ABSTRACT
In this interview, Prof. Lin Lu introduced ways to improve sleep and relieve stress, influences of sleep on the heart and mental health, essential qualities of psychiatrists, etc. His major viewpoints are: (a) sleep deprivation disrupts physiological functions, (b) prevalence of mental health problems in the general population, health-care workers, and students showed an increasing trend following COVID-19, and (c) it is a tendency for doctors to develop a comprehensive and integrated treatment plan from the physical and mental perspectives. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
ABSTRACT
Purpose : Age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma are vision-threatening diseases (VTDs) affecting 36 million people in the USA. With 5.7 ophthalmologists per 100,000 Americans, over 50% of VTDs go undetected. We assessed deep learning Artificial Intelligence (DLAI) in VTD detection in community and clinical settings. Methods : 223 subjects (mean age 54.6, 58% male) from community screenings (A) and clinic (B) underwent 45-degree retinal imaging. In A (non-dilated), an onsite telemedicine reader (R1) and remote ophthalmologist (R2) graded image quality (gamma and alignment, 1-5 scale) and referable VTD using the international grading scales for AMD and DR, and cup-to-disc ratio and nerve fiber layer for glaucoma. In B (dilated), gradings were collected from R1 and the clinical diagnosis (d). A senior ophthalmologist (R3) adjudicated disputed findings. In A, DLAI VTD referral was compared to R1/R2/R3 consensus (S);in B, overall referral was compared to R1/d/R3 consensus (C). Images were uploaded to a cloud-based DLAI (SELENA+, EyRIS Pte Ltd) (Fig 1). Cohen's kappa assessed intergrader agreement. Results : R1 and R2 found 4.7% eyes ungradable. DLAI marked 55.6% ungradable;74.6% of them were for AMD. Of the DLAI ungradable eyes, image quality was ≤ 3, and 56.2% had ≥ 1+ cataract (R1). Compared to in A, in B DLAI had higher sensitivity (97.1% vs. 63.2%) and positive predictive value (69.4% vs. 32%). In A, DLAI had higher specificity (94.5% vs.16.7%) and negative predictive value (98.4% vs. 75.0%) (Table 1). In A, Cohen's kappa was 0.946 between R1 and R2, with a 13% disagreement rate. In 56% of the disagreements, R3 agreed with R1. In B, Cohen's kappa was 0.874 for R1 and d;R1 referred more than d. In A and B, DLAI referred more than R1, R2, and H/C. DLAI referred all eyes with > 1 VTD (1%) for further examination. Grading times for DLAI, R1, and R2 were 30, 129, and 68 seconds. Conclusions : DLAI performed best in DR and glaucoma detection;a potential solution for the high ungradable rate can be for DLAI to re-center uploaded images. DLAI can increase efficiency and accessibility of screenings for multiple VTDs, in both underserved populations and clinic. The ability to minimize direct contact confers an advantage during COVID-19. Further studies will investigate DLAI use in VTD progression.
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Purpose : The most common cause of blurry vision in the United States is refractive error. Despite being a correctable condition, over 8.2 million people are estimated to have their refractive error go undiagnosed or untreated. Minorities and low-income groups in particular have significantly increased odds of inadequate correction and double the rates of near-vision impairment. We aimed to address this gap in care through the provision of refractive glasses during community-based tele-ophthalmology screenings. Methods : Eight free eye screening events were held in Newark and West New York, NJ. Demographic information, intraocular pressure, visual acuity, auto-refraction, retinal imaging, and optical coherence tomography were obtained from each subject as part of a comprehensive tele-ophthalmology protocol. Reading glasses were provided as needed based on the recommendation of a certified telemedicine reader. Eligible recipients completed surveys on site regarding access to eye care. They were surveyed again by phone after one month to assess degree of satisfaction and vision improvement. Results : 38 subjects (mean age 53, 47% male) qualified for presbyopia correction and received reading glasses. 97% were Hispanic and 3% were African American. Of the 33 that returned surveys, 88% reported not seeing an eye doctor annually. The most common reason was lack of insurance or inability to pay (71%). Others included having no need to see an eye doctor (10%), disliking eye doctors (7%), not knowing the importance of regular eye exams (3%), and COVID-19 (3%). Of the 25 subjects that were reached for follow-up, 92% reported using the glasses daily. Those that did not reported the power was too strong or they did not feel they needed them. Subjects noted an average improvement in vision of 4.4 out of 5 and an average satisfaction of 4.7 out of 5 (Figure 1). Conclusions : Glasses distribution is an effective way to address refractive error in underserved communities. Given the gaps in knowledge and utilization of eye care identified in our study, there is an obvious need for continued outreach to these areas. Further studies will include larger populations and evaluate mobile refraction devices to increase ease and reach of glasses provision.
ABSTRACT
Purpose : Vision Threatening Diseases (VTD) (age-related macular degeneration [AMD], cataract, diabetic retinopathy [DR], and glaucoma) account for 37% of all blindness. Screening and follow-up are crucial in preserving vision. During COVID-19, clinics reduced access, using telemedicine for diagnosis and follow-ups. The efficacy of remote screening and triage in the management of single or multiple VTDs was evaluated. Methods : We screened 41 subjects (19-85 years, 37% male, 17% Caucasian) (20 controls, 21 subjects). Demographics, 45-degree retinal photos, ganglion cell complex (GCC), and optic nerve head (ONH) images were collected using a non-contact puff-tonometer, nonmydriatic retinal camera, and an OCTA. Demographics and images were transmitted to two readers (onsite telemedicine screener [TS] and remote ophthalmologist [RO]) for triage. Triage was categorized: immediate referral to specialist, follow-up in person via clinic or telemedicine visit, or no follow-up necessary during COVID. Results : TS made 19 referrals (46%), 6 in person follow-ups (15%), 15 no follow-ups (37%);RO made 17 referrals (41%), 2 in person follow-ups (5%), 22 no follow-ups (54%). TS identified 12 subjects as possible VTD(s) while RO identified 11 subjects. TS and RO agreed on 8 glaucoma, 7 cataract, 3 DR, and 3 and 2 AMD cases, respectively. Glaucoma was identified using IOPs, retinal fundoscopy, and OCT imaging. Mean intraocular pressures were 12.9 and 15.7 (OD, OS) in glaucoma and 14.2 and 14.0 in controls. Fundoscopy was used for overall retinal health while OCT images were used to analyze GCC, ONH, nerve fiber layer, cup to disc ratio, and anterior chamber angles. AMD and DR were identified by fundoscopy and OCT imaging. 11 of the subjects were known clinic patients;both RO and TS referred all 11 to specialty clinics, matching the in-person clinic management. Conclusions : During the COVID pandemic, triaging patients can minimize person-toperson contact and help control the spread of the virus. Both readers agreed on the management and triage of a variety of patients with TS and RO differing only on 2 referrals and 4 in person follow-ups. Telemedicine is a promising alternative to in-person patient care for management and triage of vision threatening diseases. Further enrollment and follow-up are needed to increase robustness.
ABSTRACT
Purpose : The Centers for Disease Control reports 28.2% of surveyed US adults had reduced access to medical care (June/August 2020) due to the COVID-19 pandemic, with 8.9% reporting reduced access to vision care. A non-mydriatic digital retinal camera was piloted for deployment to the Emergency Department (ED) to help address this gap in vision care. Referrals for clinical follow-up in vision threatening diseases (VTDs) such as age-related macular degeneration, cataracts, diabetic retinopathy (DR), and glaucoma were assessed with human readers. Artificial Intelligence (AI) deep learning software was evaluated in known DR cases. Methods : 33 patients with known VTDs (48.48% male, avg 59.33 years) and 36 control subjects (41.67% male, avg 31.33 years) were included in tele-ophthalmology screening. A Canon CR-2 Plus AF non-mydriatic retinal camera captured 45-degree angle color and auto-fluorescence images of the eyes. Images (136 eyes) were graded by a certified telemedicine reader on site and an off-site clinical ophthalmologist following International Clinical Diabetic Retinopathy Disease Severity Scale (ICDRSS). Intergrader agreement between readers was evaluated with Cohen's kappa. An automated deep learning screening software optimized for DR (SELENA+, EyRIS Pte Ltd, Singapore) performed independent validation of readable color fundus images (17 eyes). Results : 5.07% of images were deemed unreadable by graders due to poor quality. Intergrader agreement for subject referral was κ = 0.710 (95% CI 0.545-0.875, p<.0005), with the clinical ophthalmologist generating more referrals than the telemedicine reader. Readers had 96.97% sensitivity (95% CI 91.12-1.028) and 72.22% specificity (95% CI 57.59- 86.85) in detecting referable disease. Positive predictive value was 76.19% (CI 63.31%- 89.07%) and negative predictive value was 96.30% (CI 89.17%- 1.034%). Of the 10 false positives, 6 were referred for rule out of glaucoma. Four had early stage cataracts that were deemed nonurgent. SELENA+ referred 100% of the known 9 DR patients. Conclusions : Tele-ophthalmology deployment in the ED helps limit patient and staff exposure to SARS-CoV-2 without sacrificing evaluation for VTDs. Tele-ophthalmology readers err on the side of caution to avoid missing VTD in a given patient. Use of AI can help keep strict adherence to referral guidelines.
ABSTRACT
Purpose : Coronavirus-19 (COVID-19) has had immense effects on access to medical care. Loss of medical care is alarming for individuals with pre-existing conditions like Type 1 Diabetes Mellitus (T1DM) which require uninterrupted care for best outcomes. Consistent care and medication use can reduce risk of developing diabetic retinopathy (DR) by 76% or progression by 54%. Healthy habits have also been linked to reduced risk of DR. The purpose of this study is to assess the effect of COVID-19 on care access and health habits in individuals with T1DM Methods : Surveys were administered from July-November of 2020 to multinational groups including the Children with Diabetes Conference (USA) and online groups, the American Diabetes Association and Connected in Motion Canadian Conference for T1DM. Data was collected from 125 patients from the USA, UK, Canada, and Bolivia. Age range was 5-81, and average years with T1DM was 17.9. The survey was online so responder rate is unclear, though response rates from previous surveys with similar groups averaged less than 10%. Results : While 73.6% of respondents saw an ophthalmologist within 1 year and 98.4% had medication without rationing, 40% postponed medical visits. Reasons for postponement included lack of appointments or transportation, financial issues and safety concerns. The majority (86.4%) were from the US where private insurance is prevalent, 12% were from Europe and Canada, where socialized medicine is common. Of respondents, 90.4% are willing to use telemedicine as an alternative. For most, diet remained the same (48.8%);25.6% stated their diet was healthier and 20% stated their diet was less healthy. 16.8% had problems accessing their usual foods due to the pandemic. A majority (55.2%) reported decreased exercise with 18.4% reporting more exercise. These overall trends were consistent across countries, and gender trends remained the same as pre-COVID, with women having better lifestyle and medical care adherence. Conclusions : Though patients delayed appointments, most were able to see an ophthalmologist and access medication. Physical activity levels decreased, though diets were mostly unchanged. In individuals with T1DM, disruptions in medical care and health habits can have negative long-term outcomes on overall and eye health. Telemedicine offers a promising solution for mitigating this risk.