[Acute kidney injury and tubular biomarkers after hematopoietic stem cell transplantation].

AIM

To determine the value of molecular biomarkers (BMs) associated with tubular epithelial damage in developing and predicting acute kidney injury (AKI) after hematopoietic stem cell transplantation (HSCT).

SUBJECTS AND METHODS

The open-label observational prospective study enrolled 90 patients (46 males and 44 females) who had undergone HSCT. The concentrations of BMs (calbindin, clusterin, interleukin-18 (IL-18), kidney injury molecules-1 (KIM-1), glutathione S-transferase-π (GST-π), and monocyte chemoattractant protein-1 (MCP-1) were measured in urinary samples 7 days before HSCT (week 0) and at weeks 1, 2, 3, 4, and 5. Main clinical parameters were simultaneously monitored. AKI was diagnosed and stratified according to the Kidney Disease Improving Global Outcomes (KDIGO) guidelines.

RESULTS

At weeks 1, 2, 3, 4, and 5 after HSCT, the proportion of AKI cases was 7.8, 8.9, 12.5, 27.3, and 35.9%, respectively. The elevated urinary levels of BMs (above the median) were found to be substantially more common than AKI cases. The urinary excretion of the majority of BMs dramatically increased in the early HSCT period. The median number of simultaneously elevated BMs was 3 (2; 5) during the entire follow-up period. Clusterin, MCP-1 and KIM-1 positively and significantly correlated with serum creatinine at the week following the determination of BMs in the multivariate linear regression models adjusted for other confounders. The higher urinary KIM-1 and/or MCP-1 excretion regardless of other clinical indicators was associated with the higher relative risk (RR) of AKI, which increased by 2.3 times with a rise in one of these indicators and by 3.4 times with a rise in both indicators.

CONCLUSION

Multiple renal toxic effects after HSCT result in a substantial and simultaneous elevation of urinary excretion of BMs for tubular damage. Among the BMs studied, KIM-1 and MCP-1 seem to be the most suitable molecules for assessing the risk of AKI in this cohort of patient within the predictive diagnostic approach.