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Colman BD, Zhu Z, Qi Z, van der Walt A. From real world data to real world evidence to improve outcomes in neuro-ophthalmology. Eye (Lond) 2024; 38:2448-2456. [PMID: 38844583 PMCID: PMC11306594 DOI: 10.1038/s41433-024-03160-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/21/2024] [Accepted: 05/28/2024] [Indexed: 08/09/2024] Open
Abstract
Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.
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Affiliation(s)
- Blake D Colman
- Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia
| | - Zhuoting Zhu
- Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, Australia
- Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, VIC, Australia
| | - Ziyi Qi
- Centre for Eye Research Australia, Ophthalmology, University of Melbourne, Melbourne, VIC, Australia
- Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, VIC, Australia
| | - Anneke van der Walt
- Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, VIC, Australia.
- Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia.
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Tang WSW, Lau NXM, Krishnan MN, Chin YC, Ho CSH. Depression and Eye Disease-A Narrative Review of Common Underlying Pathophysiological Mechanisms and their Potential Applications. J Clin Med 2024; 13:3081. [PMID: 38892791 PMCID: PMC11172702 DOI: 10.3390/jcm13113081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024] Open
Abstract
Background: Depression has been shown to be associated with eye diseases, including dry eye disease (DED), cataracts, glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR). This narrative review explores potential pathophysiological connections between depression and eye disease, as well as its potential correlations with ocular parameters. Methods: A literature search was conducted in August 2022 in PUBMED, EMBASE, and PsycINFO. Published articles related to the subject were consolidated and classified according to respective eye diseases and pathophysiological mechanisms. Results: The literature reviewed suggests that common pathophysiological states like inflammation and neurodegeneration may contribute to both depression and certain eye diseases, while somatic symptoms and altered physiology, such as disruptions in circadian rhythm due to eye diseases, can also influence patients' mood states. Grounded in the shared embryological, anatomical, and physiological features between the eye and the brain, depression is also correlated to changes observed in non-invasive ophthalmological imaging modalities, such as changes in the retinal nerve fibre layer and retinal microvasculature. Conclusions: There is substantial evidence of a close association between depression and eye diseases. Understanding the underlying concepts can inform further research on treatment options and monitoring of depression based on ocular parameters.
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Affiliation(s)
- Wymann Shao Wen Tang
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
| | - Nicole Xer Min Lau
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
| | | | - You Chuen Chin
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
- Raffles Medical Group, Singapore 188770, Singapore
| | - Cyrus Su Hui Ho
- Department of Psychological Medicine, National University of Singapore, Singapore 119077, Singapore
- Department of Psychological Medicine, National University Hospital, Singapore 119228, Singapore
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Liu X, Tan H, Wang W, Chen Z. Deep learning based retinal vessel segmentation and hypertensive retinopathy quantification using heterogeneous features cross-attention neural network. Front Med (Lausanne) 2024; 11:1377479. [PMID: 38841586 PMCID: PMC11150614 DOI: 10.3389/fmed.2024.1377479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 05/09/2024] [Indexed: 06/07/2024] Open
Abstract
Retinal vessels play a pivotal role as biomarkers in the detection of retinal diseases, including hypertensive retinopathy. The manual identification of these retinal vessels is both resource-intensive and time-consuming. The fidelity of vessel segmentation in automated methods directly depends on the fundus images' quality. In instances of sub-optimal image quality, applying deep learning-based methodologies emerges as a more effective approach for precise segmentation. We propose a heterogeneous neural network combining the benefit of local semantic information extraction of convolutional neural network and long-range spatial features mining of transformer network structures. Such cross-attention network structure boosts the model's ability to tackle vessel structures in the retinal images. Experiments on four publicly available datasets demonstrate our model's superior performance on vessel segmentation and the big potential of hypertensive retinopathy quantification.
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Affiliation(s)
- Xinghui Liu
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
- Department of Cardiovascular Medicine, Guizhou Provincial People's Hospital, Guiyang, China
| | - Hongwen Tan
- Department of Cardiovascular Medicine, Guizhou Provincial People's Hospital, Guiyang, China
| | - Wu Wang
- Electrical Engineering College, Guizhou University, Guiyang, China
| | - Zhangrong Chen
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
- Department of Cardiovascular Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
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Tomić M, Vrabec R, Ljubić S, Prkačin I, Bulum T. Patients with Type 2 Diabetes, Higher Blood Pressure, and Infrequent Fundus Examinations Have a Higher Risk of Sight-Threatening Retinopathy. J Clin Med 2024; 13:2496. [PMID: 38731024 PMCID: PMC11084692 DOI: 10.3390/jcm13092496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 03/28/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024] Open
Abstract
Background: Diabetic retinopathy (DR) is the most common cause of preventable blindness among working-age adults. This study aimed to evaluate the impact of the regularity of fundus examinations and risk factor control in patients with type 2 diabetes (T2DM) on the prevalence and severity of DR. Methods: One hundred and fifty-six T2DM patients were included in this cross-sectional study. Results: In this sample, the prevalence of DR was 46.2%. Patients with no DR mainly did not examine the fundus regularly, while most patients with mild/moderate nonproliferative DR (NPDR) underwent a fundus examination regularly. In 39.7% of patients, this was the first fundus examination due to diabetes, and 67% of them had sight-threatening DR (STDR). Diabetes duration (p = 0.007), poor glycemic control (HbA1c) (p = 0.006), higher systolic blood pressure (SBP) (p < 0.001), and diastolic blood pressure (DBP) (p = 0.002) were the main predictors of DR. However, the impact of SBP (AOR 1.07, p = 0.003) and DBP (AOR 1.13, p = 0.005) on DR development remained significant even after adjustment for diabetes duration and HbA1c. The DR prevalence was higher in patients with higher blood pressure (≥130/80 mmHg) than in those with target blood pressure (<130/80 mmHg) (p = 0.043). None of the patients with target blood pressure had STDR. The peaks in SBP and DBP were observed in T2DM with DR and the first fundus examination due to diabetes. Conclusions: In this T2DM sample, DR prevalence was very high and strongly related to blood pressure and a lack of regular fundus examinations. These results indicate the necessity of establishing systematic DR screening in routine diabetes care and targeting blood pressure levels according to T2DM guidelines.
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Affiliation(s)
- Martina Tomić
- Department of Ophthalmology, Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases, Merkur University Hospital, 10000 Zagreb, Croatia
| | - Romano Vrabec
- Department of Ophthalmology, Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases, Merkur University Hospital, 10000 Zagreb, Croatia
| | - Spomenka Ljubić
- Department of Diabetes and Endocrinology, Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases, Merkur University Hospital, 10000 Zagreb, Croatia
- School of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
| | - Ingrid Prkačin
- School of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
- Department of Internal Medicine, Merkur University Hospital, 10000 Zagreb, Croatia
| | - Tomislav Bulum
- Department of Diabetes and Endocrinology, Vuk Vrhovac University Clinic for Diabetes, Endocrinology and Metabolic Diseases, Merkur University Hospital, 10000 Zagreb, Croatia
- School of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
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Heitmar R, Link D, Kotliar K, Schmidl D, Klee S. Editorial: Functional assessments of the ocular circulation. Front Med (Lausanne) 2023; 10:1222022. [PMID: 37359007 PMCID: PMC10285660 DOI: 10.3389/fmed.2023.1222022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 05/16/2023] [Indexed: 06/28/2023] Open
Affiliation(s)
- Rebekka Heitmar
- Centre for Vision Across the Lifespan, School of Applied Sciences, University of Huddersfield, Huddersfield, United Kingdom
| | - Dietmar Link
- Division Optoelectrophysiological Engineering, Department of Computer Science and Automation, Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Konstantin Kotliar
- Medical Engineering and Technomathematics, Aachen University of Applied Sciences, Aachen, Germany
| | - Doreen Schmidl
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Sascha Klee
- Division Optoelectrophysiological Engineering, Department of Computer Science and Automation, Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
- Division Biostatistics and Data Science, Department General Health Studies, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
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Ji Y, Ji Y, Liu Y, Zhao Y, Zhang L. Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images. Front Cell Dev Biol 2023; 11:1168327. [PMID: 37056999 PMCID: PMC10086262 DOI: 10.3389/fcell.2023.1168327] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023] Open
Abstract
As the only blood vessels that can directly be seen in the whole body, pathological changes in retinal vessels are related to the metabolic state of the whole body and many systems, which seriously affect the vision and quality of life of patients. Timely diagnosis and treatment are key to improving vision prognosis. In recent years, with the rapid development of artificial intelligence, the application of artificial intelligence in ophthalmology has become increasingly extensive and in-depth, especially in the field of retinal vascular diseases. Research study results based on artificial intelligence and fundus images are remarkable and provides a great possibility for early diagnosis and treatment. This paper reviews the recent research progress on artificial intelligence in retinal vascular diseases (including diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, retinopathy of prematurity, and age-related macular degeneration). The limitations and challenges of the research process are also discussed.
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Affiliation(s)
- Yuke Ji
- The Laboratory of Artificial Intelligence and Bigdata in Ophthalmology, Affiliated Eye Hospital of Nanjing Medical University, Nanjing, China
| | - Yun Ji
- Affiliated Hospital of Shandong University of traditional Chinese Medicine, Jinan, Shandong, China
| | - Yunfang Liu
- Department of Ophthalmology, The First People’s Hospital of Huzhou, Huzhou, Zhejiang, China
| | - Ying Zhao
- Affiliated Hospital of Shandong University of traditional Chinese Medicine, Jinan, Shandong, China
- *Correspondence: Liya Zhang, ; Ying Zhao,
| | - Liya Zhang
- Department of Ophthalmology, The First People’s Hospital of Huzhou, Huzhou, Zhejiang, China
- *Correspondence: Liya Zhang, ; Ying Zhao,
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Post-COVID-19 Syndrome: Retinal Microcirculation as a Potential Marker for Chronic Fatigue. Int J Mol Sci 2022; 23:ijms232213683. [PMID: 36430175 PMCID: PMC9690863 DOI: 10.3390/ijms232213683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/04/2022] [Accepted: 11/05/2022] [Indexed: 11/10/2022] Open
Abstract
Post-COVID-19 syndrome (PCS) is characterized by persisting sequelae after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PCS can affect patients with all COVID-19 disease severities. As previous studies have revealed impaired blood flow as a provoking factor triggering PCS, it was the aim of the present study to investigate the potential association between self-reported chronic fatigue and retinal microcirculation in patients with PCS, potentially indicating an objective biomarker. A prospective study was performed, including 201 subjects: 173 patients with PCS and 28 controls. Retinal microcirculation was visualized by OCT angiography (OCT-A) and quantified using the Erlangen-Angio-Tool as macula and peripapillary vessel density (VD). Chronic fatigue (CF) was assessed according to the variables of Bell’s score, age and gender. VDs in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP) were analyzed, considering the repetitions (12 times). Seropositivity for autoantibodies targeting G protein-coupled receptors (GPCR-AAbs) was determined by an established cardiomyocyte bioassay. Taking account of the repetitions, a mixed model was performed to detect possible differences in the least square means between the different groups included in the analysis. An age effect in relation to VD was observed between patients and controls (p < 0.0001). Gender analysis showed that women with PCS showed lower VD levels in the SVP compared to male patients (p = 0.0015). The PCS patients showed significantly lower VDs in the ICP as compared to the controls (p = 0.0001 (CI: 0.32; 1)). Moreover, considering PCS patients, the mixed model revealed a significant difference between those with chronic fatigue (CF) and those without CF with respect to VDs in the SVP (p = 0.0033 (CI: −4.5; −0.92)). The model included variables of age, gender and Bell’s score, representing a subjective marker for CF. Consequently, retinal microcirculation might serve as an objective biomarker in subjectively reported chronic fatigue in patients with PCS.
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