severity: the higher the G2 to 4, the greater the postoperative visual gain. However, when comparing the final BCVA, the more advanced the disease, the lower the BCVA. Therefore, the BCVA at each Govetto stage was consistent with the functional change, as detailed quantitatively, where in G2, the baseline BCVA was 0.519\u0026thinsp;\u0026plusmn;\u0026thinsp;0.458, BCVA at 12 months was 0.256\u0026thinsp;\u0026plusmn;\u0026thinsp;0.280, \u0026Delta; mean \u0026minus;\u0026thinsp;0.263 (SD 0.465). Meanwhile, in G3, the baseline BCVA was 0.553\u0026thinsp;\u0026plusmn;\u0026thinsp;0.423, at 12 months 0.268\u0026thinsp;\u0026plusmn;\u0026thinsp;0.278, mean \u0026Delta;\u0026thinsp;\u0026minus;\u0026thinsp;0.285 (SD 0.369). Finally, in G4, baseline BCVA was 0.933\u0026thinsp;\u0026plusmn;\u0026thinsp;0.514, at 12 months 0.345\u0026thinsp;\u0026plusmn;\u0026thinsp;0.342, mean \u0026Delta;\u0026thinsp;\u0026minus;\u0026thinsp;0.588 (SD 0.467); Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults by Govetto stage, preoperatively.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eG2 (n\u0026thinsp;=\u0026thinsp;166)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eG3 (n\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eG4 (n\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCVA, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD \u0026mdash; Baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.519\u0026thinsp;\u0026plusmn;\u0026thinsp;0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.553\u0026thinsp;\u0026plusmn;\u0026thinsp;0.423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.933\u0026thinsp;\u0026plusmn;\u0026thinsp;0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u0026times;10⁻⁵\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCVA, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD \u0026mdash; 12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.256\u0026thinsp;\u0026plusmn;\u0026thinsp;0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.268\u0026thinsp;\u0026plusmn;\u0026thinsp;0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.345\u0026thinsp;\u0026plusmn;\u0026thinsp;0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.311\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta;logMAR (12 m \u0026ndash; baseline), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026minus;0.263\u0026thinsp;\u0026plusmn;\u0026thinsp;0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026minus;0.285\u0026thinsp;\u0026plusmn;\u0026thinsp;0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026minus;0.588\u0026thinsp;\u0026plusmn;\u0026thinsp;0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0223\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u0026sup1; One-way ANOVA between stages; calculation based on means, SD and n per group.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u0026sup2; Kruskal\u0026ndash;Wallis test between stages.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis according to biomarkers\u003c/h2\u003e\n \u003cp\u003eAbout structural biomarkers, the measured basal CMT showed a mean of 457.5\u0026thinsp;\u0026plusmn;\u0026thinsp;81.4 \u0026micro;m (median 449.5 \u0026micro;m; IQR 399.5\u0026ndash;504). The association of basal CMT with structural severity was highly significant. Increasing medians were observed between the different stages, 423 \u0026micro;m in G2, 482 \u0026micro;m in G3 and 514 \u0026micro;m in G4, with overall heterogeneity by Kruskal\u0026ndash;Wallis (H\u0026thinsp;=\u0026thinsp;41.80; p\u0026thinsp;=\u0026thinsp;4.4\u0026times;10⁻⁹) and a positive Spearman correlation of moderate magnitude between Govetto stage and CMT (p\u0026thinsp;=\u0026thinsp;0.346; p\u0026thinsp;=\u0026thinsp;5.14\u0026times;10⁻\u0026sup1;\u0026sup1;), which robustly confirms that macular thickening increases as the stage progresses. However, it did not correlate directly with final BCVA in the multivariate analysis (p\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.09; p\u0026thinsp;=\u0026thinsp;0.10), Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eIn the cohort, preoperative EIFL was present in 45.6% of eyes (155/340). This biomarker was associated with greater structural severity at baseline OCT and showed a relationship according to Govetto stage, concentrating in G3-4 (p\u0026thinsp;=\u0026thinsp;0.568; p\u0026thinsp;=\u0026thinsp;2.0\u0026times;10⁻\u0026sup3;⁰) and with central macular thickness (p\u0026thinsp;=\u0026thinsp;0.272; p\u0026thinsp;=\u0026thinsp;3.6\u0026times;10⁻⁷).\u003c/p\u003e\n \u003cp\u003eIn the 12-month analysis, resolved EIFL was associated with better BCVA in eyes that had this biomarker preoperatively and achieved longitudinal follow-up (n\u0026thinsp;=\u0026thinsp;77; 69 with resolution and 8 with persistence). In the ANCOVA with 12-month BCVA as the multivariate-adjusted dependent variable, the effect of resolved EIFL was favourable but not significant (\u0026beta;= \u0026minus;0.161 logMAR; 95% CI \u0026minus;\u0026thinsp;0.720 to 0.397; p\u0026thinsp;=\u0026thinsp;0.571). Consistently, in the binomial model for the probability of being a \u0026quot;respond\u0026quot; there was a trend toward a greater respond with resolved EIFL (OR 5.22; 95% CI 0.24\u0026ndash;115.6), but it did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.296); Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrognostic value of biomarkers (preoperative) on response at 12 months\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePreoperative biomarker\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted association with \u0026quot;respond\u0026quot;\u0026sup1;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnivariate discrimination (ROC)\u0026sup2;\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u0026thinsp;=\u0026thinsp;2.08 (95% CI 1.17\u0026ndash;3.70); p\u0026thinsp;=\u0026thinsp;0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u0026thinsp;=\u0026thinsp;0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEIFL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u0026thinsp;=\u0026thinsp;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDRIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u0026thinsp;=\u0026thinsp;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u0026thinsp;=\u0026thinsp;0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral bouquet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u0026thinsp;=\u0026thinsp;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasal BCVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDominant predictor in all models; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e1\u003c/sup\u003e Multivariate logistic regression; dependent variable \u0026quot;responder\u0026quot;: gain\u0026thinsp;\u0026ge;\u0026thinsp;0.2 logMAR at 12 months. Models adjusted for at least baseline AV, age, sex, aetiology, and surgical technique. OR\u0026thinsp;\u0026gt;\u0026thinsp;1 indicates a higher probability of being a responder.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003e2\u003c/sup\u003e Univariate ROC curves by preoperative biomarker. AUC interpreted as isolated discrimination of the marker.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e*NS: not significant after adjustment.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eAt 12 months, baseline disruption of the COST line in OCT behaved as an independent predictor of visual response, if it regained its continuity postoperatively. In the binary model for \u0026quot;respond\u0026quot; starting with a disrupted COST line was associated with approximately a 2-fold increased likelihood of responding (OR\u0026thinsp;=\u0026thinsp;2.08; 95% CI 1.17\u0026ndash;3.70; p\u0026thinsp;=\u0026thinsp;0.013), after adjusting for baseline VA, clinical and anatomical covariates. Consistently, in the models with continuous VA, eyes that showed COST resolution achieved better VA at 12 months than those without recovery, with the effect remaining after multivariable adjustment.\u003c/p\u003e\n \u003cp\u003eEZ, DRIL, and central bouquet, when analysing pre- versus post-operative and prognostic value of \u0026quot;respond\u0026quot;. In the unadjusted analysis, postoperative restoration of the three biomarkers was associated with better VA at 12 months, while their persistence was associated with worse VA. However, when adjusted for baseline VA and clinical covariates, none showed an independent association in either the ANCOVA of VA at 12 months as dependent or in the binary regression for \u0026quot;respond\u0026quot; with p\u0026thinsp;\u0026ge;\u0026thinsp;0.05 in all cases. Their individual discriminatory capacity was limited, EZ with AUC: 0.515, DRIL with AUC: 0.525, and central bouquet with AUC: 0.56; Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eSurvival analysis\u003c/h2\u003e\n \u003cp\u003eIn the mixed linear models, a significant time effect was observed on BCVA, with early improvement that was maintained up to 12 months (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Baseline BCVA was 0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 logMAR and at 12 months approximately 0.26 logMAR, consistent with the averages by technique; PPV\u0026thinsp;+\u0026thinsp;PHACO 0.237\u0026thinsp;\u0026plusmn;\u0026thinsp;0.242; PPV 0.324\u0026thinsp;\u0026plusmn;\u0026thinsp;0.377. The overall change at 12 months was \u0026minus;\u0026thinsp;0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 logMAR (median \u0026minus;\u0026thinsp;0.23; Wilcoxon p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eIn the entire cohort, the median time to response was close to 3 months. By severity according to Govetto stage, the medians were 3 months (G2, n\u0026thinsp;=\u0026thinsp;166), 3 months (G3, n\u0026thinsp;=\u0026thinsp;146) and 1 month (G4, n\u0026thinsp;=\u0026thinsp;28). At 12 months, the probability of not responding was 30.1% (G2), 24.7% (G3) and 10.7% (G4), equivalent to cumulative response rates of 69.9%, 75.3% and 89.3%, respectively.\u003c/p\u003e\n \u003cp\u003eIn the univariate Cox model, compared with G2, G4 had a higher response risk rate (HR\u0026thinsp;=\u0026thinsp;1.67; p\u0026thinsp;=\u0026thinsp;0.021), with no differences for G3 (HR\u0026thinsp;=\u0026thinsp;1.15; p\u0026thinsp;=\u0026thinsp;0.302). By aetiology, the medians were 3 versus 3 months and 12-month survival was 27.7% for the idiopathic group versus 19.0% for the secondary group, with no differences in the hazard ratio (HR\u0026thinsp;=\u0026thinsp;1.13; p\u0026thinsp;=\u0026thinsp;0.466). By technique, the medians were 3 months for the PPV\u0026thinsp;+\u0026thinsp;PHACO technique and 3 (3\u0026ndash;6) months for PPV; 12-month survival rates were 27.3% vs 22.6%, respectively; HR\u0026thinsp;=\u0026thinsp;0.97; p\u0026thinsp;=\u0026thinsp;0.858. The overall proportional hazards test was significant with p\u0026thinsp;=\u0026thinsp;0.012; in the comparison by technique; consequently, these HRs should be interpreted with caution. (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e,\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFinally, in the sensitivity analysis, the inclusion of the surgeon as a fixed factor or as a random term did not modify the results, whether considered as univariate or multivariate.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur demographic results are consistent with series published in the literature, which highlight advanced age, with a mean of approximately 73 years, and a slight predominance of females. Meta-analyses indicate that advanced age and female sex are significant risk factors for developing ERM\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the quantitative analysis, the data from our study variable confirm that PPV with ERM peeling produces a significant functional improvement, with a mean BCVA improved from 0.54 to 0.26 logMAR (median \u0026minus;\u0026thinsp;0.23), equivalent to a gain of around 11\u0026ndash;12 ETDRS letters, corresponding to a gain of about 2 lines, with this improvement maintained for up to 12 months (Wilcoxon p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This finding is consistent with previously published studies reporting clinically relevant improvements in VA after ERM surgery. De Clerck et al. reported an improvement in BCVA from 0.5 to 0.8 measured using Snellen charts up to one year after surgery in the idiopathic ERM group\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and Kunavisarut et al. reported an increase in ETDRS of 51 to 65 letters at 6 months post-surgery\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In addition, other series detail in their results an improvement of around 70\u0026ndash;77% of patients gaining at least two lines after membrane peeling\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and Wong et al. reported a mean improvement of 0.31 logMAR (approximately 3 lines) with 83% of eyes improving\u0026thinsp;\u0026ge;\u0026thinsp;2 lines\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The effect size was large in our study (r\u0026thinsp;=\u0026thinsp;0.78), reinforcing the clinical impact of surgery.\u003c/p\u003e \u003cp\u003eIn the adjusted multivariate analysis, baseline BCVA stands out as the dominant predictor of postoperative gain.\u003c/p\u003e \u003cp\u003eWe found that eyes with worse baseline or initial BCVA gained more, as reported by other authors\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, who observed that 69.4% of patients improved their BCVA in the long term, with patients with worse initial BCVA gaining more; Wong et al. reported a direct correlation between pre- and post-operative BCVA, with quantitatively worse initial BCVA improving more after peeling\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e \u003cp\u003eAbout aetiology, we observed that secondary ERMs had worse preoperative vision and the greatest absolute gain on the logMAR scale, with a median of \u0026minus;\u0026thinsp;0.27 versus \u0026minus;\u0026thinsp;0.22 in idiopathic cases (p\u0026thinsp;=\u0026thinsp;0.03). This coincides with studies by Kang et al., who found that test with secondary ERM had worse baseline BCVA but achieved greater postoperative visual improvement, albeit with a higher recurrence rate (20% versus 4.9%)\u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSimilarly, Norton et al. found that eyes with secondary ERM had lower preoperative VA and improved significantly after surgery but had a higher incidence of postoperative cystoid macular oedema\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, when we adjusted for covariates, including baseline VA, age, sex, and surgical technique, the aetiology lost independent significance (p\u0026thinsp;=\u0026thinsp;0.171). The adjusted means of final gain were \u0026minus;\u0026thinsp;0.290 for idiopathic ERM and \u0026minus;\u0026thinsp;0.235 for secondary ERM, suggesting that the apparent advantage of secondary ERM is largely explained by their worse initial VA. This finding emphasises, as already noted, that initial visual acuity is key to the expected improvement.\u003c/p\u003e \u003cp\u003eIn terms of surgical technique, we found no significant differences in visual outcome between PPV\u0026thinsp;+\u0026thinsp;PHACO and PPV alone, with ΔlogMAR\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.27 vs \u0026minus;\u0026thinsp;0.35 (p\u0026thinsp;=\u0026thinsp;0.517). Recent studies report similar findings. Dermer et al. compared combined versus deferred surgery in ERM and found no significant differences in VA gain or anatomical parameters between the two groups\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur data are consistent with this conclusion and suggest that the combined approach does not alter adjusted visual improvement. Furthermore, the proportion of \"respond\" was comparable, with 54% for the combined surgery group versus 60% for PPV alone. Other groups have observed that combined surgery with an experienced anterior and posterior segment surgeon produces predictable refractive and visual outcomes like sequential surgeries\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In the ANCOVA analysis and even in multivariable logistic regression, the surgical technique variable showed no independent effect on final VA (p\u0026thinsp;\u0026gt;\u0026thinsp;0.4) or on the probability of responding (OR\u0026thinsp;=\u0026thinsp;1.18; p\u0026thinsp;=\u0026thinsp;0.625), reflecting that, after controlling for it, the attributable difference is marginal.\u003c/p\u003e \u003cp\u003eThe Govetto classification, according to G2 to 4, was associated with the postoperative outcome. As other authors have shown, eyes in more advanced stages have worse preoperative VA but greater absolute gain. In our cohort, the medians obtained in ΔlogMAR were \u0026minus;\u0026thinsp;0.20, \u0026minus;\u0026thinsp;0.225, and \u0026minus;\u0026thinsp;0.370 in G2, 3, and 4, respectively. The Kruskal-Wallis test confirmed overall differences (p\u0026thinsp;=\u0026thinsp;0.022) and adjusted post-hoc analysis indicated that G4 had superior gain compared to G2 and 3 (pFDR\u0026thinsp;=\u0026thinsp;0.03). This pattern coincides with the observation by De Clerck et al.\u003csup\u003e24\u003c/sup\u003e in Retina 2025, where only eyes in G4 maintained significantly worse VA in the long term, demonstrating that structural severity predicts the outcome. Similarly, Govetto et al.\u003csup\u003e13\u003c/sup\u003e reported that, in OCT classification, BCVA progressively decreases from stage 1 to stage 4, emphasising that greater structural damage implies a worse prognosis. In summary, our findings suggest that, although advanced ERMs gain more letters, given their lower functional ceiling, their final BCVA remains lower. This highlights the importance of early detection; operating before very advanced stages could optimise long-term functional outcome.\u003c/p\u003e \u003cp\u003eRegarding preoperative OCT biomarkers, several have been linked to visual prognosis as the main functional variable. In our cohort, the presence of EIFL was observed in 45.6% of eyes and was correlated with more severe stages (p\u0026thinsp;=\u0026thinsp;0.57). In anatomical-functional terms, the biomarkers evaluated reflect the degree, type of traction and foveal microstructural damage induced by ERM. EIFL represents the ectopia of internal layers, mainly GCL and IPL, towards the centre of the fovea, secondary to tangential traction and the glial response of M\u0026uuml;ller cells; its presence is associated with loss of foveal depression, reduction of the foveal avascular zone (FAZ) and poorer visual function due to misalignment of the central photoreceptors. The literature establishes that EIFL is a marker of advanced damage. Govetto et al.\u003csup\u003e13\u003c/sup\u003e identified EIFL in approximately 33% of their cases and associated it with significant visual loss, incorporating it into their classification scheme. In line with this, Govetto found in 2019 that eyes with preoperative EIFL had worse pre- and postoperative VA (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003csup\u003e15\u003c/sup\u003e. In our analysis, the resolution of postoperative EIFL tended to be associated with better functional outcome (OR\u0026thinsp;=\u0026thinsp;5.2 for responding\u0026thinsp;\u0026ge;\u0026thinsp;2 lines), but without reaching significance (p\u0026thinsp;=\u0026thinsp;0.296), possibly due to the limited number of cases with this biomarker at the end of follow-up.\u003c/p\u003e \u003cp\u003eThe integrity of the outer layers is key to sharp vision. The COST line reflects the coupling of the cone tips with the RPE; its basal interruption usually indicates damage or misalignment of the outer segments and predicts more limited visual recovery if it persists. Classic and subsequent studies have shown that COST integrity correlates with postoperative VA in ERM and other maculopathies, while its prolonged loss is associated with worse outcomes\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNotably, we identified COST line disruption as the only preoperative biomarker with an independent effect on functional outcome. Shimozono et al. demonstrated that COST line integrity is a useful prognostic factor after MER surgery\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur findings reinforce this concept, as recovery from COST disruption at diagnosis almost doubled the odds of responding adequately after surgery (OR\u0026thinsp;=\u0026thinsp;2.08; p\u0026thinsp;=\u0026thinsp;0.013).\u003c/p\u003e \u003cp\u003eThe EZ represents the integrity of the inner segments or mitochondrial bands of the cones; its postoperative restoration suggests metabolic and phototransduction recovery, but in our series, it had no independent effect after controlling for baseline VA and covariates. The literature is heterogeneous, as some studies find that interrupted EZ and DRIL are associated with worse VA and may have value in multivariate models, while others show modest discriminatory power in the short term. As for the inner layers, DRIL summarises the disorganisation of the boundaries between INL, IPL and GCL; its persistence translates into synaptic alteration and abnormal intraretinal conduction. Although in our study DRIL was not an independent predictor, specific ERM series have described associations with VA that may depend on stage, time of evolution and duration of EZ collapse. Similarly, alterations in the central foveal bouquet, which shows traction on the M\u0026uuml;ller fibre bundle and foveal cones, whose signs of central traction have been linked to poorer foveal morphology and metamorphopsia symptoms; their normalisation after peeling may accompany recovery, but their isolated prognostic power is limited\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn fact, MacCumber et al.\u003csup\u003e35\u003c/sup\u003e reported that CMT and DRIL did not correlate significantly with visual gain, although the DRIL sample size was small, which is equivalent to that obtained in our experience.\u003c/p\u003e \u003cp\u003eAfter surgery, none of the postoperative structural biomarkers at one year showed a significant association with final adjusted VA.\u003c/p\u003e \u003cp\u003eThe Kaplan\u0026ndash;Meier curves show that the functional response already described as \u0026ge;\u0026thinsp;0.2 logMAR occurs early, with a median of close to 3 months. Therefore, the expected improvement in the first 12 weeks and the surgical opportunity should consider that, although advanced stages respond earlier, they reach lower functional ceilings, favouring intervention before progression.\u003c/p\u003e \u003cp\u003eFor this reason, our repeated measures models confirmed that most visual recovery occurs early. The study by Creuzot-Garcher et al. observed that VA improvement and foveal thickness reduction occur mainly in the first 6 months, with little additional gain beyond that point\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In fact, Romano et al. reported that the greatest increase in VA occurred 1 month post-surgery (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003csup\u003e37\u003c/sup\u003e, and in our cohort we see a similar pattern of stabilisation after 1 to 3 months. This suggests that initial follow-up should be close and that VA remains at a plateau until one year.\u003c/p\u003e \u003cp\u003eThis study provides a large cohort of patients in real-world practice, with serial follow-up and standardised anatomical characterisation. However, the retrospective design limits generalisation and may leave room for confusion regarding indications; the dichotomous definition of \"respond\" simplifies the continuous response; interobserver variability of biomarkers was not quantified. Nevertheless, the findings offer solid and clinically useful evidence.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFinally, our results support international findings, where ERM surgery with PPV significantly improves BCVA, especially in patients with poorer initial acuity. The difference between idiopathic and secondary ERM disappears when adjusted for baseline AV, as does the choice of simultaneous versus deferred PHACO. The structural stage according to Govetto predicts the degree of gain, although not the final absolute VA value. OCT biomarkers such as the COST line and the presence of EIFL are consistent with a poorer visual prognosis. Overall, these results reinforce current guidelines and help to put our findings into clinical context in comparison with the international literature.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAge-related macular degeneration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBCVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBest-corrected visual acuity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBruch\u0026rsquo;s membrane\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCotton ball sign\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentral macular thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCone outer segment tips\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDRIL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDisorganisation of the retinal inner layers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEZ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEllipsoid zone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eETDRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEarly Treatment Diabetic Retinopathy Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFinger counting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGCIPL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGanglion cell layer\u0026ndash;inner plexiform layer complex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHand motion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eILM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternal limiting membrane\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInner nuclear layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIPL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInner plexiform layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003elogMAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLogarithm of the minimum angle of resolution\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLight perception\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNLP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNo light perception\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOptical coherence tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight eye\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eONL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOuter nuclear layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOPL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOuter plexiform layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft eye\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePHACO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhacoemulsification\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePars plana vitrectomy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRNFL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRetinal nerve fibre layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRVO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRetinal vein occlusion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD-OCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSpectral-domain optical coherence tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTROBE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStrengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVitreoretinal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVIT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcquired vitelliform (lesion)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003e \u003cb\u003eEthics approval and consent to participate\u003c/b\u003e.\u003c/strong\u003e \u003cp\u003eThis study was conducted in accordance with the tenets of the Declaration of Helsinki\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The study protocol was reviewed and approved by the ethics committee of FOLA, Santiago, Chile. Given the retrospective, observational design and the use of de-identified clinical data, the requirement for written informed consent to participate was waived by the ethics committee.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003e \u003cb\u003eCompeting interests\u003c/b\u003e.\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding.\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePBA conceived and designed the study. PBA, ABR, ABB, EUI and JCO collected the data. PBA performed the statistical analysis and interpreted the results. JIVD, MJRF, LFL, JMLA, SZS, JOR and EPA contributed to patient management/surgical care and provided critical clinical input. PBA drafted the manuscript. ABR, ABB, EUI, JCO, JIVD, MJRF, LFL, JMLA, SZS, JOR and EPA critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors thank the clinical and imaging staff of FOLA for their support in patient care and data acquisition.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e- Xiao W, Chen X, Yan W, Zhu Z, He M. Prevalence and risk factors of epiretinal membranes: a systematic review and meta-analysis of population-based studies. BMJ Open 25 September. 2017;7(9):e014644.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kunavisarut P, Supawongwattana M, Patikulsila D, Choovuthayakorn J, Watanachai N, Chaikitmongkol V. Idiopathic Epiretinal Membranes: Visual Outcomes and Prognostic Factors. 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Invest Ophthalmol Vis Sci. 2019;60(9):5760.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamel -YKJ-C, Isaico R, Aur\u0026eacute;lie, De Lazzer AM, Bron. Catherine Creuzot-Garcher; Long-Term Anatomical and Functional Outcomes after Combined Cataract and Idiopathic Epiretinal Membrane Surgery. Ophthalmic Res 1 February 2017; 57 (2): 125\u0026ndash;134. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1159/000452837\u003c/span\u003e\u003cspan address=\"10.1159/000452837\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Romano M, Catania F, Vallejo-Garcia JL, Sorrentino T, Crincoli E, Vinciguerra P. Variability of Visual Recovery with Time in Epiretinal Membrane Surgery: A Predictive Analysis Based on Retinal Layer OCT Thickness Changes. J Clin Med 8 March. 2023;12(6):2107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12062107\u003c/span\u003e\u003cspan address=\"10.3390/jcm12062107\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36983110; PMCID: PMC10059266.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-retina-and-vitreous","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"IJRV","sideBox":"Learn more about [International Journal of Retina and Vitreous](https://jneurodevdisorders.biomedcentral.com/)","snPcode":"40942","submissionUrl":"https://submission.nature.com/new-submission/40942/3","title":"International Journal of Retina and Vitreous","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Epiretinal Membrane, Vitrectomy, Optical Coherence Tomography, Biomarkers, Visual Acuity","lastPublishedDoi":"10.21203/rs.3.rs-8371594/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8371594/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eTo determine the functional and anatomical outcomes at 12 months after pars plana vitrectomy (PPV) for epiretinal membrane (ERM) and the independent prognostic value of preoperative biomarkers in optical coherence tomography (OCT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFive-year analytical study of 340 eyes with ERM in stages (Govetto G2–4). Best-corrected visual acuity (BCVA) logMAR and OCT were evaluated at baseline, 1, 3, 6, and 12 months. The primary objective was to determine the change in BCVA at 12 months (ΔlogMAR 12 m – baseline). Univariate tests, ANCOVA, longitudinal mixed linear models, and logistic regression were applied for gain ≥0.2 logMAR. The models were adjusted for baseline VA, age, sex, aetiology, surgical technique, and analysis of biomarkers in OCT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eBaseline VA was 0.54±0.44 logMAR; distribution according to G2 (n=166), G3 (n=146), G4 (n=28). VA improved significantly at 12 months (Wilcoxon p\u0026lt;0.001), equivalent to 11–12 ETDRS letters. Secondary ERMs showed greater unadjusted gain than idiopathic ones, but aetiology was not an independent predictor after adjustment. The surgical technique was not independently associated with VA at 12 months (β=+0.031 logMAR; 95% CI; p=0.408) or with responder status (OR 1.18; 95% CI; p=0.625). By severity, advanced stages had worse baseline VA and greater absolute gains (Kruskal–Wallis H=7.61; p=0.0223), although with lower final VA compared to lesser stages. Baseline VA was the dominant predictor in all models (β=−0.766; 95% CI; p\u0026lt;0.001). Among preoperative biomarkers, COST line disruption independently increased the probability of response (OR=2.08; 95% CI; p=0.013). DRIL, EZ disruption, and central bouquet alterations did not reach significance after adjustment.\u003c/p\u003e\n\u003cp\u003eMixed models confirmed early improvement, maintained up to 12 months. Kaplan–Meier showed faster time to response in advanced stages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003ePPV by ERM achieves significant improvement at 12 months. Baseline VA is the main determinant of prognosis. According to Govetto's classification, the greatest gain occurs in advanced stages, but with lower final VA. The COST line emerges as the only preoperative biomarker with independent prognostic value for achieving ≥0.2 logMAR; the others provide limited utility when baseline VA is considered.\u003c/p\u003e\n\u003cp\u003eTrial registration: Not applicable.\u003c/p\u003e","manuscriptTitle":"Surgical prognosis in epiretinal membrane: A 5-year longitudinal study of OCT biomarkers and visual acuity at a high-complexity referral center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 01:04:53","doi":"10.21203/rs.3.rs-8371594/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-14T13:03:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-14T04:30:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254035089198689880420432210104591707298","date":"2026-01-28T13:48:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-11T19:41:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"63418726111557572697965565172642879424","date":"2025-12-27T15:25:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-22T12:18:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-21T08:29:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-18T18:23:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Retina and Vitreous","date":"2025-12-16T03:54:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-retina-and-vitreous","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"IJRV","sideBox":"Learn more about [International Journal of Retina and Vitreous](https://jneurodevdisorders.biomedcentral.com/)","snPcode":"40942","submissionUrl":"https://submission.nature.com/new-submission/40942/3","title":"International Journal of Retina and Vitreous","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4ae7c819-15cc-4c15-9543-40fa83199ee4","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T09:10:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 01:04:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8371594","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8371594","identity":"rs-8371594","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}