Ta-Hung Chiu

Topic: To evaluate the efficacy and safety of femtosecond laser-assisted cataract surgery (FLACS) vs conventional phacoemulsification in eyes with shallow anterior chambers or primary angle-closure disease, with endothelial cell loss (ECL) as the primary outcome (PROSPERO: CRD420251274747). Clinical Relevance: Shallow anterior chambers pose unique surgical challenges during phacoemulsification, placing the corneal endothelium at increased risk of damage. This population, disproportionately prevalent in Asia, is expected to grow substantially with aging demographics, underscoring the need for optimized surgical strategies. Methods: MEDLINE, Embase, and Cochrane CENTRAL were searched through January 2026. Randomized controlled trials and observational studies comparing FLACS with conventional phacoemulsification were included. Risk of bias was assessed using Cochrane Risk of Bias 2 tool and Newcastle-Ottawa Scale. Pooled estimates were calculated using random-effects models; certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation framework. Results: 6 studies (505 eyes) were analyzed. FLACS was associated with lower ECL (mean difference [MD] −4.97%; 95% CI −8.27 to −1.67; P = .003; I ² = 98%) and cumulative dissipated energy (MD −2.47; 95% CI −3.64 to −1.30; P < .001; I ² = 14% in sensitivity analysis). FLACS was associated with 60% lower odds of early postoperative complications (odds ratio 0.40; 95% CI 0.23-0.68; P < .001; I ² = 0%). Visual outcomes were comparable. Conclusions: FLACS was associated with fewer early postoperative complications, supported by moderate-certainty evidence, and with lower ECL and ultrasound energy, although the magnitude of these benefits remains uncertain on low-certainty evidence.

Glaucoma is a multifaceted optic neuropathy, characterized by the progressive loss of retinal ganglion cells. This damage frequently continues even after intraocular pressure (IOP) has been effectively lowered. This resistance to conventional IOP-lowering therapy underscores the critical role of interacting IOP-independent mechanisms; specifically metabolic failure and systemic mitochondrial dysfunction have emerged as key parallel drivers. This review analyzes the paradigm shift from a pressure-centric model to a bioenergetic one, focusing on mitochondrial function, peripheral blood mononuclear cell (PBMC) biomarkers, and oxygen consumption dynamics. We synthesize evidence demonstrating that glaucoma patients exhibit a metabolic vulnerability, characterized by lower PBMC oxygen consumption rates and depleted systemic nicotinamide adenine dinucleotide levels relative to healthy individuals. Furthermore, compromised systemic respiratory performance correlates with more rapid worsening of visual fields and structural thinning, independent of IOP status. Moreover, we delineate the role of Complex I defects, SARM1-mediated axonal degeneration, and proteomic alterations, which indicate defective mitophagy. These findings establish systemic metabolic profiling as a valuable supplementary tool for assessing patient risk and support the clinical translation of neuroprotective therapies targeting mitochondrial bioenergetics, specifically nicotinamide, pyruvate, coenzyme Q₁₀, and metformin.

Glaucoma continues to be a primary contributor to permanent vision loss worldwide, frequently advancing even when intraocular pressure management is clinically adequate. Accumulating research emphasizes the metabolic susceptibility of retinal ganglion cells (RGCs), specifically concerning the progressive depletion of nicotinamide adenine dinucleotide (NAD⁺), a pivotal coenzyme fundamental to mitochondrial energy production and cellular survival mechanisms. As a key biosynthetic precursor in NAD⁺ synthesis pathways, nicotinamide (NAM), a form of vitamin B3, has exhibited significant neuroprotective properties across various preclinical experimental models and preliminary clinical investigations, demonstrating enhanced preservation of RGC morphology and physiological function. This comprehensive review systematically examines the current body of evidence supporting NAM’s therapeutic utility in glaucomatous neuroprotection, focusing particularly on underlying metabolic pathways, obstacles in clinical translation, and prospective therapeutic applications. Through systematic integration of data from cellular and molecular research, animal experimental studies, and population-based epidemiological investigations, we establish a conceptual framework for repurposing NAM as an innovative complementary therapeutic strategy in comprehensive glaucoma care, addressing key considerations for future clinical development including optimal dosing strategies, delivery mechanisms, and patient selection criteria for maximizing therapeutic outcomes in this challenging neurodegenerative condition.

Glaucoma is recognized as a progressive optic neuropathy and a leading cause of irreversible blindness worldwide. While intraocular pressure (IOP) is considered the only modifiable risk factor, current medical treatments are challenged by issues such as inadequate IOP control and ocular side effects. Rho kinase (ROCK) inhibitors have been developed as a novel pharmacologic class targeting the trabecular meshwork to enhance conventional aqueous humor outflow. In this review, the pharmacokinetics and IOP-lowering efficacy of key ROCK inhibitors are summarized. Beyond IOP reduction, ROCK inhibitors exhibit neuroprotective, anti-inflammatory, antifibrotic, and ocular perfusion-enhancing effects. Finally, we analyzed the limitations and future prospects of ROCK inhibitors in the management of glaucoma.

Glaucoma is a leading cause of irreversible blindness, with challenges persisting in early diagnosis, disease progression, and surgical outcome prediction. Recent advances in artificial intelligence have enabled significant progress by extracting clinically relevant patterns from structural, functional, and molecular data. This review outlines the current applications of artificial intelligence in glaucoma care, including early detection using fundus photography and OCT and disease progression prediction using deep learning architectures such as convolutional neural networks, recurrent neural networks, transformer models, generative adversarial networks, and autoencoders. Surgical outcome forecasting has been enhanced through multimodal models that integrate electronic health records and imaging data. We also highlight emerging AI applications in omics analysis, including transcriptomics and metabolomics, for biomarker discovery and individualized risk stratification. Despite these advances, key challenges remain in interpretability, integration of heterogeneous data, and the lack of personalized surgical timing guidance. Future work should focus on transparent, generalizable, and multimodal AI models, supported by large, well-curated datasets, to advance precision medicine in glaucoma.