Table 4.

Improvement in CVD prediction by adding each subclinical measure to conventional risk factors

PredictorsΔC StatisticsaCategorical NRIContinuous NRIIDI
EventNoneventEventNonevent
CKDb
 CACc0.03 (0.01 to 0.06)0.11 (0.01 to 0.21)0.03 (−0.01 to 0.06)0.29 (0.15 to 0.43)0.15 (0.09 to 0.21)0.03 (0.02 to 0.04)
 IMTd0.002 (−0.01 to 0.01)0.03 (−0.02 to 0.08)−0.004 (−0.02 to 0.01)0.04 (−0.10 to 0.19)0.19 (0.14 to 0.25)0.003 (0.00 to 0.01)
 ABI0.01 (−0.004 to 0.03)−0.04 (−0.10 to 0.01)0.02 (−0.01 to 0.04)−0.16 (−0.32 to 0.01)0.08 (0.02 to 0.14)0.01 (0.003 to 0.02)
Non-CKD
 CACc0.04 (0.02 to 0.06)0.19 (0.12 to 0.26)−0.03 (−0.04 to −0.03)0.29 (0.18 to 0.40)0.26 (0.23 to 0.28)0.03 (0.02 to 0.03)
 IMTd0.01 (−0.001 to 0.01)−0.02 (−0.06 to 0.02)0.002 (−0.004 to 0.01)−0.03 (−0.15 to 0.08)0.14 (0.11 to 0.17)0.004 (0.002 to 0.01)
 ABI0.01 (−0.003 to 0.02)0.02 (−0.03 to 0.07)0.004 (−0.002 to 0.01)−0.001 (−0.11 to 0.13)0.08 (0.05 to 0.11)0.01 (0.01 to 0.02)
  • HR (95% CI) is shown.

  • a C statistic with only conventional predictors was 0.709 in the CKD group and 0.743 in the non-CKD group.

  • b CKD was defined as eGFR by the CKD-EPI creatinine equation<60 ml/min per 1.73 m2 or urinary albumin-to-creatinine ratio≥30 mg/g.

  • c ln(CAC score+1).

  • d Z score for overall maximal internal and common carotid IMT.