Chronic kidney disease (CKD) is a strong risk factor for cardiovascular disease (CVD), but clinical kidney measures (eGFR and albuminuria) do not fully reflect the multiple aspects of kidney tubules influencing cardiovascular health. Applied methods are needed to integrate numerous tubule biomarkers into useful prognostic scores. In SPRINT participants with CKD at baseline (eGFRcr&cys <60mL/min/1.73m2), we measured eight biomarkers from urine (alpha-1, beta-2, umod, KIM-1, MCP-1, YKL-40, NGAL, IL-18) and two biomarkers from serum (iPTH, iFGF-23). We used an unsupervised method, exploratory factor analysis, to create summary scores of tubule health dimensions. Adjusted Cox models evaluated each tubule score with CVD events, heart failure (HF), and all-cause mortality. We examined CVD discrimination using Harrell’s C-statistic. Factor analysis of ten biomarkers from 2376 SPRINT-CKD participants identified four unique dimensions of tubular health: tubule injury/repair (NGAL, IL-18, YKL-40), tubule injury/fibrosis (KIM-1, MCP-1), tubule reabsorption (alpha-1, beta-2), and tubular reserve/mineral metabolism (umod, iPTH, iFGF-23). After adjustment for CVD risk factors, eGFR, and ACR, two of four tubule scores were associated with CVD (HR per SD, reabsorption: 1.21 (1.06–1.38), reserve: 1.24 (1.08–1.38)), one with HF (reserve: 1.41 (1.13–1.74)), and none with mortality. Compared to a base model (C-statistic = 0.674), adding eGFR and ACR improved the C-statistic (C=0.704, p=0.001); further adding tubule scores additionally improved the C-statistic (C=0.719, p=0.009). In the setting of CKD, dimensions of tubule health quantified using factor analysis improved CVD discrimination beyond contemporary kidney measures.