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2 citation(s) found for "Joshi, Neil".

Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence
Zhou, Ashley , Li, Zhuolin , Paul, William , Burlina, Philippe , Mocharla, Rohita, Joshi, Neil, Gu, Sophie Z. , Nanegrungsunk, Onnisa , Bressler, Susan B., Cai, Cindy X. , Liu, T. Y. Alvin , Moini, Hadi, Bressler, Neil M. , Kong, Jun , Zhou, Ashley, Sepehrband, Farshid

JAMA Network Open | January 10, 2025 | Volume: 8 | Issue: 1 | Pages: e2453770

10.1001/jamanetworkopen.2024.53770 | PMID 39792386 Get It

ImportanceDetermining spectacle-corrected visual acuity (VA) is essential when managing many ophthalmic diseases. If artificial intelligence (AI) evaluations of macular images estimated this VA from a fundus image, AI might provide spectacle-corrected VA without technician costs, reduce visit time, or facilitate home monitoring of VA from fundus images obtained outside of the clinic.ObjectiveTo estimate spectacle-corrected VA measured on a standard eye chart among patients with diabetic macular edema (DME) in clinical practice settings using previously validated AI algorithms evaluating best-corrected VA from fundus photographs in eyes with DME.Design, Setting, and ParticipantsRetrospective cross-sectional evaluation of deidentified fundus photographs matched to spectacle-corrected VA determined by technicians on eye charts among patients with a history of DME based on optical coherence tomography and at least 2 visits within 1 to 6 months of each other at a university-based clinic between January 2014 and December 2022. Data were analyzed from January 2023 to October 2024.ExposurePreviously validated AI algorithm evaluation of fundus photographs.Main Outcomes and MeasuresAI-determined VA mean absolute error (MAE) compared with actual spectacle-corrected VA.ResultsAmong 141 patients, the mean (SD) age was 63 (13) years, 71 (50%) were male, 2 (1%) were Asian, 42 (30%) were Black or African American, and 88 (63%) were White. Among 282 eyes at visit 1, 66 had nonproliferative diabetic retinopathy (NPDR) and DME, 38 had proliferative diabetic retinopathy (PDR) and DME, 101 had NPDR and no DME, and 77 had PDR and no DME. Among 564 images (282 eyes) at both initial and follow-up visits, MAE (SD) among eyes with NPDR, with or without center-involved DME (CI-DME), was 1.16 (1.00) lines on the eye chart for VA between 20/10 and 20/20 (67 images), and 1.44 (1.15) lines for between VA 20/25 and 20/80 (231 images). MAE (SD) among eyes with PDR, with or without CI-DME, was 1.92 (1.08) lines for VA between 20/10 and 20/20 (50 images), and 1.42 (0.97) lines for spectacle-corrected VA between 20/25 and 20/80 (150 images). Only 65 images had VA 20/100 or worse, precluding meaningful analyses.Conclusions and RelevanceIn this cross-sectional study, AI evaluation of fundus photographs among patients with DME and VA 20/80 or better estimated spectacle-corrected VA within approximately 1 to 1.5 lines of actual spectacle-corrected VA. These results support use of AI evaluation of fundus photographs to determine spectacle-corrected VA among patients with DME globally, beyond ophthalmology offices.
Addressing healthcare disparities in homeless neurosurgical patients: A comprehensive literature review on strategies for equitable care and improved outcomes
Alan, Albert, Ennabe, Michelle, Withers, James, Joshi, Neil, Weinand, Martin

Surgical Neurology International | February 16, 2024 | Volume: 15 | Issue: No issue available | Pages: 49

10.25259/sni_549_2023 | PMID 38468673 Get It

Background: Homelessness is a growing concern in the US, with 3.5 million people experiencing it annually and 600,000 on any given night. Homeless individuals face increased vulnerability to 30-day hospital readmissions and higher mortality rates, straining the healthcare system and exacerbating existing disparities. This study aims to inform neurosurgeons on evidence-based strategies to reduce readmission and mortality rates among homeless patients by reviewing the literature on the impact of medical respite on 30-day readmission rates. The study aims to gauge the efficacy of medical respite in reducing hospital readmissions and improving health outcomes for homeless individuals. Methods: A comprehensive literature search was conducted across PubMed, Embase/Medline, and Cochrane databases, as well as consulting the National Institute for Medical Respite Care and the Department of Health Care Access and Information. Ten articles were chosen from an initial 296 to investigate the impact of respite programs on readmission rates among homeless patients. Results: Homeless patients experience high readmission rates due to various factors. Interventions such as respite programs and a comprehensive approach to healthcare can lower these rates. Collaboration between hospitals and medical respites has proven particularly effective. Conclusion: Inadequate healthcare for homeless individuals leads to increased readmissions, longer hospital stays, and higher costs. Medical respites are a viable solution, but limited resources hamper their effectiveness. Therefore, it is crucial to facilitate cooperation between hospitals, respites, and other entities. Future research should focus on disparity in neurosurgical procedures and explore alternative services. An interdisciplinary approach is key to addressing healthcare inequalities.