AKI in the very elderly patients without preexisting chronic kidney disease: a comparison of 48-hour window and 7-day window for diagnosing AKI using the KDIGO criteria.

OBJECTIVES

To compare the differences between the Kidney Disease Improving Global Outcomes (KDIGO) criteria of the 48-hour window and the 7-day window in the diagnosis of acute kidney injury (AKI) in very elderly patients, as well as the relationship between the 48-hour and 7-day windows for diagnosis and 90-day mortality.

PATIENTS AND METHODS

We retrospectively enrolled very elderly patients (≥75 years old) from the geriatrics department of the Chinese PLA General Hospital between January 2007 and December 2015. AKI patients were divided into 48-hour and 7-day groups by their diagnosis criteria. AKI patients were divided into survivor and nonsurvivor groups by their outcomes within 90 days after diagnosis of AKI.

RESULTS

In total, 652 patients were included in the final analysis. The median age of the cohort was 87 (84-91) years, the majority (623, 95.6%) of whom were male. Of the 652 AKI patients, 334 cases (51.2%) were diagnosed with AKI by the 48-hour window for diagnosis, while 318 cases (48.8%) were by the 7-day window for diagnosis. The 90-day mortality was 42.5% in patients with 48-hour window AKI and 24.2% in patients with 7-day window AKI. Kaplan-Meier curves showed that 90-day mortality was lower in the 7-day window AKI group than in the 48-hour window AKI group (log rank: <0.001). Multivariate analysis by the Cox model revealed that 48-hour window for diagnosis hazard ratio (HR=1.818; 95% CI: 1.256-2.631; =0.002) was associated with higher 90-day mortality.

CONCLUSION

The 90-day mortality was higher in 48-hour window AKI than in 7-day window AKI in very elderly patients. The 48-hour KDIGO window definition may be less sensitive. The 48-hour KDIGO window definition is significantly better correlated with subsequent mortality and is, therefore, still appropriate for clinical use. Finding early, sensitive biomarkers of kidney damage is a future direction of research.