Purpose: Among eyes with proliferative diabetic retinopathy, identify whether baseline characteristics impact the benefit of ranibizumab over panretinal photocoagulation (PRP) in DRCR.net Protocol S.
Methods: Participants had proliferative diabetic retinopathy, visual acuity of 20/320 or better, and no previous PRP. Eyes were randomized to PRP or intravitreous 0.5-mg ranibizumab.
Results: Ranibizumab was superior to PRP for change in visual acuity and development of vision-impairing central-involved diabetic macular edema over 2 years (P < 0.001). Among 25 characteristics, there were none in which participants assigned to PRP had superior outcomes relative to ranibizumab-assigned participants. The relative benefit of ranibizumab over PRP for change in visual acuity seemed greater in participants with higher mean arterial pressure (P = 0.03), without previous focal/grid laser (P = 0.03), with neovascularization of the disk and elsewhere on clinical examination (P = 0.04), and with more advanced proliferative diabetic retinopathy on photographs (P = 0.02). For development of vision-impairing central-involved diabetic macular edema, the relative benefit of ranibizumab over PRP seemed greater among nonwhite participants (P = 0.01) and those with higher mean arterial pressure (P = 0.01).
Conclusion: There were no characteristics identified in which outcomes were superior with PRP compared with ranibizumab. These exploratory analyses provide additional support that ranibizumab may be a reasonable alternative to PRP for proliferative diabetic retinopathy over a 2-year period.
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http://dx.doi.org/10.1097/IAE.0000000000002377 | DOI Listing |
Acta Biomater
December 2024
Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong First Medical University, Jinan, Shandong, 250021, China; Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan, Shandong, 250021, China. Electronic address:
Delayed wound healing in patients with diabetes remains a major health challenge worldwide. Uncontrolled bacterial infection leads to excessive production of reactive oxygen species (ROS) and persistent inflammatory responses, which seriously hinder conventional physiological healing processes after injury. Biofilms, as protective barriers for bacteria, pose a critical obstacle to effective bacterial eradication.
View Article and Find Full Text PDFAm J Ophthalmol
December 2024
Moorfields Eye Hospital NHS Foundation Trust, City Road London, EC1V 2PD, UK.
Am J Ophthalmol
December 2024
Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, 2-2 Yamadaoka, Suita, Osaka, Japan.
Int J Retina Vitreous
December 2024
Division of Medical Research, Faculty of Medicine and Health Sciences, SRM Medical College Hospital and Research Centre, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, 603203, India.
About one-third of individuals with diabetes develop diabetic retinopathy (DR), with one-tenth experiencing vision-threatening conditions such as diabetic macular edema (DME) or proliferative diabetic retinopathy (PDR). Current treatments only show recovery in 50% of cases, and the disease often remains asymptomatic. Therefore, novel early detection methods and new biomarkers are crucial.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Science and Information Engineering, Asia University, Taichung, 413, Taiwan.
Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring the critical importance of early detection in mitigating its impact. Addressing this challenge head-on, this study introduces an innovative deep learning framework tailored for DR diagnosis. The proposed framework utilizes the EfficientNetB0 architecture to classify diabetic retinopathy severity levels from retinal images.
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