Context: Only a few studies have assessed intraocular pressure (IOP) changes during the water drinking test (WDT) in patients with primary angle-closure glaucoma (PACG). Aims: The aim of this study is to investigate IOP changes during WDT in patients with PACG versus primary open-angle glaucoma (POAG). Settings and Design: This was a prospective and single tertiary center study. Materials and Methods: PACG and POAG patients (n = 15 each) without prior glaucoma surgery were enrolled and subjected to WDT, wherein they consumed an amount of water proportional to their body weight within 10 min. IOP was measured at baseline and every 15 min for 1 h after water intake. Statistical Analysis Used: Intergroup comparisons were performed using Mann–Whitney U-test for continuous variables and Chi-square test for categorical variables. Wilcoxon signed-ranks test was used for comparisons of IOP before and after water intake in the two groups. Regression analysis was used to determine factors associated with IOP fluctuations during WDT. Results: IOP changes over 1 h after water intake showed no significant differences between groups. The mean maximum fluctuation from baseline was 3.61 ± 2.49 and 3.79 ± 1.91 mmHg, respectively, in the PACG and POAG groups. The mean peak IOP was 19.17 ± 4.32 and 19.87 ± 3.44 mmHg in the PACG and PAOG groups, respectively. The axial length and anterior chamber depth showed no correlations with IOP fluctuations. Conclusions: We found similar IOP fluctuation curves and peak IOP values in both PACG and POAG patients subjected to WDT. These findings suggest that WDT is a useful test to induce IOP peaks in both POAG and PACG patients.

Purpose: Intraocular pressure (IOP) measurement is critical in diagnosing and managing eye conditions. This study aims to assess the comparability of three alternative devices for measuring IOP: Noncontact tonometer, Icare rebound tonometer, and Tono-Pen. Patients and Methods: A cross-sectional study included 172 adult participants (87 males and 85 females) who underwent IOP and central corneal thickness (CCT) assessments. IOP was measured using Noncontact (Canon TX-20), Icare (Icare TA01i), and Tono-Pen (Tonopen XL). CCT was measured with the built-in pachymetry of the Noncontact tonometer. Correlation coefficients and Bland-Altman analyses were conducted to assess the relationships and agreements between these tonometers. Participants were grouped based on IOP and CCT levels. The mean of the standard deviation of the three tonometer results was calculated to evaluate measurement result variability. One-way analysis of variance was conducted for comparing between the groups. Results: IOP measurements among the three devices were not significantly different, indicating their comparability. Correlation analysis revealed strong correlations between the tonometers. Bland-Altman analysis showed good agreement, with the Icare rebound tonometer and Tono-Pen exhibiting narrower limits of agreement. Furthermore, IOP levels influenced measurement result variability, with higher IOP levels associated with greater variance. Conclusion: This study demonstrates that the alternative devices examined can provide reliable IOP measurements. It highlights the potential of these alternative devices for IOP measurement. These findings have implications for clinical practice, offering practitioners additional tools for accurate IOP assessment.

(1) Purpose: To investigate the efficacy of myopia treatment in children using atropine 0.125% once every two nights (QON) compared with atropine 0.125% once every night (HS). (2) Methods: This retrospective cohort study reviewed the medical records of two groups of children with myopia. Group 1 comprised children treated with atropine 0.125% QON, while group 2 included children treated with atropine 0.125% HS. The first 6 months of data of outcome measurements were subtracted as washout periods in those children undergoing both atropine QON and HS treatment. The independent t-test and Pearson’s chi-square test were used to compare the baseline clinical characteristics between the two groups. A generalized estimating equations (GEE) model was used to determine the factors that influence treatment effects. (3) Results: The average baseline ages of group 1 (38 eyes from 19 patients) and group 2 (130 eyes from 65 patients) were 10.6 and 10.2 years, respectively. There were no significant differences in axial length (AL) or cycloplegic spherical equivalent (SEq) at baseline or changes of them after 16.9 months of follow-up. GEE showed that the frequency of atropine 0.125% use has no association with annual AL (QON vs. HS: 0.16 ± 0.10 vs. 0.18 ± 0.12) and SEq (QON vs. HS: −0.29 ± 0.44 vs. −0.34 ± 0.36) changes in all children with myopia. It also showed that older baseline age (B = −0.020, p < 0.001) was associated with lesser AL elongation. (4) Conclusion: The treatment effects of atropine 0.125% HS and QON were similar in this pilot study. The use of atropine 0.125% QON may be an alternative strategy for children who cannot tolerate the side effects of atropine 0.125% HS. This observation should be confirmed with further large-scale studies.

To segment the inner macular layers (IML) and compare the discriminating abilities of the macular and peripapillary retinal nerve fiber layer (mRNFL and pRNFL, respectively) thicknesses in patients with early-stage normal tension glaucoma (NTG). Cross-sectional study Forty-nine normal subjects and 69 preperimetric glaucoma (PPG) and 60 NTG patients were enrolled. Spectral-domain optical coherence tomography (SD-OCT) was used to obtain pRNFL and macular thickness parameters and segment the IML in all subjects. Area under the receiver operating characteristic (AUROC) curves were used to compare the diagnostic capabilities of different parameters. The pRNFL, total macular layer (TML), mRNFL, and macular ganglion cell layer (mGCL) were significantly thinner in the NTG group than in the PPG and normal groups. The global and superotemporal pRNFL and the mGCL in the superior outer area were the three best parameters for detecting early NTG. The discriminating capabilities of the superior and inferior mGCL were comparable to those of the corresponding pRNFL (p = 0.573, 0.841). Concerning location, the mGCL had higher AUROCs in the outer sectors (0.863, 0.837) than in the inner sectors (0.747, 0.747). Pearson’s correlation coefficients also revealed significant correlations between the mGCL and pRNFL (superior: r = 0.499, inferior: r = 0.624). The strongest correlation was between the mGCL and mean deviation (MD) (superior: r = 0.434 and inferior: r = 0.402). The diagnostic value of mGCL thickness is comparable to that of pRNFL thickness. IMLs in the outer sectors had better diagnostic capabilities than those in the inner sector for detecting early NTG.

Glucocorticoids play a pivotal role in therapeutic protocols in acute lymphoblastic leukemia (ALL) treatment. Systemic steroids are known to be less likely to elevate the intraocular pressure when compared to topical administration, and reports addressing hypertensive ocular response in the Asian pediatric ALL population are currently limited. We report a case of a nine-year-old girl with acute lymphoblastic leukemia (ALL) who was found to have highly elevated intraocular pressure (IOP) during maintenance treatment when taking oral dexamethasone (6 mg/m²/day). Her IOP increased on day 5 after taking dexamethasone, reached a peak on day 7 or 8, and returned back to baseline on day 13 before anti-glaucoma medications were used. Thus, we prescribed IOP-lowering agents for 10 consecutive days starting on the day oral dexamethasone was administered, and observed that not only did the peak levels lower remarkably, but the IOP levels returned to baseline more rapidly as well.

Glaucoma is a leading cause of irreversible blindness worldwide; therefore, detection of this disease in its early stage is crucial. However, previous efforts to identify early-stage glaucoma have faced challenges, including insufficient accuracy, sensitivity, and specificity. This study presents a concatenated artificial intelligence model that combines two types of input features: fundus images and quantitative retinal thickness parameters derived from macular and peri-papillary retinal nerve fiber layer (RNFL) thickness measurements. These features undergo an intelligent transformation, referred to as “smart preprocessing”, to enhance their utility. The model employs two classification approaches: a convolutional neural network approach for processing image features and an artificial neural network approach for analyzing quantitative retinal thickness parameters. To maximize performance, hyperparameters were fine-tuned using a robust methodology for the design of experiments. The proposed AI model demonstrated outstanding performance in early-stage glaucoma detection, outperforming existing models; its accuracy, sensitivity, specificity, precision, and $F_1$-Score all exceeding 0.90.