Asunto(s)
Demencia , Lentes Intraoculares , Humanos , Demencia/epidemiología , Demencia/etiología , Factores de Riesgo , Luz/efectos adversos , Luz AzulRESUMEN
The aim of this perspective is to promote the theory of salutogenesis as a novel approach to addressing ophthalmologic inflammatory conditions, illustrating several concepts in which it is based upon and how they can be applied to medical practice. This theory can better contextualize why patients with similar demographics and exposures are not uniform in their clinical presentations. Stressors in daily life can contribute to a state of ill-health and there are various factors that help alleviate their negative impact. These alleviating factors are significantly impaired in people with poor vision, one of the most common presentations of ophthalmologic conditions. Salutogenic principles can guide the treatment of eye conditions to be more respectful of patient autonomy amidst shifting expectations of the doctor-patient relationship. Being able to take ownership of their health and feeling that their cultural beliefs were considered improves compliance and subsequently gives more optimal outcomes. Population-level policy interventions could also utilize salutogenic principles to identify previously overlooked domains that can be addressed. We identified several papers about salutogenesis in an ophthalmological context and acknowledged the relatively few studies on this topic at present and offer directions in which we can explore further in subsequent studies.
RESUMEN
Data is the cornerstone of using AI models, because their performance directly depends on the diversity, quantity, and quality of the data used for training. Using AI presents unique potential, particularly in medical applications that involve rich data such as ophthalmology, encompassing a variety of imaging methods, medical records, and eye-tracking data. However, sharing medical data comes with challenges because of regulatory issues and privacy concerns. This review explores traditional and nontraditional data sharing methods in medicine, focusing on previous works in ophthalmology. Traditional methods involve direct data transfer, whereas newer approaches prioritize security and privacy by sharing derived datasets, creating secure research environments, or using model-to-data strategies. We examine each method's mechanisms, variations, recent applications in ophthalmology, and their respective advantages and disadvantages. By empowering medical researchers with insights into data sharing methods and considerations, this review aims to assist informed decision-making while upholding ethical standards and patient privacy in medical AI development.
Asunto(s)
Inteligencia Artificial , Difusión de la Información , Oftalmología , HumanosRESUMEN
Purpose: Understanding sociodemographic factors associated with poor visual outcomes in children with juvenile idiopathic arthritis-associated uveitis may help inform practice patterns. Patients and Methods: Retrospective cohort study on patients <18 years old who were diagnosed with both juvenile idiopathic arthritis and uveitis based on International Classification of Diseases tenth edition codes in the Intelligent Research in Sight Registry through December 2020. Surgical history was extracted using current procedural terminology codes. The primary outcome was incidence of blindness (20/200 or worse) in at least one eye in association with sociodemographic factors. Secondary outcomes included cataract and glaucoma surgery following uveitis diagnosis. Hazard ratios were calculated using multivariable-adjusted Cox proportional hazards models. Results: Median age of juvenile idiopathic arthritis-associated uveitis diagnosis was 11 (Interquartile Range: 8 to 15). In the Cox models adjusting for sociodemographic and insurance factors, the hazard ratios of best corrected visual acuity 20/200 or worse were higher in males compared to females (HR 2.15; 95% CI: 1.45-3.18), in Black or African American patients compared to White patients (2.54; 1.44-4.48), and in Medicaid-insured patients compared to commercially-insured patients (2.23; 1.48-3.37). Conclusion: Sociodemographic factors and insurance coverage were associated with varying levels of risk for poor visual outcomes in children with juvenile idiopathic arthritis-associated uveitis.