In the last decade, we have witnessed substantial progress in our understanding of corneal biomechanics and architecture. It is well known that diabetes is a systemic metabolic disease that causes chronic progressive damage in the main organs of the human body, including the eyeball. Although the main and most widely recognized ocular effect of diabetes is on the retina, the structure of the cornea (the outermost and transparent tissue of the eye) can also be affected by the poor glycemic control characterizing diabetes. The different corneal structures (epithelium, stroma, and endothelium) are affected by specific complications of diabetes. The development of new noninvasive diagnostic technologies has provided a better understanding of corneal tissue modifications. The objective of this review is to describe the advances in the knowledge of the corneal alterations that diabetes can induce.

Purpose: To evaluate and compare corneal hysteresis (CH), corneal resistance factor (CRF), and central corneal thickness (CCT), measurements were taken between a healthy population (controls), patients diagnosed with glaucoma (DG), and glaucoma suspect patients due to ocular hypertension (OHT), family history of glaucoma (FHG), or glaucoma-like optic discs (GLD). Additionally, Goldmann-correlated intraocular pressure (IOPg) and corneal-compensated IOP (IOPcc) were compared between the different groups of patients. Methods: In this prospective analytical-observational study, a total of 1065 patients (one eye of each) were recruited to undergo Ocular Response Analyzer (ORA) testing, ultrasound pachymetry, and clinical examination. Corneal biomechanical parameters (CH, CRF), CCT, IOPg, and IOPcc were measured in the control group (n = 574) and the other groups: DG (n = 147), FHG (n = 78), GLD (n = 90), and OHT (n = 176). We performed a variance analysis (ANOVA) for all the dependent variables according to the different diagnostic categories with multiple comparisons to identify the differences between the diagnostic categories, deeming p < 0.05 as statistically significant. Results: The mean CH in the DG group (9.69 mmHg) was significantly lower compared to controls (10.75 mmHg; mean difference 1.05, p < 0.001), FHG (10.70 mmHg; mean difference 1.00, p < 0.05), GLD (10.63 mmHg; mean difference 0.93, p < 0.05) and OHT (10.54 mmHg; mean difference 0.84, p < 0.05). No glaucoma suspects (FHG, GLD, OHT groups) presented significant differences between themselves and the control group (p = 1.00). No statistically significant differences were found in the mean CRF between DG (11.18 mmHg) and the control group (10.75 mmHg; mean difference 0.42, p = 0.40). The FHG and OHT groups showed significantly higher mean CRF values (12.32 and 12.41 mmHg, respectively) than the DG group (11.18 mmHg), with mean differences of 1.13 (p < 0.05) and 1.22 (p < 0.001), respectively. No statistically significant differences were found in CCT in the analysis between DG (562 μ) and the other groups (control = 556 μ, FHG = 576 μ, GLD = 569 μ, OHT = 570 μ). The means of IOPg and IOPcc values were higher in the DG patient and suspect groups than in the control group, with statistically significant differences in all groups (p < 0.001). Conclusion: This study presents corneal biomechanical values (CH, CRF), CCT, IOPg, and IOPcc for diagnosed glaucoma patients, three suspected glaucoma groups, and a healthy population, using the ORA. Mean CH values were markedly lower in the DG group (diagnosed with glaucoma damage) compared to the other groups. No significant difference was found in CCT between the DG and control groups. Unexpectedly, CRF showed higher values in all groups than in the control group, but the difference was only statistically significant in the suspect groups (FHG, GLD, and OHT), not in the DG group.

(1) Purpose: To assess the main corneal response differences between normal and subclinical keratoconus (SCKC) with a Corvis^® ST device. (2) Material and Methods: We selected 183 eyes of normal patients, of a mean age of 33 ± 9 years and 16 eyes of patients with SCKC of a similar mean age. We measured best corrected visual acuity (BCVA) and corneal topography with a Pentacam HD device to select the SCKC group. Biomechanical measurements were performed using the Corvis^® ST device. We carried out a non-parametric analysis of the data with SPSS software (Wilcoxon signed rank-test). (3) Results: We found statistically significant differences between the control and SCKC groups in some corneal biomechanical parameters: first and second applanation time (p = 0.05 and p = 0.02), maximum deformation amplitude (p = 0.016), highest concavity radius (p = 0.007), and second applanation length and corneal velocity ((p = 0.039 and p = 0.016). (4) Conclusions: Our results show that the use of normalised biomechanical parameters provided by noncontact tonometry, combined with a discriminant function theory, is a useful tool for detecting subclinical keratoconus.

This non-comparative prospective case series was conducted to characterize the clinical impact of intense pulsed light (IPL)-based treatment in dry eyes associated to Meibomian gland dysfunction (MGD), defining the predicting factors for a successful outcome with this therapy in a large case series. A total of 390 eyes (195 patients, range: 23–93 years) received four sessions of Optima IPL system (Lumenis, Yokneam, Israel). Significant changes were observed in tear film osmolarity in both eyes (p < 0.001) and in meibum quality (p < 0.001), with more eyes showing clear or yellow secretions after therapy. Mean change in the ocular surface disease index (OSDI) was −8.61, ranging from −27.00 to 11.00. This change was significantly correlated with the baseline value of OSDI (r = −0.489, p < 0.001). The change in osmolarity correlated significantly with the baseline osmolarity in both eyes (right r = −0.636, left r = −0.620, p < 0.001). A linear predicting model of the change in OSDI with therapy was obtained: change OSDI = 10.99 − 0.35 × OSDI − 1.03 × NIBUT_RE-LE (mean non-invasive break up time of right and left eye) − 2.03 × Meibum quality grade (p = 0.001; R²: 0.325). In conclusion, the improvement in symptomatology achieved with an IPL-based therapy can be predicted at baseline using a linear model considering the level of MGD and the magnitude of OSDI and NIBUT (non-invasive break-up time).