Correlation between diabetes and glaucoma risk: Insights from a population‐based glaucoma screening (NCT 05875090)
Bernardo MonteiroAfonso Lima‐CabritaV. L. da S. LoboRafael WhitfieldRodrigo S MarquesMatilde OuriqueTeresa VarandasRafael Correia BarãoMarta PazosIngeborg StalmansLuís Abegão Pinto
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Aims/Purpose: To evaluate the association between Glaucoma referral and Diabetes in participants in a population‐based glaucoma screening using artificial intelligence (AI). Methods: Analysis of cohort characteristics at baseline contact (screening visit). Glaucoma referral was defined by intraocular pressure (IOP) ≥ 24mmHg or AI score ≥ 0.73. Diabetes information, including HbA1C, was collected from electronic medical records. Our analysis used descriptive and bivariate statistics, including chi‐square tests. Significance was p < 0.05 with 95% confidence intervals (CI). Results: Data from 837 participants were analyzed, comprising 54% males, with an average age of 62±4 years, across 11 functional units of Santa Maria Local Health Unit. A significant portion of participants had diabetes (69%), of which 8.3% were referred. AI scores were lower in diabetic patients compared to the non‐diabetic sub‐cohort (0.57 vs 0.61; p = 0,009). Intrigingly, while no correlation in the overall range of HbA1C with the AI score was detected, there was a detectable trend towards higher AI scores in decompensated diabetic patients (HbA1C > 9%; n = 10): (ρ = 0.591; CI‐0.083‐0.894; p = 0.072) Conclusions: Overall, diabetes diagnosis may influence glaucoma referral programs. AI threshold for referral may be adapted to the setting (particularly if a dual diabetic retinopathy and glaucoma screening is considered). Interestingly, AI appears to detect retinal/disc abnormalities in metabolic decompensated patients.Glaucoma is an insidious “thief of vision” that affects millions of Americans and is a leading cause of blindness worldwide. The signs of the most common form of glaucoma are incremental and are often not noticed until the vision loss is acute. Nurses, in any practice arena, who are aware and knowledgeable about glaucoma can play a vital role in identifying those at risk for glaucoma before irreversible damage is done. In addition, knowledgeable nurses will be able to educate those diagnosed with glaucoma about their disease and the proper use of their glaucoma medications. In the following discussion, a brief explanation of how glaucoma affects vision is presented and selected medications used to treat glaucoma are identified.
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Early detection of glaucoma, a widespread visual disease, can prevent vision loss. Unfortunately, ophthalmologists are scarce and clinical diagnosis requires much time and cost. Therefore, we developed a screening Tri-Labeling deep convolutional neural network (3-LbNets) to identify no glaucoma, glaucoma suspect, and glaucoma cases in global fundus images. 3-LbNets extracts important features from 3 different labeling modals and puts them into an artificial neural network (ANN) to find the final result. The method was effective, with an AUC of 98.66% for no glaucoma, 97.54% for glaucoma suspect, and 97.19% for glaucoma when analysing 206 fundus images evaluated with unanimous agreement from 3 well-trained ophthalmologists (3/3). When analysing 178 difficult to interpret fundus images (with majority agreement (2/3)), this method had an AUC of 80.80% for no glaucoma, 69.52% for glaucoma suspect, and 82.74% for glaucoma cases.Clinical relevance—This establishes a robust global fundus image screening network based on the ensemble method that can optimize glaucoma screening to alleviate the toll on those with glaucoma and prevent glaucoma suspects from developing the disease.
Fundus (uterus)
Optic cup (embryology)
Optic disc
Gonioscopy
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Normal tension glaucoma
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Quantitative assessment
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Introduction: Glaucoma is a common eye disease that is quite dangerous to public health as one of the major causes of permanent blindness. Although glaucoma can be prevented, most glaucoma patients are underdiagnosed. It’s require a screening system to help patients detect glaucoma and treat it promptly. Objective: 1) To describe the glaucoma situation of person over 40 years old in Hue city. 2) To find out some factors related to glaucoma at study sites. Methods: A desciptive cross-sectional method was conducted with 2025 people over 40 years old in 27 wards of Hue city. Results: The percentage of glaucoma is 4.7%, with closed glaucoma accounting for 55.2%, with 9.1% of people suspected of glaucoma. The percentage of glaucoma patients suffering from blindness was 21.7%. There was an association between glaucoma and age, gender, hypertension, diabetes, cardiovascular disease, family history of glaucoma, previous history of ocular surgery. Conclusions: The percentage of glaucoma is 4.7%, blindness is 21.7%, glaucoma is related to age, gender, hypertension, diabetes, cardiovascular disease, family history of glaucoma, preoperative eye surgery. Key words: Glaucoma, people over 40 years old
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The prevalence of POAG is estimated to be 1.23% in individuals 40-89 years of age.This figure is based on a meta-analysis that used relatively narrow definitions of POAG.This meta-analysis included all screening studies in the general population. 3 In the Netherlands, in 2018, 314.900 individuals were estimated to be registered at their general practitioner with a type of glaucoma diagnosis. 4 Based on a review of published prevalence data and modelling of the data, 79.6 million individuals with glaucoma will be counted worldwide in 2020 and about 11.1 million people will be bilaterally blind from glaucoma in 2020.Open-angle glaucoma will account for 74% and angle-closure glaucoma for 26% of this number. 5A prevalence of 24.1% for unilateral glaucoma blindness and 10.6% for bilateral glaucoma blindness at the end of life has been reported for glaucoma patients. 6 Risk factors, predictive factors and prognostic factorsEstablishing risk factors, predictive factors and prognostic factors is important in order to identify patients in an early stage of glaucoma, to detect patients at risk of glaucoma progression and to adjust glaucoma therapy in these glaucoma patients.Risk factors for open-angle glaucoma are determinants that are associated with the development of open-angle glaucoma in healthy eyes. 7 Various risk factors for open-angle glaucoma have been identified 2, 7, 8 such as older age, increased 14 15
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Many glaucoma patients continue to lose vision despite treatment to lower intraocular pressure. In addition to the loss of retinal ganglion cells in the eye, there is injury to major visual pathways of the brain along the retino-geniculo-cortical pathway. Evidence for this comes from both glaucoma models and glaucoma patients. Understanding central visual system changes in glaucoma will provide insights into human glaucomatous neural degeneration and disease progression, in addition to potential novel strategies to prevent vision loss in glaucoma.
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