Computational Intelligence-Based Disease Severity Identification: A Review of Multidisciplinary Domains.

Disease severity identification using computational intelligence-based approaches is gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches are proving to be significant in the rapid and accurate diagnosis of several diseases. In addition to disease identification, these approaches have the potential to identify the severity of a disease. The problem of disease severity identification can be considered multi-class classification, where the class labels are the severity levels of the disease. Plenty of computational intelligence-based solutions have been presented by researchers for severity identification. This paper presents a comprehensive review of recent approaches for identifying disease severity levels using computational intelligence-based approaches. We followed the PRISMA guidelines and compiled several works related to the severity identification of multidisciplinary diseases of the last decade from well-known publishers, such as MDPI, Springer, IEEE, Elsevier, etc. This article is devoted toward the severity identification of two main diseases, viz. Parkinson's Disease and Diabetic Retinopathy. However, severity identification of a few other diseases, such as COVID-19, autonomic nervous system dysfunction, tuberculosis, sepsis, sleep apnea, psychosis, traumatic brain injury, breast cancer, knee osteoarthritis, and Alzheimer's disease, was also briefly covered. Each work has been carefully examined against its methodology, dataset used, and the type of disease on several performance metrics, accuracy, specificity, etc. In addition to this, we also presented a few public repositories that can be utilized to conduct research on disease severity identification. We hope that this review not only acts as a compendium but also provides insights to the researchers working on disease severity identification using computational intelligence-based approaches.

Follow-up Rates After Teleretinal Screening for Diabetic Retinopathy: Assessing Patient Barriers to Care.

Purpose: To study patient follow-up after they engage in a teleretinal screening program and to understand potential barriers to care. Methods: This was a retrospective analysis and a prospective study of telephone-based patient interviews of outpatients screened for diabetic retinopathy (DR) through a teleretinal referral system. Results: Of 2761 patients screened through a teleretinal referral program, 123 (4.5%) had moderate nonproliferative DR (NPDR), 83 (3.0%) had severe NPDR, and 31 (1.1%) had proliferative DR. Of the 114 patients with severe NPDR or worse, 67 (58.8%) saw an ophthalmologist within 3 months of referral. Eighty percent of interviewed patients reported they were not aware of the need for follow-up eye appointments. Conclusions: Of patients with severe retinopathy or worse, 58.8% presented for in-person evaluation and treatment within 3 months of screening. Although this result was negatively affected by factors related to the COVID-19 pandemic, key elements of patient education and improved referral strategies to facilitate in-person treatment are essential to improving follow-up after patients engage in telescreening.

Evaluating Adherence to Diabetic Retinopathy Care in an Urban Ophthalmology Clinic Utilizing the Compliance With Annual Diabetic Eye Exams Survey.

Introduction The objective of this study was to identify barriers that affect adherence to the management of diabetic retinopathy (DR) in an urban ophthalmology clinic. Patient beliefs regarding diabetic eye care, transportation to the eye clinic, the COVID-19 pandemic, and treatment with panretinal photocoagulation (PRP) or anti-vascular endothelial growth factor (anti-VEGF) injections were investigated. Materials and methods The original Compliance with Annual Diabetic Eye Exams Survey (CADEES) included 44 statements designed with a 5-point Likert scale to assess patients' beliefs and understanding of their eye health and the importance of diabetic eye examinations. This survey was modified to include additional statements regarding the COVID-19 pandemic and free-response questions about transportation barriers and patients' subjective experiences with PRP or anti-VEGF injections. A total of 365 patients with a diagnosis of any stage of DR from SLUCare Ophthalmology were identified as potential participants to complete the telephone survey. Patients were classified as non-adherent if they did not have a dilated eye examination within the past year, missed a scheduled follow-up appointment for DR care within the past year, or missed an appointment for anti-VEGF injections or PRP. The mean Likert scores for each CADEES statement were compared between the adherent and non-adherent groups using independent samples t-tests. Demographics and clinical indicators were also reported and compared between the two groups. Results Out of 365 patients, 68 completed the modified CADEES. Twenty-nine patients were adherent, and 39 patients were non-adherent. Results from six of the 54 CADEES statements were significantly different between the adherent and non-adherent groups. These statements addressed patients' perception of their eye health, self-confidence in making an eye appointment, knowing someone with diabetic eye complications, self-confidence in controlling blood sugar, ability to use public transportation during the COVID-19 pandemic, and prioritizing eye health during the pandemic. There were no significant differences in clinical indicators or demographics between the adherent and non-adherent groups. Of the participants, 39.7% offered reasons for why transportation to the eye clinic was difficult. Patients suggested three novel reasons for missing eye appointments that were not specifically addressed in the CADEES. Fourteen unique barriers were reported for non-adherence with PRP or anti-VEGF injections. Conclusions The CADEES is a thorough tool for evaluating social barriers impacting adherence with DR appointments in an urban ophthalmology clinic. The survey did not identify any clinical or demographic risk factors for non-adherence in this patient population. Decreased patient self-efficacy may lead to non-adherence with the management of DR. The COVID-19 pandemic impacted the adherence of a small percentage of patients.

Factors Associated with Follow-Up Adherence After Teleophthalmology for Diabetic Eye Screening Before and During the COVID-19 Pandemic.

Abstract Background: Follow-up adherence with in-person care is critical for achieving improved clinical outcomes in telemedicine screening programs. We sought to quantify the impact of the COVID-19 pandemic upon follow-up adherence and factors associated with follow-up adherence after teleophthalmology for diabetic eye screening. Methods: We retrospectively reviewed medical records of adults screened in a clinical teleophthalmology program at urban and rural primary care clinics between May 2015 and December 2020. We defined follow-up adherence as medical record documentation of an in-person eye exam within 1 year among patients referred for further care. Regression models were used to identify factors associated with follow-up adherence. Results: Among 948 patients, 925 (97.6%) had health insurance and 170 (17.9%) were referred for follow-up. Follow-up adherence declined from 62.7% (n = 52) prepandemic to 46.0% (n = 40) during the pandemic (p = 0.04). There was a significant decline in follow-up adherence among patients from rural (p < 0.001), but not urban (p = 0.72) primary care clinics. Higher median household income (odds ratio [OR] 1.68, 95% confidence interval [CI]: 1.19-2.36) and obtaining care from an urban clinic (OR 5.29, 95% CI: 2.09-13.43) were associated with greater likelihood of follow-up during the pandemic. Discussion: Follow-up adherence remains limited after teleophthalmology screening even in a highly insured patient population, with a further decline observed during the COVID-19 pandemic. Our results suggest that rural patients and those with lower socioeconomic status experienced greater barriers to follow-up eye care during the COVID-19 pandemic. Conclusions: Addressing barriers to in-person follow-up care is needed to effectively improve clinical outcomes after teleophthalmology screening.

Impact of the COVID-19 Pandemic on the Metabolic Control of Diabetic Patients in Diabetic Retinopathy and Its Screening.

(1) Background: Diabetic retinopathy (DR) is a complication of diabetes mellitus (DM), screening programs of which have been affected by the COVID-19 pandemic. The aim of the present study was to determine the impact of the COVID-19 pandemic on the screening of diabetes patients in our healthcare area (HCA). (2) Methods: We carried out a retrospective study of patients with DM who had attended the DR screening program between January 2015 and June 2022. We studied attendance, DM metabolic control and DR incidence. (3) Results: Screening for DR decreased in the first few months of the pandemic. The incidence of mild and moderate DR remained stable throughout the study, and we observed little increase in severe DR, proliferative DR and neovascular glaucoma during 2021 and 2022. (4) Conclusions: The current study shows that during the COVID-19 pandemic, screening program attendance decreased during the year 2020, which then recovered in 2021. Regarding the most severe forms of DR, a slight increase in cases was observed, beginning in the year 2021. Nevertheless, we aimed to improve the telemedicine systems, since the conditions of a significant proportion of the studied patients worsened during the pandemic; these patients are likely those who were already poorly monitored.