This study aimed to examine the association between chronic kidney disease (CKD) and glaucoma in large-scale health checkup data in Japan.
Design
Retrospective cross-sectional study.
Methods
The dataset consisted of 23,761 eyes of 12,020 subjects in two regions in Japan (Hamamatsu City and Shimane Prefecture). Subsequently, the associations between glaucoma and CKD, CKD stage, and estimated glomerular filtration rate (eGFR) were investigated using the linear mixed model, with adjustment for age, sex, hypertension, diabetes, lipidemia, body mass index, smoking status, and intraocular pressure (IOP), using each data set. Similarly, the association between IOP and CKD, CKD stage, and eGFR was also investigated.
Results
The prevalence of glaucoma was 4.5%. The mean age of those with glaucoma or suspected glaucomatous optic neuropathy was older (58.6 years old) than those without (53.6 years old) in the datasets. In this dataset showed no significant association was found between glaucoma or suspected glaucomatous optic neuropathy and CKD, stage of kidney function, and eGFR (P > 0.05). However, a significant association was found between IOP and CKD (β = − 0.71 [95% CI: −1.30 to −0.13] mmHg, p = 0.016), and eGFR (per 10 mL/min/1.73 m²: β = 0.064 [95% CI: +0.012 to +0.12] mmHg, p = 0.016).
Conclusions
The current study with a large-scale health screening program in Japan suggested no association between CKD/renal function and glaucoma or suspected glaucomatous optic neuropathy.
{"title":"Is renal function associated with glaucoma or suspected glaucomatous optic neuropathy -Findings from health screening data in Japan","authors":"Risa Nakazawa , Ryo Asaoka , Shigeki Muto , Hiroshi Murata , Kazunobu Sugihara , Kaori Ishii , Akira Obana , Masaki Tanito","doi":"10.1016/j.ajoint.2025.100195","DOIUrl":"10.1016/j.ajoint.2025.100195","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to examine the association between chronic kidney disease (CKD) and glaucoma in large-scale health checkup data in Japan.</div></div><div><h3>Design</h3><div>Retrospective cross-sectional study.</div></div><div><h3>Methods</h3><div>The dataset consisted of 23,761 eyes of 12,020 subjects in two regions in Japan (Hamamatsu City and Shimane Prefecture). Subsequently, the associations between glaucoma and CKD, CKD stage, and estimated glomerular filtration rate (eGFR) were investigated using the linear mixed model, with adjustment for age, sex, hypertension, diabetes, lipidemia, body mass index, smoking status, and intraocular pressure (IOP), using each data set. Similarly, the association between IOP and CKD, CKD stage, and eGFR was also investigated.</div></div><div><h3>Results</h3><div>The prevalence of glaucoma was 4.5%. The mean age of those with glaucoma or suspected glaucomatous optic neuropathy was older (58.6 years old) than those without (53.6 years old) in the datasets. In this dataset showed no significant association was found between glaucoma or suspected glaucomatous optic neuropathy and CKD, stage of kidney function, and eGFR (P > 0.05). However, a significant association was found between IOP and CKD (β = − 0.71 [95% CI: −1.30 to −0.13] mmHg, p = 0.016), and eGFR (per 10 mL/min/1.73 m²: β = 0.064 [95% CI: +0.012 to +0.12] mmHg, p = 0.016).</div></div><div><h3>Conclusions</h3><div>The current study with a large-scale health screening program in Japan suggested no association between CKD/renal function and glaucoma or suspected glaucomatous optic neuropathy.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-27DOI: 10.1016/j.ajoint.2025.100194
Luis Filipe Nakayama , Lucas Zago Ribeiro , Cindy Lie Tabuse , Fernando Korn Malerbi , Caio Regatieri
Purpose: To evaluate and compare commercially available portable retinal cameras with a focus on technical specifications, clinical applications, and the integration of artificial intelligence (AI) for ophthalmic screening, especially in low- and middle-income countries (LMICs). Design: Systematic review of the literature. Methods: Systematic searches of PubMed and OpenAlex were conducted up to September 2025, without language restrictions, using terms such as portable retinal camera, handheld retinal camera, and smartphone-based fundus camera. Devices were included if they were commercially available and described in peer-reviewed publications with technical or clinical data. Prototypes and systems relying solely on external smartphone lenses without integrated optics were excluded. Data extracted included imaging specifications, ergonomics, power sources, AI functionalities, quality control features, and reported clinical applications. Devices were categorized as smartphone-attached or standalone handheld systems. Results: The search retrieved 870 records (PubMed = 277; OpenAlex = 593). After removing duplicates and screening, 509 articles were included in the review, collectively reporting on 38 portable retinal cameras, of which 17 were commercially available. The most frequently reported devices were the Volk Pictor Plus, Phelcom Eyer, Optomed Aurora, ZEISS VISUSCOUT 100, and Remidio FOP. Smartphone attached systems offered greater portability and affordability, whereas standalone handheld systems provided integrated functionality, higher imaging stability, and smoother clinical integration. AI features varied across devices, encompassing referable diabetic retinopathy detection, abnormality triage, systemic risk prediction, and automated image-quality assessment. Clinical applications extended beyond diabetic retinopathy and retinopathy of prematurity to include glaucoma, AMD, and exploratory use in systemic conditions such as sepsis and COVID-19. Conclusion: Portable retinal cameras already demonstrate clear utility in extending ophthalmic screening and diagnostic services, particularly for diabetic retinopathy and retinopathy of prematurity, while also showing potential in broader clinical and systemic applications. Their portability and cost-effectiveness make them valuable for outreach and telemedicine programs, especially in LMICs. The integration of artificial intelligence further enhances their functionality, though variability in device design, regional availability, and regulatory status highlights the need for standardized validation, recurring local assessments, and head-to-head comparative studies. Real-world evaluations remain essential to ensure effective, safe, and equitable deployment.
{"title":"A comprehensive review of portable retinal cameras: Technical features, ai integration, and clinical potential","authors":"Luis Filipe Nakayama , Lucas Zago Ribeiro , Cindy Lie Tabuse , Fernando Korn Malerbi , Caio Regatieri","doi":"10.1016/j.ajoint.2025.100194","DOIUrl":"10.1016/j.ajoint.2025.100194","url":null,"abstract":"<div><div>Purpose: To evaluate and compare commercially available portable retinal cameras with a focus on technical specifications, clinical applications, and the integration of artificial intelligence (AI) for ophthalmic screening, especially in low- and middle-income countries (LMICs). Design: Systematic review of the literature. Methods: Systematic searches of PubMed and OpenAlex were conducted up to September 2025, without language restrictions, using terms such as portable retinal camera, handheld retinal camera, and smartphone-based fundus camera. Devices were included if they were commercially available and described in peer-reviewed publications with technical or clinical data. Prototypes and systems relying solely on external smartphone lenses without integrated optics were excluded. Data extracted included imaging specifications, ergonomics, power sources, AI functionalities, quality control features, and reported clinical applications. Devices were categorized as smartphone-attached or standalone handheld systems. Results: The search retrieved 870 records (PubMed = 277; OpenAlex = 593). After removing duplicates and screening, 509 articles were included in the review, collectively reporting on 38 portable retinal cameras, of which 17 were commercially available. The most frequently reported devices were the Volk Pictor Plus, Phelcom Eyer, Optomed Aurora, ZEISS VISUSCOUT 100, and Remidio FOP. Smartphone attached systems offered greater portability and affordability, whereas standalone handheld systems provided integrated functionality, higher imaging stability, and smoother clinical integration. AI features varied across devices, encompassing referable diabetic retinopathy detection, abnormality triage, systemic risk prediction, and automated image-quality assessment. Clinical applications extended beyond diabetic retinopathy and retinopathy of prematurity to include glaucoma, AMD, and exploratory use in systemic conditions such as sepsis and COVID-19. Conclusion: Portable retinal cameras already demonstrate clear utility in extending ophthalmic screening and diagnostic services, particularly for diabetic retinopathy and retinopathy of prematurity, while also showing potential in broader clinical and systemic applications. Their portability and cost-effectiveness make them valuable for outreach and telemedicine programs, especially in LMICs. The integration of artificial intelligence further enhances their functionality, though variability in device design, regional availability, and regulatory status highlights the need for standardized validation, recurring local assessments, and head-to-head comparative studies. Real-world evaluations remain essential to ensure effective, safe, and equitable deployment.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100194"},"PeriodicalIF":0.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To present the clinical characteristics, management and outcomes of glaucoma following congenital cataract surgery with primary intraocular lens (IOL) implantation.
Design
Retrospective, monocentric consecutive case series
Methods
We included patients with glaucoma following congenital cataract surgery and IOL implantation before the age of one year. Therapeutic success was defined as intraocular pressure (IOP) <21 mmHg at last follow-up without sight threatening complications, with or without medication.
Results
Sixty-one eyes of 42 patients were included. Mean age at cataract surgery was 121.4 ± 82.1 days. The mean interval between cataract surgery and glaucoma diagnosis was 3.9 ± 3.9 years. During follow-up, 34 eyes were treated medically (55 %) while 27 (45 %) needed surgery. The glaucoma surgeries included: trabeculectomy in 17 eyes, laser diode in 14 eyes, Ahmed glaucoma valve in 6 eyes and MicroShunt PRESERFLO in 2 eyes. Glaucoma was treated successfully in 48 eyes (80 %). Need for glaucoma surgery was associated with: early cataract surgery (p = 0.02), early glaucoma diagnosis (p = 0.04), use of trypan blue (p = 0.03) and associated anomalies (p = 0.01). BCVA at last follow-up was worse in eyes undergoing surgery than eyes receiving medical treatment (1.4 ± 1.0 vs. 0.63±0.57 logMAR, p = 0.001).
Conclusion
Eyes that underwent cataract surgery earlier and eyes associated with other anomalies were more likely to require surgery. The earlier glaucoma developed after cataract surgery, the more likely surgery was needed in the follow-up. Age at cataract surgery and time to glaucoma diagnosis did not affect surgical success. However, visual prognosis remains poor despite IOP control.
{"title":"Clinical characteristics and management of glaucoma following congenital cataract surgery and IOL implantation","authors":"Aïda Lachelah , Thibaut Chapron , Ismael Chehaibou , Florence Metge , Pascal Dureau , Georges Caputo , Youssef Abdelmassih","doi":"10.1016/j.ajoint.2025.100193","DOIUrl":"10.1016/j.ajoint.2025.100193","url":null,"abstract":"<div><h3>Purpose</h3><div>To present the clinical characteristics, management and outcomes of glaucoma following congenital cataract surgery with primary intraocular lens (IOL) implantation.</div></div><div><h3>Design</h3><div>Retrospective, monocentric consecutive case series</div></div><div><h3>Methods</h3><div>We included patients with glaucoma following congenital cataract surgery and IOL implantation before the age of one year. Therapeutic success was defined as intraocular pressure (IOP) <21 mmHg at last follow-up without sight threatening complications, with or without medication.</div></div><div><h3>Results</h3><div>Sixty-one eyes of 42 patients were included. Mean age at cataract surgery was 121.4 ± 82.1 days. The mean interval between cataract surgery and glaucoma diagnosis was 3.9 ± 3.9 years. During follow-up, 34 eyes were treated medically (55 %) while 27 (45 %) needed surgery. The glaucoma surgeries included: trabeculectomy in 17 eyes, laser diode in 14 eyes, Ahmed glaucoma valve in 6 eyes and MicroShunt PRESERFLO in 2 eyes. Glaucoma was treated successfully in 48 eyes (80 %). Need for glaucoma surgery was associated with: early cataract surgery (<em>p</em> = 0.02), early glaucoma diagnosis (<em>p</em> = 0.04), use of trypan blue (<em>p</em> = 0.03) and associated anomalies (<em>p</em> = 0.01). BCVA at last follow-up was worse in eyes undergoing surgery than eyes receiving medical treatment (1.4 ± 1.0 vs. 0.63±0.57 logMAR, <em>p</em> = 0.001).</div></div><div><h3>Conclusion</h3><div>Eyes that underwent cataract surgery earlier and eyes associated with other anomalies were more likely to require surgery. The earlier glaucoma developed after cataract surgery, the more likely surgery was needed in the follow-up. Age at cataract surgery and time to glaucoma diagnosis did not affect surgical success. However, visual prognosis remains poor despite IOP control.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-25DOI: 10.1016/j.ajoint.2025.100190
Ha-Neul Yu , Jocelyn He , Benjamin Kim , Gui-Shuang Ying
Purpose
While diabetic retinopathy (DR) has previously been linked to neurodegenerative diseases, it remains unclear whether DR independently reflects neurodegenerative diseases beyond those attributable to diabetes itself. In this study, we leveraged data from the All of Us Research Program to assess whether DR serves as an independent marker of neurodegenerative disease among individuals with diabetes.
Methods
A matched case-control, cross-sectional study was conducted using data from the All of Us Research Program (US-based EHR database). Three groups (exactly matched by age, sex, and race) were created and compared: individuals with both DR and DM (DR+DM, n = 7629), individuals with DM but no DR (DM-only, n = 22,887), and individuals without DM (n = 22,887). Outcomes included dementia, Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS). Univariate and multivariate logistic regression analyses were performed, adjusting for demographics, comorbidities and diabetes-related mediators.
Results
In multivariable analysis, DM-only was associated with increased odds of dementia (adjusted odds ratio [aOR] 1.28, 95 % CI: 1.08–1.51; p = 0.004). However, DR in the setting of DM (DM+DR vs. DM-only) was not associated with further increased odds of neurodegenerative disease outcome in multivariate models (aOR for dementia 1.18, 95 % CI: 0.94–1.49). No significant associations were identified for AD, PD, or MS (all p ≥ 0.10).
Conclusion
Diabetic retinopathy was not associated with increased rates of neurodegenerative diseases beyond that conferred by diabetes itself, and the relationship may be mediated by diabetes severity and related comorbidities.
虽然糖尿病视网膜病变(DR)先前已被认为与神经退行性疾病有关,但目前尚不清楚DR是否独立反映了除糖尿病本身引起的神经退行性疾病。在这项研究中,我们利用来自我们所有人研究计划的数据来评估DR是否可以作为糖尿病患者神经退行性疾病的独立标志物。方法采用匹配的病例对照横断面研究,数据来自All of Us Research Program(美国电子病历数据库)。研究人员创建了三组(按年龄、性别和种族完全匹配)进行比较:同时患有糖尿病和糖尿病的个体(DR+DM, n = 7629)、患有糖尿病但没有糖尿病的个体(仅患有糖尿病,n = 22,887)和没有糖尿病的个体(n = 22,887)。结果包括痴呆、阿尔茨海默病(AD)、帕金森病(PD)和多发性硬化症(MS)。进行单变量和多变量logistic回归分析,调整人口统计学、合并症和糖尿病相关介质。结果在多变量分析中,仅dm与痴呆风险增加相关(校正优势比[aOR] 1.28, 95% CI: 1.08-1.51; p = 0.004)。然而,在多变量模型中,DM组的DR (DM+DR vs - DM)与神经退行性疾病结局的几率进一步增加无关(痴呆的aOR为1.18,95% CI: 0.94-1.49)。未发现AD、PD或MS有显著相关性(均p≥0.10)。结论糖尿病视网膜病变与糖尿病本身引起的神经退行性疾病发生率增加无关,可能与糖尿病严重程度及相关合并症有关。
{"title":"Association between diabetic retinopathy and neurodegenerative diseases in the All of Us research program","authors":"Ha-Neul Yu , Jocelyn He , Benjamin Kim , Gui-Shuang Ying","doi":"10.1016/j.ajoint.2025.100190","DOIUrl":"10.1016/j.ajoint.2025.100190","url":null,"abstract":"<div><h3>Purpose</h3><div>While diabetic retinopathy (DR) has previously been linked to neurodegenerative diseases, it remains unclear whether DR independently reflects neurodegenerative diseases beyond those attributable to diabetes itself. In this study, we leveraged data from the All of Us Research Program to assess whether DR serves as an independent marker of neurodegenerative disease among individuals with diabetes.</div></div><div><h3>Methods</h3><div>A matched case-control, cross-sectional study was conducted using data from the All of Us Research Program (US-based EHR database). Three groups (exactly matched by age, sex, and race) were created and compared: individuals with both DR and DM (DR+DM, <em>n</em> = 7629), individuals with DM but no DR (DM-only, <em>n</em> = 22,887), and individuals without DM (<em>n</em> = 22,887). Outcomes included dementia, Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS). Univariate and multivariate logistic regression analyses were performed, adjusting for demographics, comorbidities and diabetes-related mediators.</div></div><div><h3>Results</h3><div>In multivariable analysis, DM-only was associated with increased odds of dementia (adjusted odds ratio [aOR] 1.28, 95 % CI: 1.08–1.51; <em>p</em> = 0.004). However, DR in the setting of DM (DM+DR vs. DM-only) was not associated with further increased odds of neurodegenerative disease outcome in multivariate models (aOR for dementia 1.18, 95 % CI: 0.94–1.49). No significant associations were identified for AD, PD, or MS (all <em>p</em> ≥ 0.10).</div></div><div><h3>Conclusion</h3><div>Diabetic retinopathy was not associated with increased rates of neurodegenerative diseases beyond that conferred by diabetes itself, and the relationship may be mediated by diabetes severity and related comorbidities.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-24DOI: 10.1016/j.ajoint.2025.100191
M. Basil Marchi , Adeya Al Harami , Ahmed Maher , Omar Al-Qahtani , Joenie Datingaling Anilao , Javed Iqbal , Hashem Abu Serhan
Purpose
To investigate the infectious keratitis profile, causative agents, underlying risk factors, and clinical outcomes reported over 5 years in Qatar.
Design
A retrospective cohort study.
Methods
A retrospective analysis of all patients who received treatment for infectious keratitis at Hamad Medical Corporation, Qatar, between January 2019 and December 2023 was performed. Data regarding culture results, risk factors for infectious keratitis, visual acuity at the time of presentation, and the clinical course were obtained from medical records and microbiological reports.
Results
A total of 143 patients with microbial keratitis were included. The median age was 38 years (30–47.5). 93 (65 %) of patients were male. The mean follow-up duration was 18 ± 3 months. 34 (21.1 %) were culture-positive, and 107 (79.9 %) were culture-negative. Pseudomonas aeruginosa and Staphylococci spp. were the most common pathogens in culture-positive patients (N = 18, 53 %). Most patients (N = 104, 72.7 %) had at least one risk factor. Of these, 25 (17.5 %) had two risk factors, and 14 (9.8 %) had three or more. Ocular trauma was the most common risk factor (N = 45, 31.5 %), followed by contact lens use (N = 34, 23.8 %) and ocular surface disease (N = 24, 16.8 %). 133 (93 %) of patients improved with medical treatment alone, while 10 (7 %) required surgical interventions. The mean CDVA (logMAR) improved from 0.78 at presentation to 0.48 at the final follow-up (p < 0.001). Multivariable regression analysis showed that culture positivity was significantly associated with poorer corneal healing (OR 1.91; 95 % CI 1.49–2.33). While this indicates a robust association, causal inference cannot be established due to the observational study design.
Conclusions
Ocular trauma is the major risk factor for infectious keratitis in Qatar. Pseudomonas aeruginosa and Staphylococci spp. were the most common organisms isolated. Awareness campaigns about occupational hazards and ocular safety equipment could help decrease the burden of trauma-related keratitis in the country.
{"title":"Epidemiology, risk factors, clinical outcomes, and prognostic factors of infectious keratitis: A tertiary center experience in Qatar","authors":"M. Basil Marchi , Adeya Al Harami , Ahmed Maher , Omar Al-Qahtani , Joenie Datingaling Anilao , Javed Iqbal , Hashem Abu Serhan","doi":"10.1016/j.ajoint.2025.100191","DOIUrl":"10.1016/j.ajoint.2025.100191","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate the infectious keratitis profile, causative agents, underlying risk factors, and clinical outcomes reported over 5 years in Qatar.</div></div><div><h3>Design</h3><div>A retrospective cohort study.</div></div><div><h3>Methods</h3><div>A retrospective analysis of all patients who received treatment for infectious keratitis at Hamad Medical Corporation, Qatar, between January 2019 and December 2023 was performed. Data regarding culture results, risk factors for infectious keratitis, visual acuity at the time of presentation, and the clinical course were obtained from medical records and microbiological reports.</div></div><div><h3>Results</h3><div>A total of 143 patients with microbial keratitis were included. The median age was 38 years (30–47.5). 93 (65 %) of patients were male. The mean follow-up duration was 18 ± 3 months. 34 (21.1 %) were culture-positive, and 107 (79.9 %) were culture-negative. Pseudomonas aeruginosa and Staphylococci spp. were the most common pathogens in culture-positive patients (<em>N</em> = 18, 53 %). Most patients (<em>N</em> = 104, 72.7 %) had at least one risk factor. Of these, 25 (17.5 %) had two risk factors, and 14 (9.8 %) had three or more. Ocular trauma was the most common risk factor (<em>N</em> = 45, 31.5 %), followed by contact lens use (<em>N</em> = 34, 23.8 %) and ocular surface disease (<em>N</em> = 24, 16.8 %). 133 (93 %) of patients improved with medical treatment alone, while 10 (7 %) required surgical interventions. The mean CDVA (logMAR) improved from 0.78 at presentation to 0.48 at the final follow-up (<em>p</em> < 0.001). Multivariable regression analysis showed that culture positivity was significantly associated with poorer corneal healing (OR 1.91; 95 % CI 1.49–2.33). While this indicates a robust association, causal inference cannot be established due to the observational study design.</div></div><div><h3>Conclusions</h3><div>Ocular trauma is the major risk factor for infectious keratitis in Qatar. Pseudomonas aeruginosa and Staphylococci spp. were the most common organisms isolated. Awareness campaigns about occupational hazards and ocular safety equipment could help decrease the burden of trauma-related keratitis in the country.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100191"},"PeriodicalIF":0.0,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1016/j.ajoint.2025.100189
Elad Shvartz , Regina Raiyter , Amelia Goldshtein , Omri Zur , Eyal Margalit , Daniel Bahir
Purpose
Large language models (LLMs) are increasingly evaluated in ophthalmology, often using single test iterations that overlook whether responses remain consistent under repeated conditions. We aim to assess commonly used AI models under multiple testing iterations with varying conditions, including time of day, user credentials, and input type to determine their stability in ophthalmology contexts.
Design
Comparative analysis study.
Methods
We tested GPT-4o, GPT-4, and Gemini 2.0 Experimental Advanced on 111 multiple-choice questions from the “fundamentals” section of the Israeli ophthalmology residency exams. Each underwent 12 testing iterations, alternating daily testing time and user accounts to assess for potential biases. Iteration-level consistency was assessed by variation in accuracy across runs, while question-level consistency measured agreement in answers per question. Mixed-effects logistic regression estimated the effects of time of day, user account, and question modality. Question-level agreement was further analysed with Fleiss’ κ and response-pattern distributions.
Results
Gemini achieved the highest overall accuracy with smallest variation (84.5 %, SD 1.54), followed by GPT-4o (81.2 %, SD 1.75) and GPT-4 (72.4 %, SD 2.98). Mixed-effects models showed significant evening performance decline in GPT-4 (OR 1.61, p = 0.0045). No account-related differences were observed. All models performed markedly worse on image-based items than text (p < 0.001). Question-level analysis revealed high raw consistency but lower corrected consistency, especially for GPT-4.
Conclusions
LLMs tested demonstrated stable outputs across repeated questioning, though with notable model-specific variability and consistent challenges in image-based items. Future consistency testing should complement accuracy assessments when evaluating LLMs for potential integration into ophthalmology education and practice.
{"title":"Assessing consistency of AI chatbot responses in ophthalmology medical exams","authors":"Elad Shvartz , Regina Raiyter , Amelia Goldshtein , Omri Zur , Eyal Margalit , Daniel Bahir","doi":"10.1016/j.ajoint.2025.100189","DOIUrl":"10.1016/j.ajoint.2025.100189","url":null,"abstract":"<div><h3>Purpose</h3><div>Large language models (LLMs) are increasingly evaluated in ophthalmology, often using single test iterations that overlook whether responses remain consistent under repeated conditions. We aim to assess commonly used AI models under multiple testing iterations with varying conditions, including time of day, user credentials, and input type to determine their stability in ophthalmology contexts.</div></div><div><h3>Design</h3><div>Comparative analysis study.</div></div><div><h3>Methods</h3><div>We tested GPT-4o, GPT-4, and Gemini 2.0 Experimental Advanced on 111 multiple-choice questions from the “fundamentals” section of the Israeli ophthalmology residency exams. Each underwent 12 testing iterations, alternating daily testing time and user accounts to assess for potential biases. Iteration-level consistency was assessed by variation in accuracy across runs, while question-level consistency measured agreement in answers per question. Mixed-effects logistic regression estimated the effects of time of day, user account, and question modality. Question-level agreement was further analysed with Fleiss’ κ and response-pattern distributions.</div></div><div><h3>Results</h3><div>Gemini achieved the highest overall accuracy with smallest variation (84.5 %, SD 1.54), followed by GPT-4o (81.2 %, SD 1.75) and GPT-4 (72.4 %, SD 2.98). Mixed-effects models showed significant evening performance decline in GPT-4 (OR 1.61, <em>p</em> = 0.0045). No account-related differences were observed. All models performed markedly worse on image-based items than text (<em>p</em> < 0.001). Question-level analysis revealed high raw consistency but lower corrected consistency, especially for GPT-4.</div></div><div><h3>Conclusions</h3><div>LLMs tested demonstrated stable outputs across repeated questioning, though with notable model-specific variability and consistent challenges in image-based items. Future consistency testing should complement accuracy assessments when evaluating LLMs for potential integration into ophthalmology education and practice.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To evaluate and compare the performance of five AI chatbots—ChatGPT 3.5 (OpenAI), Google Gemini, Grok (xAI), DeepSeek, and Perplexity AI—in delivering accurate, clear, educational, and safe responses to pediatric ophthalmology-related queries.
Methods
Sixteen standardized caregiver-facing questions were posed to each chatbot in separate fresh sessions. Five pediatric ophthalmologists independently rated the responses across four domains—Accuracy, Clarity, Educational Value, and Safety—using a 5-point Likert scale (1–5). This produced 400 ratings per domain (5 chatbots × 16 questions × 5 raters). Inter-rater reliability was assessed using ICC(2,1), ICC(2,5), quadratic-weighted Fleiss’ κ, Gwet’s AC1, and percent agreement. Between-chatbot comparisons were analyzed with cumulative-link mixed models (CLMMs), reporting odds ratios (OR) with 95 % confidence intervals. Post-hoc pairwise contrasts were corrected using Holm adjustment.
Results
ChatGPT achieved the highest scores for Accuracy, while Google Gemini and Grok (xAI) showed modest advantages in Clarity and Educational Value. Safety ratings were similar across platforms and clustered at “adequate,” with limited probability of top scores. CLMM analyses confirmed significant between-chatbot differences in Accuracy, Clarity, and Educational Value, but not Safety. Inter-rater reliability was poor-to-fair for single raters [ICC(2,1) = 0.08–0.24], improving to moderate when averaging across all five raters [ICC(2,5) = 0.29–0.61]. Weighted Fleiss’ κ indicated only slight agreement (0.14), but Gwet’s AC1 (0.86) and high percent agreement (94 %) suggested stronger underlying consensus.
Conclusion
Performance of AI chatbots varied across domains: ChatGPT led in Accuracy, Gemini and Grok in Clarity and Educational Value, while no system excelled in Safety. Low agreement reflects the difficulty of scoring nuanced AI-generated responses rather than a lack of expert consensus. These findings support the potential of AI chatbots as educational adjuncts in pediatric ophthalmology, while underscoring the need for expert oversight, standardized rubrics, and domain-specific fine-tuning to improve reliability and safety
{"title":"Comparative evaluation of five AI chatbots in pediatric ophthalmology: A multidomain expert-based appraisal”","authors":"Shweta Dhiman , Chitaranjan Mishra , Savleen Kaur , Paromita Dutta , Prolima Thacker , Ashini Maniar , Raj Kenia , Logesh Balakrishnan","doi":"10.1016/j.ajoint.2025.100188","DOIUrl":"10.1016/j.ajoint.2025.100188","url":null,"abstract":"<div><h3>Aim</h3><div>To evaluate and compare the performance of five AI chatbots—ChatGPT 3.5 (OpenAI), Google Gemini, Grok (xAI), DeepSeek, and Perplexity AI—in delivering accurate, clear, educational, and safe responses to pediatric ophthalmology-related queries.</div></div><div><h3>Methods</h3><div>Sixteen standardized caregiver-facing questions were posed to each chatbot in separate fresh sessions. Five pediatric ophthalmologists independently rated the responses across four domains—Accuracy, Clarity, Educational Value, and Safety—using a 5-point Likert scale (1–5). This produced 400 ratings per domain (5 chatbots × 16 questions × 5 raters). Inter-rater reliability was assessed using ICC(2,1), ICC(2,5), quadratic-weighted Fleiss’ κ, Gwet’s AC1, and percent agreement. Between-chatbot comparisons were analyzed with cumulative-link mixed models (CLMMs), reporting odds ratios (OR) with 95 % confidence intervals. Post-hoc pairwise contrasts were corrected using Holm adjustment.</div></div><div><h3>Results</h3><div>ChatGPT achieved the highest scores for Accuracy, while Google Gemini and Grok (xAI) showed modest advantages in Clarity and Educational Value. Safety ratings were similar across platforms and clustered at “adequate,” with limited probability of top scores. CLMM analyses confirmed significant between-chatbot differences in Accuracy, Clarity, and Educational Value, but not Safety. Inter-rater reliability was poor-to-fair for single raters [ICC(2,1) = 0.08–0.24], improving to moderate when averaging across all five raters [ICC(2,5) = 0.29–0.61]. Weighted Fleiss’ κ indicated only slight agreement (0.14), but Gwet’s AC1 (0.86) and high percent agreement (94 %) suggested stronger underlying consensus.</div></div><div><h3>Conclusion</h3><div>Performance of AI chatbots varied across domains: ChatGPT led in Accuracy, Gemini and Grok in Clarity and Educational Value, while no system excelled in Safety. Low agreement reflects the difficulty of scoring nuanced AI-generated responses rather than a lack of expert consensus. These findings support the potential of AI chatbots as educational adjuncts in pediatric ophthalmology, while underscoring the need for expert oversight, standardized rubrics, and domain-specific fine-tuning to improve reliability and safety</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100188"},"PeriodicalIF":0.0,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-17DOI: 10.1016/j.ajoint.2025.100186
Mariapaola Giordano, Claudio Xompero, Carl-Joe Mehanna, Eric H. Souied
Purpose
To evaluate the ability of a large language model (LLM) to identify exudative recurrence in neovascular age-related macular degeneration (nAMD) from optical coherence tomography (OCT) scans and compare its performance with retina specialists.
Two consecutive OCT scans of patients with nAMD under pro re nata (PRN) regimen were collected. Screen recordings of the complete OCT scan comparisons (previous vs. current) were analyzed by two retina specialists versus ChatGPT-4o after providing a standardized prompt. Main outcome measure was agreement between the LLM and the ophthalmologists in detecting exudative activity. Statistical measures included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen’s kappa for agreement.
Results
A total of 102 eyes were included. Among 71 confirmed recurrences, ChatGPT-4o correctly identified 63 and missed 8; of 31 non-recurrences, it correctly identified 10 and misclassified 21 as positive. Overall accuracy was 71.57 %, with sensitivity of 88.73 % and specificity of 32.26 %. Agreement with ophthalmologists was fair (Cohen’s k = 0.238).
Conclusion
ChatGPT-4o demonstrated strong sensitivity in detecting exudative recurrences in nAMD, but limited specificity. Given the small, single-center cohort, the lack of external or same-dataset validation, these results should be considered preliminary, but highlights as LLM-assisted analysis, while not yet capable of replacing clinical expertise, may serve as a valuable adjunct for screening exudative changes in nAMD. Further refinements in the LLM could improve specificity and clinical utility.
{"title":"Identifying exudative recurrence in neovascular age-related macular degeneration using large language models","authors":"Mariapaola Giordano, Claudio Xompero, Carl-Joe Mehanna, Eric H. Souied","doi":"10.1016/j.ajoint.2025.100186","DOIUrl":"10.1016/j.ajoint.2025.100186","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the ability of a large language model (LLM) to identify exudative recurrence in neovascular age-related macular degeneration (nAMD) from optical coherence tomography (OCT) scans and compare its performance with retina specialists.</div></div><div><h3>Design</h3><div>Retrospective, single-center, observational study.</div></div><div><h3>Methods</h3><div>Two consecutive OCT scans of patients with nAMD under <em>pro re nata</em> (PRN) regimen were collected. Screen recordings of the complete OCT scan comparisons (previous vs. current) were analyzed by two retina specialists versus ChatGPT-4o after providing a standardized prompt. Main outcome measure was agreement between the LLM and the ophthalmologists in detecting exudative activity. Statistical measures included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen’s kappa for agreement.</div></div><div><h3>Results</h3><div>A total of 102 eyes were included. Among 71 confirmed recurrences, ChatGPT-4o correctly identified 63 and missed 8; of 31 non-recurrences, it correctly identified 10 and misclassified 21 as positive. Overall accuracy was 71.57 %, with sensitivity of 88.73 % and specificity of 32.26 %. Agreement with ophthalmologists was fair (Cohen’s <em>k</em> = 0.238).</div></div><div><h3>Conclusion</h3><div>ChatGPT-4o demonstrated strong sensitivity in detecting exudative recurrences in nAMD, but limited specificity. Given the small, single-center cohort, the lack of external or same-dataset validation, these results should be considered preliminary, but highlights as LLM-assisted analysis, while not yet capable of replacing clinical expertise, may serve as a valuable adjunct for screening exudative changes in nAMD. Further refinements in the LLM could improve specificity and clinical utility.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100186"},"PeriodicalIF":0.0,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-14DOI: 10.1016/j.ajoint.2025.100184
Ryan S. Huang , Michael Balas , David J. Mathew
Purpose
To assess the feasibility and utility of a text-to-image artificial intelligence (AI) model in enhancing patient counseling on the cosmetic side effects of prostaglandin analogue (PGA) therapy.
Design
Cross-sectional study.
Methods
Pre- and post-treatment periocular photographs of PGA-treated patients were collected. To simulate bilateral pre-treatment appearance, untreated eyes were mirrored. The Generative Fill feature powered by Adobe Firefly was applied to masked orbital regions, using descriptive text prompts to generate visualizations of prostaglandin-associated periorbitopathy (PAP), including upper eyelid ptosis, enophthalmos, and hypertrichosis. Prompts were iteratively refined to closely replicate known treatment-related changes.
Results
The AI model successfully produced visually realistic images within two minutes that closely resembled the actual post-treatment appearance of PAP. Key manifestations such as eyelash hypertrichosis, enophthalmos, deepened upper lid sulcus, and ptosis were effectively simulated using tailored prompts.
Conclusion
This proof-of-concept study demonstrates that text-to-image AI may serve as a novel, rapid, and personalized tool for visualizing potential cosmetic side effects of PGA therapy. By enabling patients to preview changes on their own faces, this technology may enhance informed consent, set realistic expectations, and improve treatment adherence. Future research should evaluate patient perceptions, the accuracy of AI-generated outcomes, and integration into clinical workflows.
{"title":"Text-to-image model for prostaglandin-associated periorbitopathy counseling: a proof-of-concept study","authors":"Ryan S. Huang , Michael Balas , David J. Mathew","doi":"10.1016/j.ajoint.2025.100184","DOIUrl":"10.1016/j.ajoint.2025.100184","url":null,"abstract":"<div><h3>Purpose</h3><div>To assess the feasibility and utility of a text-to-image artificial intelligence (AI) model in enhancing patient counseling on the cosmetic side effects of prostaglandin analogue (PGA) therapy.</div></div><div><h3>Design</h3><div>Cross-sectional study.</div></div><div><h3>Methods</h3><div>Pre- and post-treatment periocular photographs of PGA-treated patients were collected. To simulate bilateral pre-treatment appearance, untreated eyes were mirrored. The Generative Fill feature powered by Adobe Firefly was applied to masked orbital regions, using descriptive text prompts to generate visualizations of prostaglandin-associated periorbitopathy (PAP), including upper eyelid ptosis, enophthalmos, and hypertrichosis. Prompts were iteratively refined to closely replicate known treatment-related changes.</div></div><div><h3>Results</h3><div>The AI model successfully produced visually realistic images within two minutes that closely resembled the actual post-treatment appearance of PAP. Key manifestations such as eyelash hypertrichosis, enophthalmos, deepened upper lid sulcus, and ptosis were effectively simulated using tailored prompts.</div></div><div><h3>Conclusion</h3><div>This proof-of-concept study demonstrates that text-to-image AI may serve as a novel, rapid, and personalized tool for visualizing potential cosmetic side effects of PGA therapy. By enabling patients to preview changes on their own faces, this technology may enhance informed consent, set realistic expectations, and improve treatment adherence. Future research should evaluate patient perceptions, the accuracy of AI-generated outcomes, and integration into clinical workflows.</div></div>","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100184"},"PeriodicalIF":0.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-14DOI: 10.1016/j.ajoint.2025.100187
Mohamed Nasser Elshabrawi , Hashem Abu Serhan
{"title":"Reply to “Comments on “Effectiveness of intracameral antibiotics in reducing postoperative endophthalmitis risk after cataract surgery: A meta-analysis””","authors":"Mohamed Nasser Elshabrawi , Hashem Abu Serhan","doi":"10.1016/j.ajoint.2025.100187","DOIUrl":"10.1016/j.ajoint.2025.100187","url":null,"abstract":"","PeriodicalId":100071,"journal":{"name":"AJO International","volume":"2 4","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}