Improving clinical prediction rules in acute kidney injury with the use of biomarkers of cell cycle arrest: a pilot study

Abstract

Introduction: Early recognition of patients developing acute kidney injury (AKI) is of considerable interest, we report the first use of a combination of a clinical prediction rule with a biomarker in emergent adult medical patients to improve AKI recognition.

Methods: Single-centre prospective pilot study of medical admissions without AKI identified as high risk by a clinical prediction rule. Urine samples were obtained and tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) - biomarkers associated with cell cycle arrest, were measured.

Outcome: Creatinine-based KDIGO hospital-acquired AKI (HA-AKI).

Results: Of 69 patients recruited, HA-AKI developed in 13% (n = 9), in whom biomarker values were higher (median 0.43 (interquartile range (IQR) 0.21-1.25) vs. 0.07 (0.03-0.16) in cases without (p = 0.008). Peak rise in creatinine was higher in biomarker positive cases (median 30 μmol/L (7-72) vs. 1 μmol/L (0-16), p = 0.002). AUROC was 0.78 (95% CI 0.57-0.98). At the suggested cut-off (0.3) sensitivity for predicting AKI was 78% (95% CI 40-97%), specificity 89% (78-95%), positive predictive value 50% (31-69%) and negative predictive value 96% (89-99%).

Discussion: Addition of a urinary biomarker allows exclusion of a significant number of patients identified to be at higher risk of AKI by a clinical prediction rule.

Keywords: Acute kidney injury (AKI); insulin-like growth factor binding protein 7 (IGFBP7); tissue inhibitor of metalloproteinases-2 (TIMP-2).