JAMA ophthalmology最新文献

英文中文

Large Bilateral Exudative Retinal Detachments Related to Checkpoint Inhibitors 与检查点抑制剂有关的大的双侧渗出性视网膜脱离

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-20 DOI: 10.1001/jamaophthalmol.2025.3648

Roger P. Harrie

This case report discusses a diagnosis of exudative retinal detachment secondary to melanoma immunotherapy with the checkpoint inhibitors ipilimaud and nivolumab.

本病例报告讨论了继发于黑色素瘤免疫治疗与检查点抑制剂伊匹莫和纳沃单抗的渗出性视网膜脱离的诊断。

引用次数: 0

Prevalence, Risk Determinants, and Burden of Undiagnosed Age-Related Eye Diseases Among Older Asian Adults 亚洲老年人中未确诊的年龄相关性眼病的患病率、风险决定因素和负担

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-20 DOI: 10.1001/jamaophthalmol.2025.4623

Hiromi Yee, Chiew Meng Johnny Wong, Preeti Gupta, Sahil Thakur, Eva Fenwick, Ecosse L. Lamoureux, Ryan E. K. Man

Importance While population-based surveys have identified a high prevalence of undiagnosed eye diseases among Asian adults, these studies were conducted more than a decade ago, and there is a paucity of contemporary data. Objectives To determine the contemporary prevalence of undiagnosed age-related macular degeneration (AMD), diabetic retinopathy (DR), cataracts, and glaucoma and their shared risk determinants and to evaluate these conditions’ patient-centered and economic burden in a large multiethnic cohort of older Asian adults. Design, Setting, and Participants This cross-sectional cohort study was conducted among individuals from the Population Health and Eye Disease Profile in Elderly Singaporeans study (PIONEER-1, conducted from December 2017 to November 2022), a population-based cohort of community-dwelling individuals of Chinese, Malay, and Indian ethnicity aged 60 years or older living in Singapore. Data analysis was performed from April 2024 to December 2024. Exposures The 4 eye diseases were diagnosed clinically by a study ophthalmologist; participants were considered undiagnosed if no prior physician diagnosis or related interventions were reported. Main Outcomes and Measures One primary outcome, visual impairment (VI), was assessed clinically using the logMAR chart at 4 m by certified optometrists, while key patient-centered and economic outcomes were assessed using validated questionnaires. Results This study was conducted among 1878 individuals from the PIONEER-1 study, among whom mean (SD) age was 72.7 (8.3) years and 1013 participants (53.9%) were female. A total of 742 participants (weighted prevalence: 35.8%) had at least 1 type of undiagnosed eye disease, with 650 participants (87.6%), 87 participants (11.7%), and 5 participants (0.7%) having 1, 2, and 3 conditions, respectively. Among individuals with AMD, DR, cataracts, or glaucoma, the weighted prevalences of undiagnosed disease were 89.8%, 89.8%, 40.8%, and 48.1%, respectively. Younger age (odds ratio [OR], 1.08 per year decrease; 95% CI, 1.06-1.10; P &lt; .001), wearing multifocal glasses (OR, 1.75; 95% CI, 1.19-2.59; P = .005), and Malay (OR, 1.71; 95% CI, 1.21-2.43; P = .003) and Indian (OR, 1.43; 95% CI, 1.00-2.04; P = .05) ethnicities compared with Chinese individuals were associated with greater odds of having undiagnosed eye disease. Individuals with undiagnosed eye diseases reported −1.97% to −4.57% lower scores in health- and vision-related quality of life, as well as a greater likelihood of having VI (OR, 2.46; 95% CI, 1.68-3.61; P &lt; .001). Additionally, undiagnosed individuals incurred 1.73-fold higher health care expenditures compared with those who were diagnosed (diagnosed: reference; undiagnosed: OR, 1.73; 95% CI, 1.06-2.84; <jats:italic tog

虽然以人群为基础的调查已经确定了亚洲成年人中未确诊眼病的高发率，但这些研究是在十多年前进行的，并且缺乏当代数据。目的确定当代未确诊的年龄相关性黄斑变性（AMD）、糖尿病视网膜病变（DR）、白内障和青光眼的患病率及其共同的风险决定因素，并评估这些疾病在亚洲老年人群中以患者为中心的状况和经济负担。设计、环境和参与者本横断面队列研究是在新加坡老年人人口健康和眼病概况研究（PIONEER-1，于2017年12月至2022年11月进行）的个体中进行的，该研究是一项基于人群的队列研究，由居住在新加坡的60岁或以上的华人、马来人和印度人组成。数据分析时间为2024年4月至2024年12月。4种眼病由一名研究眼科医师临床诊断；如果没有先前的医生诊断或相关干预措施报告，参与者被认为是未确诊的。其中一个主要结局是视力损害（VI），由认证验光师在4米处使用logMAR图进行临床评估，而以患者为中心的关键结局和经济结局通过有效的问卷进行评估。结果本研究纳入了PIONEER-1研究的1878名个体，其中平均（SD）年龄为72.7（8.3）岁，女性1013名（53.9%）。共有742名参与者（加权患病率：35.8%）至少有一种未确诊的眼病，其中650名参与者（87.6%）、87名参与者（11.7%）和5名参与者（0.7%）分别有1、2和3种眼病。在AMD、DR、白内障或青光眼患者中，未确诊疾病的加权患病率分别为89.8%、89.8%、40.8%和48.1%。年龄更小(优势比[OR]， 1.08 /年下降；95% CI, 1.06-1.10; P &lt；001)、佩戴多焦点眼镜（OR, 1.75; 95% CI, 1.19-2.59; P = 0.005）、马来（OR, 1.71; 95% CI, 1.21-2.43; P = 0.003）和印度（OR, 1.43; 95% CI, 1.00-2.04; P = 0.05）与华人相比，患未确诊眼病的几率更高。患有未确诊眼病的个体在健康和视力相关生活质量方面的得分低- 1.97%至- 4.57%，患VI的可能性更大（OR, 2.46; 95% CI, 1.68-3.61; P < .001）。此外，未确诊个体的医疗保健支出比确诊个体高1.73倍（确诊：参考；未确诊：OR， 1.73; 95% CI, 1.06-2.84; P = 0.03）。在这项横断面队列研究中，未确诊的年龄相关眼病的发生率相对较高，这些疾病与较差的以患者为中心的结果和较高的医疗保健支出相关。这些结果支持使用社区眼科筛查服务和健康意识运动，针对60岁以上年龄范围低端的个人以及马来人和印度人，以减轻未确诊眼病对这些人的有害影响。

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引用次数: 0

OCT Angiography in X-Linked Retinoschisis x连锁视网膜裂的OCT血管造影

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-20 DOI: 10.1001/jamaophthalmol.2025.3605

Nan Zhou, Lihong Yang, Wenbin Wei

This case report provides a description of bullous retinoschisis using swept-source optical coherence tomography (OCT) in a 13-year-old boy diagnosed with X-linked retinoschisis.

本病例报告描述了一名13岁男孩使用扫描源光学相干断层扫描（OCT）诊断为x连锁视网膜裂的大疱性视网膜裂。

引用次数: 0

Treatment of Ligneous Conjunctivitis With Intravenous Plasminogen 静脉注射纤溶酶原治疗木质结膜炎

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-20 DOI: 10.1001/jamaophthalmol.2025.3314

Hazem M. Mousa, Amy M. Fowler, Amol A. Sura

This case report discusses the diagnosis and treatment of ligneous conjunctivitis in a man who presented with a left upper eyelid pseudomembrane of 1-year duration, recalcitrant periodontitis, and chronic sinusitis.

本病例报告讨论的诊断和治疗木质结膜炎的男子谁提出了左上眼睑假膜1年的持续时间，顽固性牙周炎，慢性鼻窦炎。

引用次数: 0

Undiagnosed Age-Related Eye Disease in Adults in Singapore. 新加坡成人未确诊的与年龄相关的眼病

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-20 DOI: 10.1001/jamaophthalmol.2025.4981

John S Wittenborn,Dean VanNasdale,David B Rein

引用次数: 0

Performance of Foundation Models vs Physicians in Textual and Multimodal Ophthalmological Questions 基础模型与医生在文本和多模式眼科问题中的表现

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-13 DOI: 10.1001/jamaophthalmol.2025.4255

Henry Rocha, Yu Jeat Chong, Arun James Thirunavukarasu, Yee Ling Wong, Shiao Wei Wong, Yin-Hsi Chang, Matthew Azzopardi, Benjamin Kye Jyn Tan, Anna Song, Andrew Malem, Nikhil Jain, Sean Zhou, Ting Fang Tan, Saaeha Rauz, Marcus Ang, Jodhbir S. Mehta, Daniel Shu Wei Ting, Darren Shu Jeng Ting

Importance There is an increasing amount of literature evaluating the clinical knowledge and reasoning performance of large language models (LLMs) in ophthalmology, but to date, investigations into its multimodal abilities clinically—such as interpreting images and tables—have been limited. Objective To evaluate the multimodal performance of the following 7 foundation models (FMs): GPT-4o (OpenAI), Gemini 1.5 Pro (Google), Claude 3.5 Sonnet (Anthropic), Llama-3.2-11B (Meta), DeepSeek V3 (High-Flyer), Qwen2.5-Max (Alibaba Cloud), and Qwen2.5-VL-72B (Alibaba Cloud) in answering offline Fellowship of the Royal College of Ophthalmologists part 2 written multiple-choice textual and multimodal questions, with head-to-head comparisons with physicians. Design, Setting, and Participants This cross-sectional study was conducted between September 2024 and March 2025 using questions sourced from a textbook used as an examination preparation resource for the Fellowship of the Royal College of Ophthalmologists part 2 written examination. Exposure FM performance. Main Outcomes and Measures The primary outcome measure was FM accuracy, defined as the proportion of answers generated by the model matching the textbook’s labeled letter answer. Results For textual questions, Claude 3.5 Sonnet (accuracy, 77.7%) outperformed all other FMs (followed by GPT-4o [accuracy, 69.9%], Qwen2.5-Max [accuracy, 69.3%], DeepSeek V3 [accuracy, 63.2%], Gemini Advanced [accuracy, 62.6%], Qwen2.5-VL-72B [accuracy, 58.3%], and Llama-3.2-11B [accuracy, 50.7%]), ophthalmology trainees (difference, 9.0%; 95% CI, 2.4%-15.6%; P = .01) and junior physicians (difference, 35.2%; 95% CI, 28.3%-41.9%; P &lt; .001), with comparable performance with expert ophthalmologists (difference, 1.3%; 95% CI, −5.1% to 7.4%; P = .72). GPT-4o (accuracy, 69.9%) outperformed GPT-4 (OpenAI; difference, 8.5%; 95% CI, 1.1%-15.8%; P = .02) and GPT-3.5 (OpenAI; difference, 21.8%; 95% CI, 14.3%-29.2%; P &lt; .001). For multimodal questions, GPT-4o (accuracy, 57.5%) outperformed all other FMs (Claude 3.5 Sonnet [accuracy, 47.5%], Qwen2.5-VL-72B [accuracy, 45%], Gemini Advanced [accuracy, 35%], and Llama-3.2-11B [accuracy, 25%]) and the junior physician (difference, 15%; 95% CI, −6.7% to 36.7%; P = .18) but was weaker than expert ophthalmologists (accuracy range, 70.0%-85.0%; P = .16) and trainees (accuracy range, 62.5%-80%; P = .35). Conclusions and Relevance Results of this cross-sectional study suggest that for textual questions, current FMs exhibited notable improvements in ophthalmological knowledge reasoning when compared with older LLMs and ophthalmology trainees, with performance co

越来越多的文献评价了眼科学中大型语言模型（llm）的临床知识和推理性能，但迄今为止，对其临床多模式能力（如解释图像和表格）的研究还很有限。目的评价gpt - 40 （OpenAI）、Gemini 1.5 Pro（谷歌）、Claude 3.5 Sonnet （Anthropic）、Llama-3.2-11B （Meta）、DeepSeek V3 （highflyer）、Qwen2.5-Max（阿里云）和Qwen2.5-VL-72B（阿里云）这7个基础模型在回答英国皇家眼科学院院士第二部分书面多项选择文本和多模态问题时的多模态表现，并与医生进行直接比较。设计、设置和参与者本横断面研究于2024年9月至2025年3月进行，使用的问题来自一本教科书，该教科书是英国皇家眼科学院院士资格第二部分笔试的备考资源。曝光调频性能。主要结果和测量方法主要结果测量方法是FM准确性，定义为模型生成的答案与教科书标记的字母答案匹配的比例。结果对于文本问题，Claude 3.5 Sonnet（准确率，77.7%）优于所有其他FMs（其次是gpt - 40[准确率，69.9%]、Qwen2.5-Max[准确率，69.3%]、DeepSeek V3[准确率，63.2%]、Gemini Advanced[准确率，62.6%]、Qwen2.5-VL-72B[准确率，58.3%]和Llama-3.2-11B[准确率，50.7%]）、眼科实习生（差异，9.0%;95% CI, 2.4%-15.6%; P = 0.01）和初级医生（差异，35.2%;95% CI, 28.3%-41.9%; P & lt;）。001)，与眼科专家的表现相当（差异为1.3%;95% CI, - 5.1%至7.4%;P = 0.72）。gpt - 40（准确率，69.9%）优于GPT-4 （OpenAI；差异，8.5%;95% CI, 1.1%-15.8%; P = 0.02）和GPT-3.5 （OpenAI；差异，21.8%;95% CI, 14.3%-29.2%; P < .001）。对于多模态问题，gpt - 40（准确率，57.5%）优于所有其他FMs （Claude 3.5 Sonnet[准确率，47.5%]、Qwen2.5-VL-72B[准确率，45%]、Gemini Advanced[准确率，35%]和Llama-3.2-11B[准确率，25%]）和初级医生（差异，15%;95% CI, - 6.7%至36.7%;P = 0.18），但弱于眼科专家（准确率范围，70.0%-85.0%;P = 0.16）和培训生（准确率范围，62.5%-80%;P = 0.35）。本横断面研究的结果表明，对于文本问题，与老年法学硕士和眼科培训生相比，当前的FMs在眼科知识推理方面表现出显著的改善，与专业眼科医生的表现相当。这些模型显示了回答眼科文本查询的医疗援助潜力，但它们的多模式能力仍然有限。进一步的研究或对具有多种眼科多模态数据的模型进行微调，可能会导致具有多模态功能的更有能力的应用。

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引用次数: 0

Large Choroidal Excavation in Stargardt Disease Stargardt病的大脉络膜挖掘

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-13 DOI: 10.1001/jamaophthalmol.2025.4342

Wenjia Yan, Yuntong Li, Zhaotian Zhang

This case report describes a large choroidal excavation and outer retinal atrophy in an otherwise healthy man aged 29 years who presented with bilateral gradually worsening vision since childhood.

本病例报告描述了一个大脉络膜挖掘和外视网膜萎缩在其他健康的男性29岁，表现为双侧视力逐渐恶化自幼。

引用次数: 0

Distribution of Ophthalmologists and Optometrists in the US. 美国眼科医生和验光师的分布。

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-13 DOI: 10.1001/jamaophthalmol.2025.4495

Peter R Kastl,Claire Senot,Yatish Hegde

引用次数: 0

Mastering Ophthalmology in the Digital Age. 掌握数字时代的眼科学。

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-13 DOI: 10.1001/jamaophthalmol.2025.4755

Rithambara Ramachandran,Stephanie Wey

引用次数: 0

Optic Disc Complication of Orbital Abscess. 视盘并发症的眼眶脓肿。

IF 8.1 1区医学 Q1 OPHTHALMOLOGY

JAMA ophthalmology

Pub Date : 2025-11-13 DOI: 10.1001/jamaophthalmol.2025.4499

Ali Aghajani,Afsaneh Naderi Beni,Sahar Vasezade

引用次数: 0

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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JAMA ophthalmology

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