Table 2.

Predictive ability of baseline clinical models for renal recovery and mortality

Outcome and Clinical ModelaAUROC (95% CI)Difference in AUROC's (95% CI)P Value
Recovery
 ATN0.77 (0.72 to 0.81)Reference model
 Reduced ATNb0.74 (0.69 to 0.79)−0.02 (−0.05 to -0.001)0.05
 LASSO modelc0.76 (0.71 to 0.81)−0.01 (−0.03 to 0.02)0.60
 Stepwise modelc0.75 (0.70 to 0.80)−0.02 (−0.05 to 0.01)0.16
 Parsimonious modeld0.73 (0.68 to 0.78)−0.03 (−0.06 to −0.01)0.02
Mortality
 ATN0.80 (0.76 to 0.85)Reference model
 Reduced ATNb0.75 (0.71 to 0.80)−0.03 (−0.05 to −0.01)<0.01
 Lasso modelc0.78 (0.74 to 0.83)−0.02 (−0.05 to 0.001)0.07
 Stepwise modelc0.77 (0.73 to 0.82)−0.03 (−0.05 to −0.01)<0.01
 Parsimonious modeld0.74 (0.69 to 0.78)−0.06 (−0.10 to −0.03)<0.001
  • ATN, Acute renal failure Trial Network; LASSO, least absolute shrinkage and selection operator; AUROC, area under the receiver-operating characteristic curve; 95% CI, 95% confidence interval.

  • a All models were built using the validation cohort consisting of 423 participants and had a Hosmer–Lemeshow P value >0.05 indicating model calibration. Variables included in various clinical models are shown in Supplemental Table 1.

  • b Variables that remained significant at P<0.05 in a multivariable model in the Biologic Markers of Recovery for the Kidney cohort.

  • c Variables deemed to be significant in a stepwise or penalized least absolute shrinkage and selection operator–based selection model.

  • d Four-variable parsimonious clinical model.