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• W4362602496 abstract "SLE is associated with a significant mortality, data from South Asia is limited. Thus, we analyzed the causes and predictors of mortality and hierarchical cluster-based survival in the Indian SLE Inception cohort for Research (INSPIRE).Data of SLE patients was extracted from the INSPIRE database. Univariate analyses for different disease variable associations with mortality was performed. Agglomerative unsupervised hierarchical cluster analysis was done using 25 variables defining SLE phenotype. Survival rates across clusters were assessed using non-adjusted and adjusted cox-proportion models.Among 2072 patients (median follow up of 18 months), there were 170 deaths (49.2 deaths per 1000 patient years). 47.1% of the deaths occurred in the first 6 months. The majority of patients (n = 87) died due to disease activity, 23 to infections, 24 to coexisting disease activity and infection and 21 to other causes. Pneumonia led to death in 24 patients. Clustering identified 4 clusters and the mean survival estimates were 39.26, 39.78, 37.69 and 35.86 months in clusters 1, 2, 3 and 4, respectively (p< 0.001). The adjusted HR(95%CI) were significant for cluster-4 [2.19 (1.44, 3.31)], low socio-economic-status [1.69 (1.22, 2.35)], number of BILAG-A [1.5 (1.29, 1.73)] and BILAG-B [1.15 (1.01, 1.3)] and need for hemodialysis [4.63 (1.87,11.48)].SLE in India has high early mortality and the majority of deaths occur outside the health care setting. Clustering using the clinically relevant variables at baseline may help identify individuals at high risk for mortality in SLE even after adjusting for high disease activity." @default.
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• W4362602496 date "2023-04-05" @default.
• W4362602496 modified "2023-10-01" @default.
• W4362602496 title "Clusters based on demography, disease phenotype, and autoantibody status predicts mortality in lupus: data from Indian lupus cohort (INSPIRE)" @default.
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• W4362602496 doi "https://doi.org/10.1093/rheumatology/kead148" @default.
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