Purpose: To evaluate the effect of corneal nerves assessment on predicting corneal complications following pars plana vitrectomy (PPV). Methods: In this prospective single-center cohort study, 94 patients (94 eyes) received PPV, and were divided into postoperative groups with and without corneal complications. All eyes had corneal nerve fiber length (CNFL), corneal nerve fiber density, and branch density of corneal nerve fibers assessed and calculated with Image J preoperatively. Multivariate logistic regression analysis was used to identify corneal nerve fiber parameters that correlated to post-operative corneal complications. Receiver operator characteristic curve analysis was performed to identify the optimal cut-off point of the corneal fibers’ parameters for predicting corneal complications after PPV. Results: Eleven eyes (11.70%) developed corneal complications at 1 week after PPV. There was significant difference between CNFL (19.44 ± 6.88 vs. 26.84 ± 7.53, p = 0.003), corneal nerve fiber density (28.82 ± 9.91 vs. 37.10 ± 10.16, p = 0.013) and branch density of corneal nerve fibers (55.84 ± 21.08 vs. 82.04 ± 31.89, p = 0.01) in two groups, respectively. Receiver operator characteristic analysis showed that the optimal cutoff value of CNFL to predict corneal complications following PPV was <26.495 mm/mm2. Conclusions The decrease of CNFL may predict corneal complications following PPV. Regular preoperative corneal confocal microscopy test in PPV patients could be considered.

Purpose: To evaluate the effect of corneal nerves assessment on predicting corneal complications following pars plana vitrectomy (PPV). Methods: In this prospective single-center cohort study, 94 patients (94 eyes) received PPV, and were divided into postoperative groups with and without corneal complications. All eyes had corneal nerve fiber length (CNFL), corneal nerve fiber density, and branch density of corneal nerve fibers assessed and calculated with Image J preoperatively. Multivariate logistic regression analysis was used to identify corneal nerve fiber parameters that correlated to post-operative corneal complications. Receiver operator characteristic curve analysis was performed to identify the optimal cut-off point of the corneal fibers’ parameters for predicting corneal complications after PPV. Results: Eleven eyes (11.70%) developed corneal complications at 1 week after PPV. There was significant difference between CNFL (19.44 ± 6.88 vs. 26.84 ± 7.53, p = 0.003), corneal nerve fiber density (28.82 ± 9.91 vs. 37.10 ± 10.16, p = 0.013) and branch density of corneal nerve fibers (55.84 ± 21.08 vs. 82.04 ± 31.89, p = 0.01) in two groups, respectively. Receiver operator characteristic analysis showed that the optimal cutoff value of CNFL to predict corneal complications following PPV was <26.495 mm/mm2. Conclusions The decrease of CNFL may predict corneal complications following PPV. Regular preoperative corneal confocal microscopy test in PPV patients could be considered.

Purpose: To assess the feasibility of applying ultra-widefield fundus (UWF) images for macular staphyloma area (MSA) measurement and investigate the associated factors with MSA. Methods: This is a retrospective study. MSA was measured by UWF imaging. Central foveal thickness, subfoveal choroidal thickness, subfoveal scleral thickness were measured on spectral domain optical coherence tomography. Intraclass correlation coefficients of MSA measurement would be evaluated. Multiple linear regression analysis was used to analyze the associated factors with MSA. Results: In total, 135 eyes of 92 patients were enrolled. The mean age was 64.73 ± 10.84 years. Mean MSA on UWF image was 279.67 ± 71.70 mm2. Intraclass correlation coefficients of MSA measurement was 0.965 (95% confidence interval [CI], 0.946 to 0.977; p < 0.001). In the multiple linear regression analysis, after adjusting for subfoveal choroidal thickness, best-corrected visual acuity, central foveal thickness, and subfoveal scleral thickness, the factors independently related to MSA were axial length (β = 8.352; 95% CI, 3.306 to 13.398; p = 0.001), sex (β = -26.673; 95% CI, -51.759 to -1.586; p = 0.037), age (β = 1.184; 95% CI, 0.020 to 2.348; p = 0.046). Conclusions It is feasible to measure MSA on UWF image. Female, longer axial length, and older age may indicate larger MSA.