Aim To report on outcomes of gonioscopy-assisted transluminal trabeculotomy (GATT) in eyes with pseudoexfoliative glaucoma (PXG). Methods Prospective, interventional, non-comparative case series. A total of 103 eyes from 84 patients with PXG were enrolled to undergo a 360-degree ab interno trabeculotomy with gonioscopic assistance using either a 5.0 polypropylene suture or an illuminated microcatheter with up to 24 months of follow-up. Main outcome measures were intraocular pressure (IOP), number of antiglaucoma medications, success rate (IOP reduction ≥20% from baseline or IOP between 6 and 21 mm Hg, without further glaucoma surgery) and complication rate. Results Mean preoperative IOP was 27.1 mm Hg (95% CI 25.5 to 28.7) using 2.9 (SD 1.1) glaucoma medications which decreased postoperatively to 13.0 mm Hg (95% CI 11.5 to 14.4) and 1.0 (SD 1.1) medications at 24 months (p<0.001). Success rate was 89.2% at 24 months of follow-up, and complication rate was 2.9%. Conclusion At 24 months of follow-up, our results for GATT in PXG demonstrate that this conjunctival sparing procedure effectively lowers IOP and reduces the medications with a low complication rate, in this relatively aggressive glaucoma subtype.

Despite significant recent advances in artificial intelligence (AI) technology within several ophthalmic subspecialties, AI seems to be underutilized in the diagnosis and management of cataracts. In this article, we review AI technology that may soon become central to the cataract surgical pathway, from diagnosis to completion of surgery. This review describes recent advances in AI in the preoperative, intraoperative, and postoperative phase of cataract surgery, demonstrating its impact on the pathway and the surgical team. A systematic search of PubMed was conducted to identify relevant publications on the topic of AI for cataract surgery. Articles of high quality and relevance to the topic were selected. Before surgery, diagnosis and grading of cataracts through AI-based image analysis has been demonstrated in several research settings. Optimal intraocular lens (IOL) power to achieve the desired postoperative refraction can be calculated with a higher degree of accuracy using AI-based modeling compared with traditional IOL formulae. During surgery, innovative AI-based video analysis tools are in development, promoting a paradigm shift for documentation, storage, and cataloging libraries of surgical videos with applications for teaching and training, complication review, and surgical research. Situation-aware computer-assisted devices can be connected to surgical microscopes for automated video capture and cloud storage upload. Artificial intelligence-based software can provide workflow analysis, tool detection, and video segmentation for skill evaluation by the surgeon and the trainee. Mixed reality features, such as real-time intraoperative warnings, may have a role in improving surgical decision-making with the key aim of reducing complications by recognizing surgical risks in advance and alerting the operator to them. For the management of patient flow through the pathway, AI-based mathematical models generating patient referral patterns are in development, as are simulations to optimize operating room use. In the postoperative phase, AI has been shown to predict the posterior capsule status with reasonable accuracy, and can therefore improve the triage pathway in the treatment of posterior capsular opacification. Artificial intelligence for cataract surgery will be as relevant as in other subspecialties of ophthalmology and will eventually constitute a future cornerstone for an enhanced cataract surgery pathway.

Background/Objectives: The pathological changes preceding the onset of Parkinson’s disease (PD) commence several decades before motor symptoms manifest, offering a potential window for identifying objective biomarkers for early diagnosis and disease monitoring. Among the primary non-motor features of PD is autonomic dysfunction; however, its precise assessment remains challenging, limiting its viability as a reliable biomarker. Both the pupillary light reflex (PLR) and pupillary unrest are regulated by autonomic pathways suggesting their potential as objective non-invasive indicators of the PD prodromal phase. This review systematically evaluates studies that compare PLR and pupillary unrest in individuals with PD and healthy controls to determine their utility as potential biomarkers of the disease. Methods: A systematic search strategy was designed to identify studies reporting PLR and pupillary unrest findings in PD patients. Searches were conducted across three databases (MEDLINE, Embase PsycINFO), supplemented by cross-referencing relevant studies found on Google Scholar. The literature search was last updated on 7 December 2020. Pupillometric parameters that permitted statistical synthesis included maximum constriction velocity (VMax), constriction amplitude (CAmp), and constriction latency (CL). Pooled incidence and effect sizes were determined using a random-effects model with an inverse variance DerSimonian–Laird estimator. The I² statistic was used to assess study heterogeneity. When meta-analysis was not feasible, a qualitative analysis was undertaken. Results: The initial search yielded 219 references. Following deduplication and exclusion of ineligible studies, 31 papers were selected for review. Pupillometric data from 11 studies were incorporated into the meta-analysis. Effect sizes for PD patients were significant for VMax −0.92, (p < 0.01), CAmp −0.58, (p < 0.05), and CL 0.46, (p < 0.05). Measures of pupillary unrest were elevated in PD patients compared to controls, but evidence was limited to two studies. Conclusions: Pupillary constriction in response to light is characterised by reduced speed and amplitude in PD, with effect sizes suggesting potential clinical applicability. However, evidence regarding baseline pupillary variability remains insufficient, underlining the necessity for further research. Pupillary metrics represent a promising avenue for early PD detection, though their clinical utility is constrained by methodological heterogeneity and variations in disease duration among studies.

Human Immunodeficiency Virus (HIV) remains a significant global health challenge with approximately 38 million people currently having the virus worldwide. Despite advances in treatment development, the virus persists in the human population and still leads to new infections. The virus has a powerful ability to mutate and hide from the human immune system in reservoirs of the body. Current standard treatment with antiretroviral therapy effectively controls viral replication but requires lifelong adherence and does not eradicate the virus. This review explores the potential of Advanced Therapy Medicinal Products as novel therapeutic approaches to HIV, including cell therapy, immunisation strategies and gene therapy. Cell therapy, particularly chimeric antigen receptor T cell therapy, shows promise in preclinical studies for targeting and eliminating HIV-infected cells. Immunisation therapies, such as broadly neutralising antibodies are being investigated to control viral replication and reduce reservoirs. Despite setbacks in recent trials, vaccines remain a promising avenue for HIV therapy development. Gene therapy using technologies like CRISPR/Cas9 aims to modify cells to resist HIV infection or eliminate infected cells. Challenges such as off-target effects, delivery efficiency and ethical considerations persist in gene therapy for HIV. Future directions require further research to assess the safety and efficacy of emerging therapies in clinical trials. Combined approaches may be necessary to achieve complete elimination of the HIV reservoir. Overall, advanced therapies offer new hope for advancing HIV treatment and moving closer to a cure.

Key Messages Efforts to increase access to surgical care will achieve improved health outcomes only if those efforts are intertwined with efforts to increase surgical safety and quality. The World Health Organization Surgical Safety Checklist and Non-Technical Skills for Surgeons (NOTSS) framework are 2 tools to increase surgery quality and safety. The NOTSS for variable resource contexts is a new 1-day educational course developed in Rwanda that integrates contextually appropriate behaviors and values and can be implemented with low costs in any health care context. Program managers should provide context-specific NOTSS training for surgeons and operating theater staff. Policy makers should implement NOTSS framework into health care policy focusing on modern virtual teaching methods. Surgeons and operating theater staff should be familiar with the NOTSS framework and regularly update their knowledge through didactic courses, simulation, and online trainings.