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The cult of saints in Western Europe developed during the late period of antiquity and the early Middle Ages. Their importance to European society was undeniable; holy medicine was the only hope for people, because there were no doctors. The number of saints had increased over the years, and people sought medical help from them through prayer and other religious practices. Some of the saints became "specialized" in treating various wounds and dermatologic diseases. During our research, we tried to determine whether the cult of saints led to the develop-ment of hospitals that treated skin diseases, as discovered in the Hospital Brother of Saint Anthony. A large number of saints who were patrons of wounds and skin diseases were collected in three studies. In the first report, we presented a great number of saints who were patrons to treat animal bites. The second report presented patron saints of wounds, ulcers, burns, and frostbites; and the third report decsribed saints who treated contagious diseases (such as ergotism, leprosy, and scabies). The phenomenon of holy medicine is part of the history of dermatology and is important due to "specializations," which refer to an understanding of skin diseases and the methods of treating various wounds and dermatologic diseases.
Subject(s)
Bites and Stings , Humans , Animals , Saints/history , Wounds and Injuries/history , Skin Diseases/history , Skin Diseases/etiology , History, Ancient , Religion and Medicine , Dermatology/historyABSTRACT
Purpose: Fundus fluorescein angiography (FFA) is the gold standard for retinal vein occlusion (RVO) diagnosis. This study aims to develop a deep learning-based system to diagnose and classify RVO using FFA images, addressing the challenges of time-consuming and variable interpretations by ophthalmologists. Methods: 4028 FFA images of 467 eyes from 463 patients were collected and annotated. Three convolutional neural networks (CNN) models (ResNet50, VGG19, InceptionV3) were trained to generate the label of image quality, eye, location, phase, lesions, diagnosis, and macular involvement. The performance of the models was evaluated by accuracy, precision, recall, F-1 score, the area under the curve, confusion matrix, human-machine comparison, and Clinical validation on three external data sets. Results: The InceptionV3 model outperformed ResNet50 and VGG19 in labeling and interpreting FFA images for RVO diagnosis, achieving 77.63%-96.45% accuracy for basic information labels and 81.72%-96.45% for RVO-relevant labels. The comparison between the best CNN and ophthalmologists showed up to 19% accuracy improvement with the inceptionV3. Conclusion: This study developed a deep learning model capable of automatically multi-label and multi-classification of FFA images for RVO diagnosis. The proposed system is anticipated to serve as a new tool for diagnosing RVO in places short of medical resources.
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Background and Objectives: Myopia is the most widespread ocular disorder globally and its prevalence has been increasing over the past decades. Atropine eye drops stand out as the only pharmacological intervention used in clinical practice to control myopia progression. The aim of this study was to explore the effect of 0.01% atropine eye drops on myopia progression. Patients and Methods: Healthy children aged 6-12 years with cycloplegic spherical equivalent (SE) from -0.5 D to -5.0 D and astigmatism ≤1.5 D were included. Myopia progression was assessed by changes in SE and axial length (AL) over 1 year and SE changes 1 year before the study enrollment and during the 1-year follow-up. Adverse events were evaluated based on complaints reported by either parents or the children themselves during follow-up visits. Results: The analysis involved 55 patients in the 0.01% atropine eye drops group and 66 in the control group. After the 1-year follow-up, the change in SE was -0.50 (-2.25-0.50) D in the control group compared to -0.50 (-1.50-0.50) D in the 0.01% atropine group (p = 0.935); AL change was 0.31 (0.18) mm in the control group and 0.29 (0.18) mm in the 0.01% atropine group (p = 0.480). The change in SE was -0.68 (-2.0--0.25) D/year before the study and remained similar -0.50 (-2.25-0.25) D over the 1-year follow-up in the control group (p = 0.111); SE change was reduced from -1.01 (-2.0--0.25) D/year before the study to -0.50 (-1.5-0.5) D over the 1-year follow-up in the 0.01% atropine group (p < 0.001). In the 0.01% atropine group, ten (16.4%) children experienced mild adverse events, including blurred near vision, ocular discomfort, photophobia, dry eyes, and anisocoria. Conclusions: Compared to the control group, the administration of 0.01% atropine eye drops demonstrated no significant effect on changes in SE and AL over a 1-year follow-up. However, children in the 0.01% atropine group initially experienced higher myopia progression, which decreased with treatment over the course of 1 year. Future studies should explore the long-term effects, rebound effects, potential genetic associations, and efficacy of higher doses of atropine in managing myopia progression.
Subject(s)
Atropine , Myopia , Ophthalmic Solutions , Humans , Atropine/administration & dosage , Atropine/therapeutic use , Child , Ophthalmic Solutions/administration & dosage , Male , Female , Myopia/drug therapy , Follow-Up Studies , Mydriatics/administration & dosage , Mydriatics/therapeutic use , White People/statistics & numerical data , Refraction, Ocular/drug effects , Refraction, Ocular/physiologyABSTRACT
Objective: To investigate the efficacy and safety of one-year treatment with 0.03% atropine eye drops for slowing myopia progression among children aged 6-12 years. Methods: Healthy Caucasian children aged 6-12 years with cycloplegic spherical equivalent (SE) from -1.0 D to -5.0 D and astigmatism and anisometropia ≤1.5 D were included. Changes in mean axial length (AL) and objective SE as well as changes in intraocular pressure (IOP), central corneal thickness (CCT), anterior chamber depth (ACD) and lens thickness (LT) were assessed in the 0.03% atropine eye drops group and the control group from baseline through the 1-year follow-up. The proportion of participants showing myopia progression of <0.5 D from baseline in each group and any potential side effects in 0.03% atropine group were evaluated. Results: The study involved 31 patients in the 0.03% atropine eye drops group and 41 in the control group. Administration of 0.03% atropine for 1 year resulted in a mean change in SE of -0.34 (0.44) D/year, significantly lower than the -0.60 (0.50) D/year observed in the control group (p = 0.024). The change in AL was 0.19 (0.17) mm in the 0.03% atropine group, compared to 0.31 (0.20) mm in the control group (p = 0.015). There were no significant differences in changes of IOP, CCT and LT between the groups (all p ≥ 0.05). The 0.03% atropine group had a significantly greater increase in ACD compared to the control group (p = 0.015). In total, 64.5% of patients in the 0.03% atropine group showed progression <0.5 D/year, in contrast to 39.0% in the control group (p = 0.032). Adverse events were reported in 13 (35.0%) out of 37 patients in the treatment group, leading to discontinuation of the eye drops in six (16.0%) cases. None of the adverse events were severe. Conclusions: Despite a higher incidence of adverse events, 0.03% atropine eye drops effectively slowed the progression of myopia over 1-year.
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Background: The convergence of smartphone technology and artificial intelligence (AI) has revolutionized the landscape of ophthalmic care, offering unprecedented opportunities for diagnosis, monitoring, and management of ocular conditions. Nevertheless, there is a lack of systematic studies on discussing the integration of smartphone and AI in this field. Main text: This review includes 52 studies, and explores the integration of smartphones and AI in ophthalmology, delineating its collective impact on screening methodologies, disease detection, telemedicine initiatives, and patient management. The collective findings from the curated studies indicate promising performance of the smartphone-based AI screening for various ocular diseases which encompass major retinal diseases, glaucoma, cataract, visual impairment in children and ocular surface diseases. Moreover, the utilization of smartphone-based imaging modalities, coupled with AI algorithms, is able to provide timely, efficient and cost-effective screening for ocular pathologies. This modality can also facilitate patient self-monitoring, remote patient monitoring and enhancing accessibility to eye care services, particularly in underserved regions. Challenges involving data privacy, algorithm validation, regulatory frameworks and issues of trust are still need to be addressed. Furthermore, evaluation on real-world implementation is imperative as well, and real-world prospective studies are currently lacking. Conclusions: Smartphone ocular imaging merged with AI enables earlier, precise diagnoses, personalized treatments, and enhanced service accessibility in eye care. Collaboration is crucial to navigate ethical and data security challenges while responsibly leveraging these innovations, promising a potential revolution in care access and global eye health equity.
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We conducted a systematic review of research in artificial intelligence (AI) for retinal fundus photographic images. We highlighted the use of various AI algorithms, including deep learning (DL) models, for application in ophthalmic and non-ophthalmic (i.e., systemic) disorders. We found that the use of AI algorithms for the interpretation of retinal images, compared to clinical data and physician experts, represents an innovative solution with demonstrated superior accuracy in identifying many ophthalmic (e.g., diabetic retinopathy (DR), age-related macular degeneration (AMD), optic nerve disorders), and non-ophthalmic disorders (e.g., dementia, cardiovascular disease). There has been a significant amount of clinical and imaging data for this research, leading to the potential incorporation of AI and DL for automated analysis. AI has the potential to transform healthcare by improving accuracy, speed, and workflow, lowering cost, increasing access, reducing mistakes, and transforming healthcare worker education and training.
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INTRODUCTION: The aim of this work is to compare 20 intraocular lens (IOL) power calculation formulas in medium-long eyes (24.50-25.99 mm) in terms of root mean square absolute error (RMSAE), median absolute error (MedAE), and percentage of eyes with prediction error (PE) within ± 0.50 D. METHODS: The data of patients who underwent uneventful phacoemulsification between January 2017 and September 2023 were reviewed. Pre-surgery IOL power was calculated using Holladay1, SRK/T, Hoffer Q, Holladay 2, and Haigis. Three months after phacoemulsification, refraction was measured. Post-surgery IOL power calculations were performed utilizing the following formulas: Barrett Universal II, Kane, K6, Olsen (OLCR), Olsen (standalone), PEARL-DGS, Ladas Super Formula AI (LSF AI), T2, EVO, VRF, Hoffer QST, Castrop, VRF-G, Karmona, and Naeser 2. RMSAE, MedAE, and percentage of eyes with PE within ± 0.25 D, ± 0.50 D, ± 0.75 D and ± 1.00 were calculated. RESULTS: One hundred twenty-four eyes with axial length ranges between 24.52 and 25.97 mm were studied. The SRK/T formula yielded the lowest RMSAE (0.206) just before Holladay 1 (0.260) and T2 (0.261). In terms of MedAE, the best outcome was obtained by SRK/T (0.12) followed by Barrett Universal II (0.15) and LSF AI (0.15). The highest percentage of eyes with prediction error within ± 0.50 D was achieved by SRK/T, T2, and Holladay 1 (97.58, 93.55, and 93.55%, respectively). CONCLUSIONS: Third-generation formulas (SRK/T, Holladay 1) provided highly accurate outcomes in medium-long eyes and still can be wildly used to calculate IOL power.
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The integration of artificial intelligence (AI) in ophthalmology has promoted the development of the discipline, offering opportunities for enhancing diagnostic accuracy, patient care, and treatment outcomes. This paper aims to provide a foundational understanding of AI applications in ophthalmology, with a focus on interpreting studies related to AI-driven diagnostics. The core of our discussion is to explore various AI methods, including deep learning (DL) frameworks for detecting and quantifying ophthalmic features in imaging data, as well as using transfer learning for effective model training in limited datasets. The paper highlights the importance of high-quality, diverse datasets for training AI models and the need for transparent reporting of methodologies to ensure reproducibility and reliability in AI studies. Furthermore, we address the clinical implications of AI diagnostics, emphasizing the balance between minimizing false negatives to avoid missed diagnoses and reducing false positives to prevent unnecessary interventions. The paper also discusses the ethical considerations and potential biases in AI models, underscoring the importance of continuous monitoring and improvement of AI systems in clinical settings. In conclusion, this paper serves as a primer for ophthalmologists seeking to understand the basics of AI in their field, guiding them through the critical aspects of interpreting AI studies and the practical considerations for integrating AI into clinical practice.
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INTRODUCTION: Myopia and its vision-threatening complications present a significant public health problem. This review aims to provide an updated overview of the multitude of known and emerging interventions to control myopia, including their potential effect, safety, and costs. METHODS: A systematic literature search of three databases was conducted. Interventions were grouped into four categories: environmental/behavioral (outdoor time, near work), pharmacological (e.g., atropine), optical interventions (spectacles and contact lenses), and novel approaches such as red-light (RLRL) therapies. Review articles and original articles on randomized controlled trials (RCT) were selected. RESULTS: From the initial 3224 retrieved records, 18 reviews and 41 original articles reporting results from RCTs were included. While there is more evidence supporting the efficacy of low-dose atropine and certain myopia-controlling contact lenses in slowing myopia progression, the evidence about the efficacy of the newer interventions, such as spectacle lenses (e.g., defocus incorporated multiple segments and highly aspheric lenslets) is more limited. Behavioral interventions, i.e., increased outdoor time, seem effective for preventing the onset of myopia if implemented successfully in schools and homes. While environmental interventions and spectacles are regarded as generally safe, pharmacological interventions, contact lenses, and RLRL may be associated with adverse effects. All interventions, except for behavioral change, are tied to moderate to high expenditures. CONCLUSION: Our review suggests that myopia control interventions are recommended and prescribed on the basis of accessibility and clinical practice patterns, which vary widely around the world. Clinical trials indicate short- to medium-term efficacy in reducing myopia progression for various interventions, but none have demonstrated long-term effectiveness in preventing high myopia and potential complications in adulthood. There is an unmet need for a unified consensus for strategies that balance risk and effectiveness for these methods for personalized myopia management.
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PURPOSE: To examine the association between ambient air pollution and dry eye symptoms (DES) during the COVID-19 pandemic and explore whether air pollution had increased the risk of DES to a greater extent than other risk factors. METHODS: A nationwide cross-sectional survey was conducted from June 20, 2022 to August 31, 2022. The Ocular Surface Disease Index-6 (OSDI-6) questionnaire was used to assess the presence of DES. Logistic regression models were employed to analyze the associations between DES and air pollution variables, including air quality index (AQI), fine particulate matter (PM2.5), PM10, sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3) and residing near industrial zones. We explored the interactions of air pollutants and other risk factors in the additive models by calculating the synergy index (SI). Standardized regression coefficients were calculated to compare the relative importance of risk factors for DES. RESULTS: A total of 21,909 participants were included in the analysis. Residing near industrial zones was significantly correlated with a higher risk of DES (Odds ratio (OR): 1.57, 95 % confidence interval (CI): 1.38-1.79). No significant associations were found between DES and air pollutants except SO2 (OR: 1.05, 95 % CI: 1.02-1.09, per standard deviation increment in SO2 concentration). The restricted cubic spline analyses revealed a linear concentration-response relationship between SO2 and DES. The interaction analyses suggested synergetic interactions of SO2 with depression and problematic internet use. Among the risk factors, depression, anxiety and problematic Internet use contributed more to the increased risk of DES. CONCLUSION: The association between ambient air pollutants and DES may have been mitigated during the pandemic due to increased time spent indoors. Despite this, our findings support the deleterious health impact of air pollutants. Future urban planning should plan industrial zones further away from residential areas.
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Air Pollutants , Air Pollution , COVID-19 , Dry Eye Syndromes , Particulate Matter , Adult , Aged , Female , Humans , Male , Middle Aged , Air Pollutants/analysis , Air Pollution/statistics & numerical data , China/epidemiology , COVID-19/epidemiology , Cross-Sectional Studies , Dry Eye Syndromes/epidemiology , Dry Eye Syndromes/chemically induced , East Asian People , Environmental Exposure/statistics & numerical data , Pandemics , Particulate Matter/analysis , Risk Factors , Sulfur Dioxide/analysisABSTRACT
This Viewpoint discusses common myths about myopia and educational strategies for bringing clinical practice better in line with evidence.
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Myopia , Humans , Myopia/epidemiology , Myopia/therapy , Myopia/physiopathology , Prevalence , Refraction, Ocular/physiologyABSTRACT
Importance: Various studies have widely explored the association between index of dietary inflammation (DII) and occurrence of diseases. Accumulating evidence have revealed that a lower DII seems to be protective against a variety of diseases. Nevertheless, the association between DII and age-related cataract remains unclear. Objective: To investigate the correlation between DII and age-related cataract in a representative sample of the American population. Design setting and participants: This cross-sectional population-based study comprised 6,395 participants from the National Health and Nutrition Examination Survey (NHANES) conducted in cycles from 2005 to 2008. DII was calculated using dietary recall information, with higher scores indicating greater inflammatory potential of the diet. Age-related cataract was evaluated using cataract surgery as a surrogate measure. Covariates included sociodemographic factors, lifestyle factors, physical measures, and comorbidities. Logistic regression models were employed to assess the association between DII and cataract. The presence of a non-linear relationship was examined using restricted cubic spline analysis. Subgroup analysis was conducted to explore potential interaction effects. Data analysis was performed from September 1 to December 30, 2022. Main outcomes and measures: Age-related cataract assessed through cataract surgery information obtained from a self-reported questionnaire. Results: A total of 6,395 participants were included, with a mean (standard deviation, SD) age of 48.7 (15.3) years. Of these, 3,115 (48.7%) were male, 3,333 (52.1%) were non-Hispanic white, and 683 (10.7%) had cataract. The mean (SD) DII was -4.78 (1.74). After adjusting for all included covariates, DII showed a positive association with cataract, both as a continuous variable (odds ratio (OR): 1.054, 95% confidence interval (CI): 1.007-1.103, p = 0.023) and in quartiles, with the highest quartile compared to the lowest (OR: 1.555, 95% CI: 1.233-1.967, p < 0.001). Restricted cubic spline analysis revealed no evidence of a non-linear relationship (p for non-linearity 0.085). Subgroup analysis indicated no interaction effects among the studied covariates. Conclusions and relevance: These findings suggest that a pro-inflammatory diet serves as a risk factor for the occurrence of cataracts.
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PURPOSE: To comprehensively identify the corneal biomechanical differences measured by Corvis ST between different degrees of myopia and emmetropia. DESIGN: Systematic review and meta-analysis. METHODS: Electronic databases, including PubMed, Embase, and Web of Science, were systematically searched for studies comparing the corneal biomechanics among various degrees of myopes and emmetropes using Corvis ST. The weighted mean differences and 95% confidence intervals were calculated. Meta-analysis was performed in high and nonhigh myopes and in myopes and emmetropes, respectively. RESULTS: Eleven studies were included in this study. The meta-analysis among myopes and emmetropes included 1947 myopes and 621 emmetropes, and 443 high myopes and 449 nonhigh myopes were included in the meta-analysis among high and nonhigh myopia. Myopes showed the cornea with significantly longer time at the first applanation (A1t) and lower length at the second applanation (A2L) than emmetropes. High myopes showed significantly greater A1t, velocity at the second applanation (A2v), deformation amplitude at the highest concavity (HC-DA), and peak distance at the highest concavity (HC-PD) and decreased time at the second applanation (A2t) and radius of the highest concavity (HC-R). CONCLUSIONS: Corneal biomechanics is different in myopia, especially in high myopia. Compared with nonhigh myopes, the corneas of high myopes deformed slower during the first applanation, faster during the second applanation, and showed greater deformation amplitude, indicating greater elasticity and viscidity.
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Cornea , Emmetropia , Myopia , Humans , Cornea/physiopathology , Emmetropia/physiology , Biomechanical Phenomena/physiology , Myopia/physiopathology , Elasticity/physiology , Intraocular Pressure/physiology , Tonometry, Ocular , Refraction, Ocular/physiologyABSTRACT
Endophthalmitis is a rare but vision-threatening infection characterized by marked inflammation of intraocular fluids and tissues, uncommonly seen following surgery and intravitreal injection. Antimicrobials are used worldwide in the prophylaxis and treatment of bacterial and fungal infections of the eye and are standard treatment in the preoperative and postoperative care of surgical patients. However, antimicrobials are reported to be overprescribed in many parts of the world, which contributes to antimicrobial resistance (AMR). AMR complicates the prophylaxis and treatment of endophthalmitis. This article examines the prevalence and mechanisms of AMR in ocular microorganisms, emphasizing the importance of understanding AMR patterns for tailored treatments. It also explores prophylaxis and management strategies for endophthalmitis, with a discussion on the use of intracameral antibiotic administration. The use of prophylactic intracameral antibiotics during cataract surgery is common in many parts of the world but is still controversial in some locations, especially in the US. Finally, it highlights the role of stewardship in ophthalmology and its benefits in the treatment of endophthalmitis.
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The present study was designed to investigate the physical stability of three organic materials with similar chemical structures. The examined compounds revealed completely different crystallization tendencies in their supercooled liquid states and were classified into three distinct classes based on their tendency to crystallize. (S)-4-Benzyl-2-oxazolidinone easily crystallizes during cooling from the melt; (S)-4-Benzylthiazolidine-2-thione does not crystallize during cooling from the melt, but crystallizes easily during subsequent reheating above Tg; and (S)-4-Benzyloxazolidine-2-thione does not crystallize either during cooling from the melt or during reheating. Such different tendencies to crystallize are observed despite the very similar chemical structures of the compounds, which only differ in oxide or sulfur atoms in one of their rings. We also studied the isothermal crystallization kinetics of the materials that were shown to transform into a crystalline state. Molecular dynamics and thermal properties were thoroughly investigated using broadband dielectric spectroscopy, as well as conventional and temperature-modulated differential scanning calorimetry in the wide temperature range. It was found that all three glass formers have the same dynamic fragility (m = 93), calculated directly from dielectric structural relaxation times. This result verifies that dynamic fragility is not related to the tendency to crystallize. In addition, thermodynamic fragility predictions were also made using calorimetric data. It was found that the thermodynamic fragility evaluated based on the width of the glass transition, observed in the temperature dependence of heat capacity, correlates best with the tendency to crystallize.
Subject(s)
Thiones , Crystallization/methods , Phase Transition , Temperature , Thermodynamics , Calorimetry, Differential ScanningSubject(s)
Eyeglasses , Myopia , Standard of Care , Humans , Myopia/therapy , Myopia/physiopathologyABSTRACT
PURPOSE: The association between sleep and myopia in children and adolescents has been reported, yet it remains controversial and inconclusive. This study aimed to investigate the influence of different sleep traits on the risk of myopia using meta-analytical and Mendelian randomization (MR) techniques. METHODS: The literature search was performed in August 31, 2023 based on PubMed, Embase, Web of Science, and Cochrane library. The meta-analysis of observational studies reporting the relationship between sleep and myopia was conducted. MR analyses were carried out to assess the causal impact of genetic pre-disposition for sleep traits on myopia. RESULTS: The results of the meta-analysis indicated a significant association between the risk of myopia and both short sleep duration [odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.08-1.42, P = 0.003] and long sleep duration (OR = 0.75, 95% CI = 0.66-0.86, P < 0.001). MR analyses revealed no significant causal associations of genetically determined sleep traits with myopia, including chronotype, sleep duration, short sleep duration and long sleep duration (all P > 0.05). CONCLUSIONS: No evidence was found to support a causal relationship between sleep traits and myopia. While sleep may not independently predict the risk of myopia, the potential impact of sleep on the occurrence and development of myopia cannot be disregarded.