• Aravind Lathika Rajendrakumar, Simona M Hapca, Anand Thakarakkattil Narayanan Nair, Yu Huang, Mehul Kumar Chourasia, Ryan Shun-Yuen Kwan, Charvi Nangia, SiddiquiMoneeza KMKDivision of Population Health and Genomics, Ninewells Hospital, University of Dundee, Dundee, UK.Wolfson Institute of Population Health, Queen Mary University of London, London, E1 4NS, UK., Prathiba Vijayaraghavan, Shona Z Matthew, Graham P Leese, Viswanathan Mohan, Ewan R Pearson, DoneyAlexander S FASFDivision of Population Health and Genomics, Ninewells Hospital, University of Dundee, Dundee, UK., and PalmerColin N ACNA0000-0002-6415-6560Division of Population Health and Genomics, Ninewells Hospital, University of Dundee, Dundee, UK. c.n.a.palmer@dundee.ac.uk..
• Division of Population Health and Genomics, Ninewells Hospital, University of Dundee, Dundee, UK.
• Bmc Med. 2023 Aug 10; 21 (1): 304304.

BackgroundDiabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil-lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.MethodsThe incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.ResultsWe analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28-2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70-2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR.ConclusionsThe current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.© 2023. The Author(s).

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