Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Authors: Aravind Lathika Rajendrakumar, Simona M. Hapca, Anand Thakarakkattil Narayanan Nair, Yu Huang, Mehul Kumar Chourasia, Ryan Shun-Yuen Kwan, Charvi Nangia, Moneeza K. Siddiqui, Prathiba Vijayaraghavan, Shona Z. Matthew, Graham P. Leese, Viswanathan Mohan, Ewan R. Pearson, Alexander S. F. Doney, Colin N. A. Palmer

Source: BMC Medicine, Vol 21, Iss 1, Pp 1-11 (2023)

Subject Terms: Diabetic retinopathy, Neutrophil–lymphocyte ratio, Competing risks, Subdistribution hazard ratio, Cause-specific hazard ratio, Medicine

File Description: electronic resource

Relation: https://doaj.org/toc/1741-7015

Access URL: https://doaj.org/article/f99aa2ef079f42f481821a664ed074e3

Tele-Ophthalmology Versus Face-to-Face Retinal Consultation for Assessment of Diabetic Retinopathy in Diabetes Care Centers in India: A Multicenter Cross-Sectional Study

Authors: Rajalakshmi, Ramachandran, UmaSankari, Ganesan, Prathiba, Vijayaraghavan, Anjana, Ranjit Mohan, Unnikrishnan, Ranjit, Venkatesan, Ulagamathesan, JebaRani, Saravanan, Shanthirani, Coimbatore Subramanian, Sivaprasad, Sobha, Mohan, Viswanathan

Source: Diabetes technology & therapeutics. 24(8):556-563

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100156833870.0x000001&indx=1&recIds=ETOCvdc_100156833870.0x000001

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification

Authors: Mookiah, Muthu Rama Krishnan, Hogg, Stephen, MacGillivray, Tom J, Prathiba, Vijayaraghavan, Pradeepa, Rajendra, Mohan, Viswanathan, Anjana, Ranjit Mohan, Doney, Alexander S., Palmer, Colin N.A., Trucco, Emanuele

Source: In Medical Image Analysis February 2021 68

Does tight control of systemic factors help in the management of diabetic retinopathy?
Dr in India (Written symposium)

Authors: Rajalakshmi, Ramachandran, Prathiba, Vijayaraghavan, Mohan, Viswanathan

Source: Indian journal of ophthalmology. 64(1):62-68

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCCN601318604&indx=1&recIds=ETOCCN601318604

Various models for diabetic retinopathy screening that can be applied to India.

Authors: Rajalakshmi, Ramachandran¹ drraj@drmohans.com, Prathiba, Vijayaraghavan¹, Rani, Padmaja Kumari², Mohan, Viswanathan³

Source: Indian Journal of Ophthalmology. Nov2021, Vol. 69 Issue 11, p2951-2958. 8p.

Subject Terms: *DIABETIC retinopathy, *PEOPLE with diabetes, *RETINAL imaging, *OUTDOOR photography, *DIABETES complications

Geographic Terms: INDIA

Wide-field imaging with smartphone based fundus camera: grading of severity of diabetic retinopathy and locating peripheral lesions in diabetic retinopathy

Authors: Rajalakshmi, Ramachandran, Mohammed, Rajah, Vengatesan, Kalaivani, PramodKumar, Thyparambil Aravindakshan, Venkatesan, Ulagamathesan, Usha, Manoharan, Arulmalar, Subramanian, Prathiba, Vijayaraghavan, Mohan, Viswanathan

Source: Eye; June 2024, Vol. 38 Issue: 8 p1471-1476, 6p

Comparison Among Methods of Retinopathy Assessment (CAMRA) Study: Smartphone, Nonmydriatic, and Mydriatic Photography

Authors: Ryan, Martha E., Rajalakshmi, Ramachandran, Prathiba, Vijayaraghavan, Anjana, Ranjit Mohan, Ranjani, Harish, Narayan, K.M. Venkat, Olsen, Timothy W., Mohan, Viswanathan, Ward, Laura A., Lynn, Michael J., Hendrick, Andrew M.

Source: In Ophthalmology October 2015 122(10):2038-2043

Does tight control of systemic factors help in the management ofdiabetic retinopathy?

Authors: Rajalakshmi, Ramachandran, Prathiba, Vijayaraghavan, Mohan, Viswanathan

Source: Indian journal of ophthalmology. 64(1):62-68

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100088355807.0x000001&indx=1&recIds=ETOCvdc_100088355807.0x000001

Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy.

Authors: Prathiba, Vijayaraghavan¹ drprathiba@drmohans.com, Rajalakshmi, Ramachandran¹, Arulmalar, Subramaniam¹, Usha, Manoharan¹, Subhashini, Radhakrishnan¹, Gilbert, Clare E.², Anjana, Ranjit Mohan¹, Mohan, Viswanathan¹

Source: Indian Journal of Ophthalmology. 2020 Supplement, Vol. 68, pS42-S46. 5p.

Subject Terms: *DIABETIC retinopathy, *RETINAL imaging, *CAMERAS, *EYE care, *TERTIARY care, *CONFIDENCE intervals, *RETINA, *CROSS-sectional method, *MYDRIATICS, *PRODUCT design, *EYE examination, *LONGITUDINAL method, RESEARCH evaluation

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study.

Authors: Mordi, Ify R., Trucco, Emanuele, Syed, Mohammad Ghouse, MacGillivray, Tom, Nar, Adi, Huang, Yu, George, Gittu, Hogg, Stephen, Radha, Venkatesan, Prathiba, Vijayaraghavan, Anjana, Ranjit Mohan, Mohan, Viswanathan, Palmer, Colin N.A., Pearson, Ewan R., Lang, Chim C., Doney, Alex S.F.

Source: Diabetes Care; 2022, Vol. 45 Issue 3, p710-716, 7p

Subject Terms: MAJOR adverse cardiovascular events, TYPE 2 diabetes, DISEASE risk factors, FRACTAL dimensions, CORONARY disease

Author′s reply

Authors: Rajalakshmi, Ramachandran, Prathiba, Vijayaraghavan, Mohan, Viswanathan

Source: Indian journal of ophthalmology. 64(6):477-478

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100088356809.0x000001&indx=1&recIds=ETOCvdc_100088356809.0x000001

Review of retinal cameras for global coverage of diabetic retinopathy screening

Authors: Rajalakshmi, Ramachandran, Prathiba, Vijayaraghavan, Arulmalar, Subramanian, Usha, Manoharan

Source: Eye; January 2021, Vol. 35 Issue: 1 p162-172, 11p

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