Tissue inhibitor metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) best predicts the development of acute kidney injury

Background: Acute kidney injury (AKI) is routinely diagnosed by creatinine-based guidelines, which is sub-optimal marker after injury due to renal and non-renal factors. This has necessitated the need for more specific and sensitive biomarkers for early detection of AKI in at risk patients. This prospective cross-sectional study used the biomarkers of cell cycle arrest and Neutrophil Gelatinase Associated Lipocalin (NGAL) to assess AKI among hospitalized patients. Methods: We conveniently enrolled 151 in-patients at the Trauma and Specialist Hospital, Winneba in Ghana. Socio-demographic and clinical information were collected using structured questionnaires. Blood samples were collected for the estimation of serum creatinine, and AKI diagnosed and staged using the KDIGO guideline. Fresh urine samples were collected and urinary NGAL, TIMP-2 (tissue inhibitor metalloproteinase 2) and IGFBP-7 (insulin-like growth factor binding protein 7) were estimated using ELISA kits. Results: The cell cycle arrest biomarkers and NGAL were significantly (P < 0.001) higher among participants with AKI than those without AKI. [TIMP-2]*[IGFBP-7] showed the best diagnostic performance (AUC = 0.94, CI = 0.90-0.98) followed by [IGFBP-7]*NGAL] (AUC = 0.93, CI = 0.87-0.99), with NGAL having the least (AUC = 0.62, CI = 0.46-0.78). The cut-off for [TIMP-2]*[IGFBP-7] showed the best predictive ability (95.8% sensitivity, 77.2% specificity, 44.2% PPV and 99% NPV). The cut-off for NGAL, on the other hand, showed the least predictive ability (62.5% sensitivity, 42.5% specificity, 17.0% PPV and 85.7% NPV). Conclusion: Tissue inhibitor metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) best predicts the development of AKI, and can be used in high risk patients for early diagnosis of AKI.

Automated summary

This study assessed AKI among hospitalized patients using cell cycle arrest biomarkers and NGAL, with TIMP-2 and IGFBP7 showing the best predictive ability for AKI development. These biomarkers can be used for early diagnosis of AKI in high risk patients.