Pub Date : 2024-10-01DOI: 10.1001/jamaophthalmol.2024.3627
Megan E Collins, Adrienne W Scott
{"title":"Racial and Ethnic Disparities in Pediatric Ophthalmology Research.","authors":"Megan E Collins, Adrienne W Scott","doi":"10.1001/jamaophthalmol.2024.3627","DOIUrl":"10.1001/jamaophthalmol.2024.3627","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":" ","pages":"933-934"},"PeriodicalIF":7.8,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142132760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1001/jamaophthalmol.2024.3348
Shiuan-Tzuen Su, James C-C Wei
{"title":"Risk of Keratitis With EGFR Inhibitors Remains Controversial.","authors":"Shiuan-Tzuen Su, James C-C Wei","doi":"10.1001/jamaophthalmol.2024.3348","DOIUrl":"10.1001/jamaophthalmol.2024.3348","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":" ","pages":"983-984"},"PeriodicalIF":7.8,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142107522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1001/jamaophthalmol.2024.3330
Alice Verticchio Vercellin, Louis R Pasquale, Alon Harris
{"title":"Disc Hemorrhages in Open-Angle Glaucoma-Between a Rock and a Hard Place?","authors":"Alice Verticchio Vercellin, Louis R Pasquale, Alon Harris","doi":"10.1001/jamaophthalmol.2024.3330","DOIUrl":"10.1001/jamaophthalmol.2024.3330","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":" ","pages":"950-951"},"PeriodicalIF":7.8,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142132757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1001/jamaophthalmol.2024.3829
Todd E Scheetz,Mallory R Tollefson,Ben R Roos,Erin A Boese,Andrew E Pouw,Edwin M Stone,Michael J Schnieders,John H Fingert
ImportanceThis research confirms and further establishes that pathogenic variants in a fourth gene, METTL23, are associated with autosomal dominant normal-tension glaucoma (NTG).ObjectiveTo determine the frequency of glaucoma-causing pathogenic variants in the METTL23 gene in a cohort of patients with NTG from Iowa.Design, Setting, and ParticipantsThis case-control study took place at a single tertiary care center in Iowa from January 1997 to January 2024, with analysis occurring between January 2023 and January 2024. Two groups of participants were enrolled from the University of Iowa clinics: 331 patients with NTG and 362 control individuals without glaucoma. Patients with a history of trauma; steroid use; stigmata of pigment dispersion syndrome; exfoliation syndrome; or pathogenic variants in MYOC, TBK1, or OPTN were also excluded.Main Outcomes and MeasuresDetection of an enrichment of METTL23 pathogenic variants in individuals with NTG compared with control individuals without glaucoma.ResultsThe study included 331 patients with NTG (mean [SD] age, 68.0 [11.7] years; 228 [68.9%] female and 103 [31.1%] male) and 362 control individuals without glaucoma (mean [SD] age, 64.5 [12.6] years; 207 [57.2%] female and 155 [42.8%] male). There were 5 detected instances of 4 unique METTL23 pathogenic variants in patients with NTG. Three METTL23 variants-p.Ala7Val, p.Pro22Arg, and p.Arg63Trp-were judged to be likely pathogenic and were detected in 3 patients (0.91%) with NTG. However, when all detected variants were evaluated with either mutation burden analysis or logistic regression, their frequency was not statistically higher in individuals with NTG than in control individuals without glaucoma (1.5% vs 2.5%; P = .27).Conclusion and RelevanceThis investigation provides evidence that pathogenic variants in METTL23 are associated with NTG. Within an NTG cohort at a tertiary care center, pathogenic variants were associated with approximately 1% of NTG cases, a frequency similar to that of other known normal-tension glaucoma genes, including optineurin (OPTN), TANK-binding kinase 1 (TBK1), and myocilin (MYOC). The findings suggest that METTL23 pathogenic variants are likely involved in a biologic pathway that is associated with glaucoma that occurs at lower intraocular pressures.
{"title":"METTL23 Variants and Patients With Normal-Tension Glaucoma.","authors":"Todd E Scheetz,Mallory R Tollefson,Ben R Roos,Erin A Boese,Andrew E Pouw,Edwin M Stone,Michael J Schnieders,John H Fingert","doi":"10.1001/jamaophthalmol.2024.3829","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3829","url":null,"abstract":"ImportanceThis research confirms and further establishes that pathogenic variants in a fourth gene, METTL23, are associated with autosomal dominant normal-tension glaucoma (NTG).ObjectiveTo determine the frequency of glaucoma-causing pathogenic variants in the METTL23 gene in a cohort of patients with NTG from Iowa.Design, Setting, and ParticipantsThis case-control study took place at a single tertiary care center in Iowa from January 1997 to January 2024, with analysis occurring between January 2023 and January 2024. Two groups of participants were enrolled from the University of Iowa clinics: 331 patients with NTG and 362 control individuals without glaucoma. Patients with a history of trauma; steroid use; stigmata of pigment dispersion syndrome; exfoliation syndrome; or pathogenic variants in MYOC, TBK1, or OPTN were also excluded.Main Outcomes and MeasuresDetection of an enrichment of METTL23 pathogenic variants in individuals with NTG compared with control individuals without glaucoma.ResultsThe study included 331 patients with NTG (mean [SD] age, 68.0 [11.7] years; 228 [68.9%] female and 103 [31.1%] male) and 362 control individuals without glaucoma (mean [SD] age, 64.5 [12.6] years; 207 [57.2%] female and 155 [42.8%] male). There were 5 detected instances of 4 unique METTL23 pathogenic variants in patients with NTG. Three METTL23 variants-p.Ala7Val, p.Pro22Arg, and p.Arg63Trp-were judged to be likely pathogenic and were detected in 3 patients (0.91%) with NTG. However, when all detected variants were evaluated with either mutation burden analysis or logistic regression, their frequency was not statistically higher in individuals with NTG than in control individuals without glaucoma (1.5% vs 2.5%; P = .27).Conclusion and RelevanceThis investigation provides evidence that pathogenic variants in METTL23 are associated with NTG. Within an NTG cohort at a tertiary care center, pathogenic variants were associated with approximately 1% of NTG cases, a frequency similar to that of other known normal-tension glaucoma genes, including optineurin (OPTN), TANK-binding kinase 1 (TBK1), and myocilin (MYOC). The findings suggest that METTL23 pathogenic variants are likely involved in a biologic pathway that is associated with glaucoma that occurs at lower intraocular pressures.","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":"24 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1001/jamaophthalmol.2024.3707
Bo Qian,Bin Sheng,Hao Chen,Xiangning Wang,Tingyao Li,Yixiao Jin,Zhouyu Guan,Zehua Jiang,Yilan Wu,Jinyuan Wang,Tingli Chen,Zhengrui Guo,Xiang Chen,Dawei Yang,Junlin Hou,Rui Feng,Fan Xiao,Yihao Li,Mostafa El Habib Daho,Li Lu,Ye Ding,Di Liu,Bo Yang,Wenhui Zhu,Yalin Wang,Hyeonmin Kim,Hyeonseob Nam,Huayu Li,Wei-Chi Wu,Qiang Wu,Rongping Dai,Huating Li,Marcus Ang,Daniel Shu Wei Ting,Carol Y Cheung,Xiaofei Wang,Ching-Yu Cheng,Gavin Siew Wei Tan,Kyoko Ohno-Matsui,Jost B Jonas,Yingfeng Zheng,Yih-Chung Tham,Tien Yin Wong,Ya Xing Wang
ImportanceMyopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings.ObjectivesTo evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists.Design, Setting, and ParticipantsThe Myopic Maculopathy Analysis Challenge (MMAC) was an international competition to develop automated solutions for 3 tasks: (1) MM classification, (2) segmentation of MM plus lesions, and (3) spherical equivalent (SE) prediction. Participants were provided 3 subdatasets containing 2306, 294, and 2003 fundus images, respectively, with which to build algorithms. A group of 5 ophthalmologists evaluated the same test sets for tasks 1 and 2 to ascertain performance. Results from model ensembles, which combined outcomes from multiple algorithms submitted by MMAC participants, were compared with each individual submitted algorithm. This study was conducted from March 1, 2023, to March 30, 2024, and data were analyzed from January 15, 2024, to March 30, 2024.ExposureDL algorithms submitted as part of the MMAC competition or ophthalmologist interpretation.Main Outcomes and MeasuresMM classification was evaluated by quadratic-weighted κ (QWK), F1 score, sensitivity, and specificity. MM plus lesions segmentation was evaluated by dice similarity coefficient (DSC), and SE prediction was evaluated by R2 and mean absolute error (MAE).ResultsThe 3 tasks were completed by 7, 4, and 4 teams, respectively. MM classification algorithms achieved a QWK range of 0.866 to 0.901, an F1 score range of 0.675 to 0.781, a sensitivity range of 0.667 to 0.778, and a specificity range of 0.931 to 0.945. MM plus lesions segmentation algorithms achieved a DSC range of 0.664 to 0.687 for lacquer cracks (LC), 0.579 to 0.673 for choroidal neovascularization, and 0.768 to 0.841 for Fuchs spot (FS). SE prediction algorithms achieved an R2 range of 0.791 to 0.874 and an MAE range of 0.708 to 0.943. Model ensemble results achieved the best performance compared to each submitted algorithms, and the model ensemble outperformed ophthalmologists at MM classification in sensitivity (0.801; 95% CI, 0.764-0.840 vs 0.727; 95% CI, 0.684-0.768; P = .006) and specificity (0.946; 95% CI, 0.939-0.954 vs 0.933; 95% CI, 0.925-0.941; P = .009), LC segmentation (DSC, 0.698; 95% CI, 0.649-0.745 vs DSC, 0.570; 95% CI, 0.515-0.625; P < .001), and FS segmentation (DSC, 0.863; 95% CI, 0.831-0.888 vs DSC, 0.790; 95% CI, 0.742-0.830; P < .001).Conclusions and RelevanceIn this diagnostic study, 15 AI models for MM classification and segmentation on a public dataset made available for the MMAC competition were validated and evaluated, with some models achieving better diagnostic performance than ophthalmologists.
{"title":"A Competition for the Diagnosis of Myopic Maculopathy by Artificial Intelligence Algorithms.","authors":"Bo Qian,Bin Sheng,Hao Chen,Xiangning Wang,Tingyao Li,Yixiao Jin,Zhouyu Guan,Zehua Jiang,Yilan Wu,Jinyuan Wang,Tingli Chen,Zhengrui Guo,Xiang Chen,Dawei Yang,Junlin Hou,Rui Feng,Fan Xiao,Yihao Li,Mostafa El Habib Daho,Li Lu,Ye Ding,Di Liu,Bo Yang,Wenhui Zhu,Yalin Wang,Hyeonmin Kim,Hyeonseob Nam,Huayu Li,Wei-Chi Wu,Qiang Wu,Rongping Dai,Huating Li,Marcus Ang,Daniel Shu Wei Ting,Carol Y Cheung,Xiaofei Wang,Ching-Yu Cheng,Gavin Siew Wei Tan,Kyoko Ohno-Matsui,Jost B Jonas,Yingfeng Zheng,Yih-Chung Tham,Tien Yin Wong,Ya Xing Wang","doi":"10.1001/jamaophthalmol.2024.3707","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3707","url":null,"abstract":"ImportanceMyopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings.ObjectivesTo evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists.Design, Setting, and ParticipantsThe Myopic Maculopathy Analysis Challenge (MMAC) was an international competition to develop automated solutions for 3 tasks: (1) MM classification, (2) segmentation of MM plus lesions, and (3) spherical equivalent (SE) prediction. Participants were provided 3 subdatasets containing 2306, 294, and 2003 fundus images, respectively, with which to build algorithms. A group of 5 ophthalmologists evaluated the same test sets for tasks 1 and 2 to ascertain performance. Results from model ensembles, which combined outcomes from multiple algorithms submitted by MMAC participants, were compared with each individual submitted algorithm. This study was conducted from March 1, 2023, to March 30, 2024, and data were analyzed from January 15, 2024, to March 30, 2024.ExposureDL algorithms submitted as part of the MMAC competition or ophthalmologist interpretation.Main Outcomes and MeasuresMM classification was evaluated by quadratic-weighted κ (QWK), F1 score, sensitivity, and specificity. MM plus lesions segmentation was evaluated by dice similarity coefficient (DSC), and SE prediction was evaluated by R2 and mean absolute error (MAE).ResultsThe 3 tasks were completed by 7, 4, and 4 teams, respectively. MM classification algorithms achieved a QWK range of 0.866 to 0.901, an F1 score range of 0.675 to 0.781, a sensitivity range of 0.667 to 0.778, and a specificity range of 0.931 to 0.945. MM plus lesions segmentation algorithms achieved a DSC range of 0.664 to 0.687 for lacquer cracks (LC), 0.579 to 0.673 for choroidal neovascularization, and 0.768 to 0.841 for Fuchs spot (FS). SE prediction algorithms achieved an R2 range of 0.791 to 0.874 and an MAE range of 0.708 to 0.943. Model ensemble results achieved the best performance compared to each submitted algorithms, and the model ensemble outperformed ophthalmologists at MM classification in sensitivity (0.801; 95% CI, 0.764-0.840 vs 0.727; 95% CI, 0.684-0.768; P = .006) and specificity (0.946; 95% CI, 0.939-0.954 vs 0.933; 95% CI, 0.925-0.941; P = .009), LC segmentation (DSC, 0.698; 95% CI, 0.649-0.745 vs DSC, 0.570; 95% CI, 0.515-0.625; P < .001), and FS segmentation (DSC, 0.863; 95% CI, 0.831-0.888 vs DSC, 0.790; 95% CI, 0.742-0.830; P < .001).Conclusions and RelevanceIn this diagnostic study, 15 AI models for MM classification and segmentation on a public dataset made available for the MMAC competition were validated and evaluated, with some models achieving better diagnostic performance than ophthalmologists.","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":"44 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1001/jamaophthalmol.2024.3778
Shahin Hallaj,Niloofar Radgoudarzi,Sally L Baxter
{"title":"Crowdsourcing for Artificial Intelligence Models in Ophthalmology.","authors":"Shahin Hallaj,Niloofar Radgoudarzi,Sally L Baxter","doi":"10.1001/jamaophthalmol.2024.3778","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3778","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":"6 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1001/jamaophthalmol.2024.3836
Ehsan Ullah,Siying Lin,Jiaxiong Lu,Chelsea Bender,Andrew R Webster,Samantha Malka,Savita Madhusudhan,Emma Rees,Denise Williams,Aime R Agather,Catherine A Cukras,Robert B Hufnagel,Rui Chen,Laryssa A Huryn,Gavin Arno,Bin Guan
ImportanceInherited retinal dystrophies (IRDs) present a challenge in clinical diagnostics due to their pronounced genetic heterogeneity. Despite advances in next-generation sequencing (NGS) technologies, a substantial portion of the genetic basis underlying IRDs remains elusive. Addressing this gap seems important for gaining insights into the genetic landscape of IRDs, which may help improve diagnosis and prognosis and develop targeted therapies in the future.ObjectiveTo provide a clinical and molecular characterization of 6 patients with IRDs with biallelic disease-causing variants in a novel candidate IRD disease gene.Design, Setting, and ParticipantsThis multicenter case series study included 6 patients with IRDs from 4 tertiary hospitals (in the US: National Eye Institute, National Institutes of Health Clinical Center; in the UK: Moorfields Eye Hospital, Royal Liverpool University Hospital, Birmingham Women's and Children's).ExposuresBiallelic disease-causing variants in the novel candidate IRD disease gene, UBAP1L.Main Outcome and MeasuresParticipants underwent comprehensive clinical ophthalmic assessments to characterize the features of retinal dystrophy. Exome and genome sequencing revealed candidate variants in the UBAP1L gene; no other plausible disease variants in known IRD genes were identified. A minigene assay provided functional insights for a noncanonical splice variant, and a knockout mouse model was used for in vivo functional elucidation.ResultsFour homozygous UBAP1L variants were identified in the affected individuals from 6 families, including 2 frameshift variants (c.710del and c.634_644del), 1 canonical splice variant (c.121-2A>C), and 1 noncanonical splice variant (c.910-7G>A), which was shown to cause aberrant splicing and frameshift in a minigene assay. Participants presented with retinal dystrophy including maculopathy, cone dystrophy, and cone-rod dystrophy. Single-cell RNA sequencing of the retina showed that human UBAP1L is highly expressed in both cones and retinal pigment epithelium, whereas mouse Ubap1l is highly expressed in cone cells only. Mice with truncation of the C-terminal SOUBA domain did not manifest retinal degeneration up to 15 months of age.Conclusions and RelevanceStudy results reveal clinical and genetic evidence that loss of UBAP1L function was associated with inherited retinopathy in humans. These findings hold promise for improved clinical diagnostics, prognosis, and the potential development of targeted therapies for individuals affected by IRDs.
{"title":"Biallelic Loss-of-Function Variants in UBAP1L and Nonsyndromic Retinal Dystrophies.","authors":"Ehsan Ullah,Siying Lin,Jiaxiong Lu,Chelsea Bender,Andrew R Webster,Samantha Malka,Savita Madhusudhan,Emma Rees,Denise Williams,Aime R Agather,Catherine A Cukras,Robert B Hufnagel,Rui Chen,Laryssa A Huryn,Gavin Arno,Bin Guan","doi":"10.1001/jamaophthalmol.2024.3836","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3836","url":null,"abstract":"ImportanceInherited retinal dystrophies (IRDs) present a challenge in clinical diagnostics due to their pronounced genetic heterogeneity. Despite advances in next-generation sequencing (NGS) technologies, a substantial portion of the genetic basis underlying IRDs remains elusive. Addressing this gap seems important for gaining insights into the genetic landscape of IRDs, which may help improve diagnosis and prognosis and develop targeted therapies in the future.ObjectiveTo provide a clinical and molecular characterization of 6 patients with IRDs with biallelic disease-causing variants in a novel candidate IRD disease gene.Design, Setting, and ParticipantsThis multicenter case series study included 6 patients with IRDs from 4 tertiary hospitals (in the US: National Eye Institute, National Institutes of Health Clinical Center; in the UK: Moorfields Eye Hospital, Royal Liverpool University Hospital, Birmingham Women's and Children's).ExposuresBiallelic disease-causing variants in the novel candidate IRD disease gene, UBAP1L.Main Outcome and MeasuresParticipants underwent comprehensive clinical ophthalmic assessments to characterize the features of retinal dystrophy. Exome and genome sequencing revealed candidate variants in the UBAP1L gene; no other plausible disease variants in known IRD genes were identified. A minigene assay provided functional insights for a noncanonical splice variant, and a knockout mouse model was used for in vivo functional elucidation.ResultsFour homozygous UBAP1L variants were identified in the affected individuals from 6 families, including 2 frameshift variants (c.710del and c.634_644del), 1 canonical splice variant (c.121-2A>C), and 1 noncanonical splice variant (c.910-7G>A), which was shown to cause aberrant splicing and frameshift in a minigene assay. Participants presented with retinal dystrophy including maculopathy, cone dystrophy, and cone-rod dystrophy. Single-cell RNA sequencing of the retina showed that human UBAP1L is highly expressed in both cones and retinal pigment epithelium, whereas mouse Ubap1l is highly expressed in cone cells only. Mice with truncation of the C-terminal SOUBA domain did not manifest retinal degeneration up to 15 months of age.Conclusions and RelevanceStudy results reveal clinical and genetic evidence that loss of UBAP1L function was associated with inherited retinopathy in humans. These findings hold promise for improved clinical diagnostics, prognosis, and the potential development of targeted therapies for individuals affected by IRDs.","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":"32 1","pages":""},"PeriodicalIF":8.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-19DOI: 10.1001/jamaophthalmol.2024.3837
Roomasa Channa, Fasika Woreta
{"title":"Federally Qualified Health Centers to Reduce Disparities in Ophthalmology.","authors":"Roomasa Channa, Fasika Woreta","doi":"10.1001/jamaophthalmol.2024.3837","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3837","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":" ","pages":""},"PeriodicalIF":7.8,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142287376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-19DOI: 10.1001/jamaophthalmol.2024.3991
Joshua R Ehrlich
{"title":"Untreated Vision Loss as a Modifiable Dementia Risk Factor.","authors":"Joshua R Ehrlich","doi":"10.1001/jamaophthalmol.2024.3991","DOIUrl":"https://doi.org/10.1001/jamaophthalmol.2024.3991","url":null,"abstract":"","PeriodicalId":14518,"journal":{"name":"JAMA ophthalmology","volume":" ","pages":""},"PeriodicalIF":7.8,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142287377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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