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Every ophthalmic surgical supply, including intraocular lenses (IOLs), IOL cartridges, and ophthalmic viscosurgical device syringes, is packaged with instructions for use (IFU). These pamphlets are printed in multiple languages and, in the case of an IOL, significantly increase the size and weight of the packaging. To eliminate this significant and unnecessary source of waste, we recommend that manufacturers move to Quick Response codes that link to online electronic IFU (e-IFU) as a sensible alternative. In addition to reducing carbon emissions and manufacturing costs, e-IFU can be updated more easily and accessed by surgeons in the clinic, where IOL models and powers are selected. Varying and inconsistent IFU requirements between different countries are a barrier to wider adoption of e-IFU by the ophthalmic surgical industry. Regulatory agencies in every country should allow and encourage e-IFU. This position paper has been endorsed by the 3 major societies that sponsor EyeSustain, a consortium of global societies dedicated to advancing sustainability in ophthalmology., (Copyright © 2024 Published by Wolters Kluwer on behalf of ASCRS and ESCRS.)

As the field of ophthalmology has evolved in the last several decades, so has the gender distribution of ophthalmologists. We conducted a narrative review to further characterise the status of women in the realm of publication, presentations, editorial positions, grants, academic promotion, and financial compensation. While the proportion of women publishing, presenting, and filling academic and editorial roles has increased over time, it still does not match that of men. Women are more likely to be first authors instead of senior authors, have lower average h-indices, and are awarded fewer grants. The magnitude of some of these differences is smaller when adjusted for women's shorter career duration on average. Despite increased representation of women in ophthalmology, women continue to receive less compensation for the same work. This review highlights that more can be done to improve gender parity in ophthalmology., (© 2024 Royal Australian and New Zealand College of Ophthalmologists.)

Competing Interests: Im Folgenden sind die Interessenerklärungen als tabellarische Zusammenfassung dargestellt. Siehe Tab. 2 im Anhang.

This position article on reducing topical drug waste with ophthalmic surgery was written by the Ophthalmic Instrument Cleaning and Sterilization Task Force, comprising representatives of the ASCRS, American Academy of Ophthalmology, American Glaucoma Society, and Outpatient Ophthalmic Surgery Society. Drug waste significantly increases the costs and carbon footprint of ophthalmic surgery. Surgical facilities should be permitted to use topical drugs in multidose containers on multiple patients until the manufacturer's labeled date of expiration, if proper guidelines are followed. Surgical patients requiring a topical medication not used for other patients should be allowed to bring that partially used medication home for postoperative use. These recommendations are based on published evidence and clarification of policies from multiple regulatory and accrediting agencies with jurisdiction over surgical facilities. Surveys suggest that most ambulatory surgery centers and hospitals performing cataract surgery are wasting topical drugs unnecessarily., (Copyright © 2022 Published by Wolters Kluwer on behalf of ASCRS and ESCRS.)

Purpose: To conduct a bibliometric analysis of the 100 most cited publications on LASIK using the Scientific Information (ISI) Web of Knowledge database., Methods: This analysis used keyword-specific searches within the Web of Science database to isolate the 100 most frequently cited LASIK articles published between 1996 and 2019 (T100). Number of citations per article and per year were quantified from 1996 to 2019. Title, authors (as well as affiliated institutions and countries of origin), journal, year of publication, and citation frequency were variables analyzed., Results: Of the T100 articles, each article was cited between 103 to 411 times with a mean of 167 citations. Between 0-11 articles in the T100 were published every year on average with a median of 5 publications per year. The highest concentration of T100 publications occurred between 2003 and 2008 at 51%. A decrease in the annual publication rate of influential articles was observed after 2010 at 23%; 39.1% of these articles compared LASIK to newer refractive surgical approaches. The highest number of T100 articles were from the Journal of Refractive Surgery. The University of California System produced the highest number of T100 articles. The author with the most articles in the T100 is Dan Z. Reinstein. Most T100 articles originated from the United States., Conclusion: The peak of influential LASIK research occurred between 2000-2010, likely due to topics such as postprocedural corneal ectasia and the femtosecond laser approach. While newer surgical techniques such as SMILE may have contributed to the decline in the annual rate of LASIK-related publication, the underlying cause for this decline is unclear.

The 100 most cited papers on retinal detachment (RD) were analysed using a bibliographic study. The bibliographic databases of the ISI Web of Knowledge were searched, limited to research articles published between 1965 and 2020 in peer-reviewed journals. The papers were ranked in order of number of citations since publication. Ninety of the 100 most cited papers on RD were published in 12 ophthalmology journals, with 74 of them published in American Journal of Ophthalmology (n=31), Ophthalmology (n=23), Archives of Ophthalmology (n=10) and Investigative Ophthalmology and Visual Science (n=10); the remaining 10 papers were published in 8 journals from other fields of medical research. All papers in the top 100 were published in English. The 100 most cited papers on RD originated from 12 different countries, with the majority (72 papers) originating from the USA. The 100 identified papers represent a mix of clinical trials and animal/laboratory studies. This bibliographic study provides a unique perspective and insight into some of the most influential contributions in RD understanding and management over the last 55 years., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Worldwide, the incidence rate of myopia is maintained in a high level. Especially, the morbidity is rising continuously among children and adolescents. The progression of myopia affects visual acuity, vision related quality of life and productivity. Moreover, high myopia and its related ocular complications also aggravate the family and social burden. Therefore, the mechanism of myopia, related complications and methods of myopia prevention and control need further exploration. International Myopia Institute(IMI)published the second-edition white papers in April 2021. These white papers included reflections on the implications for clinical practice, the impact of myopia, the risk factors of myopia, the relationship among accommodation and binocular vision with myopia, pathologic myopia, prevention of myopia and digest. Comparing to the first edition, more than thousands of articles and conference abstracts were considered in white papers II, highlighting the latest research and progress related to myopia prevention and control. This article briefly summarizes and interprets the contents of the above white papers, including overview of myopia, impact of myopia, risk factors in myopia, ocular changes in the progress of myopia, and myopia prevention and control, hoping to provide advice for the clinical and scientific research work relating to myopia prevention and control.

Sihem Lazreg,1 Mohamed Hosny,2 Muhammad A Ahad,3 Mazen M Sinjab,4 Riadh Messaoud,5 Shady T Awwad,6 Antoine Rousseau7 1Ophthalmology Cabinet, Blida, Algeria; 2Refractive and Cornea Service, Cairo University Hospitals, Cairo, Egypt; 3Department of Ophthalmology, Anterior Segment Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 4Dr Sulaiman Al Habib Hospital, DHCC, Dubai, United Arab Emirates; 5Department of Ophthalmology, Tahar SFAR University Hospital, Mahdia, Tunisia; 6Department of Ophthalmology, American University of Beirut - Medical Center, Beirut, Lebanon; 7Department of Ophthalmology, Bicêtre Hospital, Paris-Saclay University, Le Kremlin-Bicêtre, FranceCorrespondence: Antoine Rousseau, Pierre Testas Building, Bicêtre Hospital, 78 Rue du Général Leclerc, Le Kremlin-Bicêtre, 94270, France, Tel +33145213690, Email arousseau1010@gmail.comAbstract: In the Middle East and Northern Africa (MENA), dry eye disease (DED) is often misdiagnosed or overlooked. This review summarizes a series of conversations with ophthalmologists in the region around a variety of climatic, lifestyle, and iatrogenic factors that contribute to specific features of DED in the MENA region. These considerations are further classified by patient lifestyle and surgical choices. All statements are based on discussions and formal voting to achieve consensus over three meetings. Overall, a deeper understanding of the disease characteristics of DED specific to MENA can better guide local eyecare practitioners on appropriate management and follow-up care. Additionally, population-based studies and patient and physician education on ocular surface diseases, together with the use of culturally appropriate and language-specific questionnaires can help ease the public health burden of DED in this region.Keywords: ocular surface, regional clinical practice, epidemiology, treatment, patient outcomes

AIM: To analyze research hotspots and trends of artificial intelligence in diabetic retinopathy(DR)based on bibliometrics and high-impact papers.METHODS: Papers on artificial intelligence in DR research published in the Web of Science Core Collection(WoSCC)from January 1, 2012, to December 31, 2022 were retrieved. The data was analyzed by CiteSpace software to examine annual publication number, countries, institutions, source journal, research categories, keywords, and to perform an in-depth analysis of high-impact papers.RESULTS: A total of 1 009 papers on artificial intelligence in DR from 79 countries were included in the study, with 272 papers published in 2022. Notably, China and India contributed 287 and 234 papers, respectively. The United Kingdom exhibited a centrality score of 0.31, while the United States boasted an impressive H-index of 48. Three prominent institutions in the United Kingdom(University of London, Moorfields Eye Hospital, and University College London)and one institution in Egypt(Egyptian Knowledge Bank)all achieved a notable H-index of 14. The primary academic disciplines associated with this research field encompassed ophthalmology, computer science, and artificial intelligence. Burst keywords in the years 2021～2022 included transfer learning, vessel segmentation, and convolutional neural networks.CONCLUSION: China emerged as the leading contributor in terms of publication number in this field, while the United States stood out as a key player. Notably, Egyptian Knowledge Bank and University of London assumed leading roles among research institutions. Additionally, IEEE Access was identified as the most active journal within this domain. The research focus in the field of artificial intelligence in DR has transitioned from AI applications in disease detection and grading to a more concentrated exploration of AI-assisted diagnostic systems. Transfer learning, vessel segmentation, and convolutional neural networks hold substantial promise for widespread applications in this field.

Purpose: To study cases of hardware-associated secondary acquired lacrimal duct obstructions (SALDO) and the role of computed tomography dacryocystography (CT-DCG) scans in its diagnosis and management. Observations: Retrospective, interventional case review of four patients diagnosed as Hardware-associated SALDO, with primary maxillofacial repair performed elsewhere, were analyzed. The mean age was 36.5 years (range: 22–74 years), three of them being males. Left and right lacrimal systems were equally involved. Epiphora, swelling and discharge were the main presenting features. Three lacrimal sacs and nasolacrimal ducts on CT-DCG showed the screws of the orbital fracture plate directly piercing their walls, whereas a single case showed the sac displaced and pierced by the medial side of the orbital floor implant. Two cases underwent dacryocystorhinostomy with intubation, and the remaining two had to undergo dacryocystectomy due to extensive damage. Post-operatively all four cases were doing well at a mean follow-up of 2 months. Conclusions: The present series highlights the role of CT-DCG in delineating spatial relationship of lacrimal drainage system with the surrounding structures, facilitating planning as well as choice of surgery, and anticipating the intraoperative challenges. It also signifies importance of interdisciplinary coordination between oculoplastic and maxillofacial surgeons to avoid iatrogenic trauma to the lacrimal drainage system.

Purpose: To study the emerging trend of development of secondary acquired nasolacrimal duct obstruction (SALDO) in the cases treated for rhino-orbito-cerebral mucormycosis (ROCM). Observations: Prospective, interventional case series of five patients who developed SALDO post-surgical and medical management of ROCM. The mean age was 45.4 years (range: 40–62 years), all five being males. Right lacrimal drainage pathways was involved slightly more than the left (right:left = 3:2). Epiphora and discharge were the main presenting features. All five patients were treated with extensive debridement of the nose, sinuses, orbit and cerebral involvement as needed followed by medical management for ROCM. CT- Dacryocystography for all 5 patients showed obstruction at the lower end of the nasolacrimal duct. The patients underwent external dacryocystorhinostomy with mitomycin-C with or without intubation with good anatomical and functional outcomes at 6 months follow-up. Conclusions and importance: The present series highlights the possible etiology of development of SALDO in cases treated for ROCM, its management and discusses the role of Computed Tomography Dacryocystography (CT-DCG) in understanding the pathophysiology of the development of SALDO along with delineating the spatial relationship of the lacrimal drainage system with the surrounding structures.

The electronic medical record management system plays a crucial role in clinical practice, optimizing the recording and management of healthcare data. To enhance the functionality of the medical record management system, this paper develops a customized schema designed for ophthalmic diseases. A multi-modal knowledge graph is constructed, which is built upon expert-reviewed and de-identified real-world ophthalmology medical data. Based on this data, we propose an auxiliary diagnostic model based on a contrastive graph attention network (CGAT-ADM), which uses the patient's diagnostic results as anchor points and achieves auxiliary medical record diagnosis services through graph clustering. By implementing contrastive methods and feature fusion of node types, text, and numerical information in medical records, the CGAT-ADM model achieved an average precision of 0.8563 for the top 20 similar case retrievals, indicating high performance in identifying analogous diagnoses. Our research findings suggest that medical record management systems underpinned by multimodal knowledge graphs significantly enhance the development of AI services. These systems offer a range of benefits, from facilitating assisted diagnosis and addressing similar patient inquiries to delving into potential case connections and disease patterns. This comprehensive approach empowers healthcare professionals to garner deeper insights and make well-informed decisions., (© 2024. The Author(s).)

There is a growing number of publicly available ophthalmic imaging datasets and open-source code for Machine Learning algorithms. This allows ophthalmic researchers and practitioners to independently perform various deep-learning tasks. With the advancement in artificial intelligence (AI) and in the field of imaging, the choice of the most appropriate AI architecture for different tasks will vary greatly. The best-performing AI-dataset combination will depend on the specific problem that needs to be solved and the type of data available. The article discusses different machine learning models and deep learning architectures currently used for various ophthalmic imaging modalities and for different machine learning tasks. It also proposes the most appropriate models based on accuracy and other important factors such as training time, the ability to deploy the model on clinical devices/smartphones, heatmaps that enhance the self-explanatory nature of classification decisions, and the ability to train/adapt on small image datasets to determine if further data collection is worthwhile. The article extensively reviews the existing state-of-the-art AI methods focused on useful machine-learning applications for ophthalmology. It estimates their performance and viability through training and evaluating architectures with different public and private image datasets of different modalities, such as full-color retinal images, OCT images, and 3D OCT scans. The article is expected to benefit the readers by enriching their knowledge of artificial intelligence applied to ophthalmology., (© 2024. The Author(s).)

Manoj Motwani Cornea Revolution/Motwani LASIK Institute, San Diego, CA, 92121, USACorrespondence: Manoj Motwani, Cornea Revolution/Motwani LASIK Institute, 9710 Scranton Road, Suite 170, San Diego, CA, 92121, USA, Tel +1 858 554-0008, Email drmmlj@gmail.com

Majid Moshirfar,1–3 Joshua S Theis,4 David S Cha,5 Kaiden B Porter,4 Carter J Payne,1,6 Phillip C Hoopes1 1Hoopes Vision Research Center, Hoopes Vision, Draper, UT, USA; 2John A. Moran Eye Center, University of Utah, School of Medicine, Salt Lake City, UT, USA; 3Utah Lions Eye Bank, Murray, UT, USA; 4University of Arizona College of Medicine Phoenix, Phoenix, AZ, USA; 5Saint Louis University, School of Medicine, Saint Louis, MO, USA; 6Department of Ophthalmology, George Washington University School of Medicine and Health Sciences, Washington, DC, USACorrespondence: Majid Moshirfar, Hoopes Vision Research Center, 11820 S. State St. #200, Draper, UT, 84020, USA, Tel +1 801 568 – 0200, Fax +1 415-476-0336, Email cornea2020@me.com

This study examines the impact of social insurance benefit restrictions on physician behaviour, using ophthalmologists as a case study. We examine whether ophthalmologists use their market power to alter their fees and rebates across services to compensate for potential policy-induced income losses. The results show that ophthalmologists substantially reduced their fees and rebates for services directly targeted by the benefit restriction compared to other medical specialists' fees and rebates. There is also some evidence that they increased their fees for services that were not targeted. High-fee charging ophthalmologists exhibited larger fee and rebate responses while the low-fee charging group raise their rebates to match the reference price provided by the policy environment., (© 2024 The Authors. Health Economics published by John Wiley & Sons Ltd.)

Background: Patient education in ophthalmology poses a challenge for physicians because of time and resource limitations. ChatGPT (OpenAI, San Francisco) may assist with automating production of patient handouts on common neuro-ophthalmic diseases., Methods: We queried ChatGPT-3.5 to generate 51 patient education handouts across 17 conditions. We devised the "Quality of Generated Language Outputs for Patients" (QGLOP) tool to assess handouts on the domains of accuracy/comprehensiveness, bias, currency, and tone, each scored out of 4 for a total of 16. A fellowship-trained neuro-ophthalmologist scored each passage. Handout readability was assessed using the Simple Measure of Gobbledygook (SMOG), which estimates years of education required to understand a text., Results: The QGLOP scores for accuracy, bias, currency, and tone were found to be 2.43, 3, 3.43, and 3.02 respectively. The mean QGLOP score was 11.9 [95% CI 8.98, 14.8] out of 16 points, indicating a performance of 74.4% [95% CI 56.1%, 92.5%]. The mean SMOG across responses as 10.9 [95% CI 9.36, 12.4] years of education., Conclusions: The mean QGLOP score suggests that a fellowship-trained ophthalmologist may have at-least a moderate level of satisfaction with the write-up quality conferred by ChatGPT. This still requires a final review and editing before dissemination. Comparatively, the rarer 5% of responses collectively on either extreme would require very mild or extensive revision. Also, the mean SMOG score exceeded the accepted upper limits of grade 8 reading level for health-related patient handouts. In its current iteration, ChatGPT should be used as an efficiency tool to generate an initial draft for the neuro-ophthalmologist, who may then refine the accuracy and readability for a lay readership., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 by North American Neuro-Ophthalmology Society.)

Prcis: This study demonstrated that the compliance levels with International Council of Ophthalmology (ICO) Guidelines for glaucoma eye care were low for all the elements in both public and private health care settings., Purpose: To determine the compliance with the ICO guidelines for glaucoma eye care among Pakistani ophthalmologists and to compare differences among ophthalmologists practicing in public and private health care settings., Materials and Methods: This was a retrospective chart review, and the records were reviewed according to ICO guidelines. The ICO recommends that each patient with glaucoma be evaluated for 19 items from 3 elements which are history, examination, and investigations. Mean compliance was recorded for each of the 3 elements. The compliance of each item was also checked and then a compared between the 2 settings, that is, public and private health care settings., Results: A total of 394 records were analyzed, with a mean age of 51.9±14.9 years and 232 (58.9%) male patients. Most records were from private settings 339 (86%), and primary open angle glaucoma 163 (41.4%) was the most common diagnosis. Compliance was low for all elements; history (31.8%), examination (61.3%), and investigation (6%). Pupil reaction differed significantly between the 2 groups ( P =0.001)., Conclusion: Pakistan's ophthalmologists, whether in public or private health care settings, lack knowledge of ICO guidelines for glaucoma eye care. This study emphasizes the importance of implementing these guidelines in the general ophthalmology curriculum., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose of Review: The purpose of this review is to evaluate the current state of eco-sustainability in ophthalmology, highlighting key practices, recent advancements, and areas requiring improvement. This review aims to provide ophthalmologists with a comprehensive overview of sustainable practices that can reduce environmental impact., Recent Findings: Recent studies have identified several areas within ophthalmology where sustainable practices can be implemented including multidose eyedrops, adjusting surgical packs, making package inserts available electronically, and reusing surgical instruments. Moreover, there is an increasing emphasis on waste reduction both in the surgical and clinical setting, by decreasing the use of unnecessary materials and implementing more efficient use of recycling programs. Telemedicine has also emerged as a sustainable option, reducing the carbon footprint associated with patient travel. Despite these advancements, significant challenges remain, particularly in balancing the cost and accessibility of sustainable options with traditional practices., Summary: Eco-sustainability in ophthalmology is gaining momentum as the medical community aims to reduce its environmental impact. While progress has been made, further efforts are required to overcome financial and logistical barriers to widespread implementation. Continued research, education, and policy development are essential to advancing eco-sustainable practices, ensuring that environmental considerations become an integral part of ophthalmic care., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The aim of this study was to bibliometrically analyze the 100 most-cited articles published in the Veterinary Ophthalmology (VO) journal., Methods: Web of Science was searched for citations of VO articles published in 1998-2022. Tissue and species studied, and first and last author domicile and affiliation were recorded for the 100 most-cited articles and descriptively analyzed., Results: Altogether, the 100 most-cited VO articles have cited a total of 5483 times. Most commonly, these were devoted to the cornea (23%), multiple tissues (19%), and glaucoma (16%). Studies on dogs (36%), horses (17%), and multiple species (15%) were most often cited. Most first/last authors were from the USA (n = 113), Brazil (n = 13), and France and Germany (n = 7 each), and most frequently affiliated with the University of Florida (n = 36), University of Wisconsin-Madison (n = 15), and Animal Health Trust, North Carolina State University, and Ohio State University (n = 6 each). KN Gelatt (n = 9), DE Brooks (n = 6), and FJ Ollivier and EO MacKay (n = 5 each) were the most frequent first or last authors. The greatest number of citations was for articles with KN Gelatt (n = 555), FJ Ollivier (n = 411), and DE Brooks (n = 372) as first or last authors. "The comparative morphology of the tapetum lucidum" by FJ Ollivier et al. (2002) is the most frequently cited article in VO history (n = 178)., Conclusions: This study provides insight into the impact of publishing in VO and a more comprehensive understanding of trends and the most influential contributions to VO., (© 2023 The Authors. Veterinary Ophthalmology published by Wiley Periodicals LLC on behalf of American College of Veterinary Ophthalmologists.)

Artificial neural networks (ANN) are artificial intelligence (AI) techniques used in the automated recognition and classification of pathological changes from clinical images in areas such as ophthalmology, dermatology, and oral medicine. The combination of enterprise imaging and AI is gaining notoriety for its potential benefits in healthcare areas such as cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, and endoscopic. The present study aimed to analyze, through a systematic literature review, the application of performance of ANN and deep learning in the recognition and automated classification of lesions from clinical images, when comparing to the human performance. The PRISMA 2020 approach (Preferred Reporting Items for Systematic Reviews and Meta-analyses) was used by searching four databases of studies that reference the use of IA to define the diagnosis of lesions in ophthalmology, dermatology, and oral medicine areas. A quantitative and qualitative analyses of the articles that met the inclusion criteria were performed. The search yielded the inclusion of 60 studies. It was found that the interest in the topic has increased, especially in the last 3 years. We observed that the performance of IA models is promising, with high accuracy, sensitivity, and specificity, most of them had outcomes equivalent to human comparators. The reproducibility of the performance of models in real-life practice has been reported as a critical point. Study designs and results have been progressively improved. IA resources have the potential to contribute to several areas of health. In the coming years, it is likely to be incorporated into everyday life, contributing to the precision and reducing the time required by the diagnostic process., (© 2023. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

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Purpose: With the introduction of ChatGPT, artificial intelligence (AI)-based large language models (LLMs) are rapidly becoming popular within the scientific community. They use natural language processing to generate human-like responses to queries. However, the application of LLMs and comparison of the abilities among different LLMs with their human counterparts in ophthalmic care remain under-reported., Recent Findings: Hitherto, studies in eye care have demonstrated the utility of ChatGPT in generating patient information, clinical diagnosis and passing ophthalmology question-based examinations, among others. LLMs' performance (median accuracy, %) is influenced by factors such as the iteration, prompts utilised and the domain. Human expert (86%) demonstrated the highest proficiency in disease diagnosis, while ChatGPT-4 outperformed others in ophthalmology examinations (75.9%), symptom triaging (98%) and providing information and answering questions (84.6%). LLMs exhibited superior performance in general ophthalmology but reduced accuracy in ophthalmic subspecialties. Although AI-based LLMs like ChatGPT are deemed more efficient than their human counterparts, these AIs are constrained by their nonspecific and outdated training, no access to current knowledge, generation of plausible-sounding 'fake' responses or hallucinations, inability to process images, lack of critical literature analysis and ethical and copyright issues. A comprehensive evaluation of recently published studies is crucial to deepen understanding of LLMs and the potential of these AI-based LLMs., Summary: Ophthalmic care professionals should undertake a conservative approach when using AI, as human judgement remains essential for clinical decision-making and monitoring the accuracy of information. This review identified the ophthalmic applications and potential usages which need further exploration. With the advancement of LLMs, setting standards for benchmarking and promoting best practices is crucial. Potential clinical deployment requires the evaluation of these LLMs to move away from artificial settings, delve into clinical trials and determine their usefulness in the real world., (© 2024 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.)

Objectives: To compare the performance of a composite citation score (c-score) and its six constituent citation indices, including H-index, in predicting winners of the Weisenfeld Award in ophthalmologic research. Secondary objectives were to explore career and demographic characteristics of the most highly cited researchers in ophthalmology., Methods: A publicly available database was accessed to compile a set of top researchers in the field of clinical ophthalmology and optometry based on Scopus data from 1996 to 2021. Each citation index was used to construct a multivariable model adjusted for author demographic characteristics. Using area under the receiver operating curve (AUC) analysis, each index's model was evaluated for its ability to predict winners of the Weisenfeld Award in Ophthalmology, a research distinction presented by the Association for Research in Vision and Ophthalmology (ARVO). Secondary analyses investigated authors' self-citation rates, career length, gender, and country affiliation over time., Results: Approximately one thousand unique authors publishing primarily in clinical ophthalmology/optometry were analyzed. The c-score outperformed all other citation indices at predicting Weisenfeld Awardees, with an AUC of 0.99 (95% CI: 0.97-1.0). The H-index had an AUC of 0.89 (95% CI: 0.83-0.96). Authors with higher c-scores tended to have longer career lengths and similar self-citation rates compared to other authors. Sixteen percent of authors in the database were identified as female, and 64% were affiliated with the United States of America., Conclusion: The c-score is an effective metric for assessing research impact in ophthalmology, as seen through its ability to predict Weisenfeld Awardees., (© 2024. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)