Exploring Potential Reasons for the Temporal Trend in Dialysis-Requiring AKI in the United States

Abstract

Background and objectives: The population incidence of dialysis-requiring AKI has risen substantially in the last decade in the United States, and factors associated with this temporal trend are not well known.

Design, setting, participants, & measurements: We conducted a retrospective cohort study using data from the Nationwide Inpatient Sample, a United States nationally representative database of hospitalizations from 2007 to 2009. We used validated International Classification of Diseases, Ninth Revision codes to identify hospitalizations with dialysis-requiring AKI and then, selected the diagnostic and procedure codes most highly associated with dialysis-requiring AKI in 2009. We applied multivariable logistic regression adjusting for demographics and used a backward selection technique to identify a set of diagnoses or a set of procedures that may be a driver for this changing risk in dialysis-requiring AKI.

Results: From 2007 to 2009, the population incidence of dialysis-requiring AKI increased by 11% per year (95% confidence interval, 1.07 to 1.16; P<0.001). Using backward selection, we found that the temporal trend in the six diagnoses, septicemia, hypertension, respiratory failure, coagulation/hemorrhagic disorders, shock, and liver disease, sufficiently and fully accounted for the temporal trend in dialysis-requiring AKI. In contrast, temporal trends in 15 procedures most commonly associated with dialysis-requiring AKI did not account for the increasing dialysis-requiring AKI trend.

Conclusions: The increasing risk of dialysis-requiring AKI among hospitalized patients in the United States was highly associated with the changing burden of six acute and chronic conditions but not with surgeries and procedures.

Keywords: acute kidney injury; cohort studies; dialysis; epidemiology; humans; incidence; renal dialysis; retrospective studies; sepsis; temporal trend.

Copyright © 2016 by the American Society of Nephrology.

Figures

Figure 1.

Multivariable logistic regression and a backward selection technique were applied to identify a final set of diagnoses to sufficiently account for the temporal trend in dialysis-requiring AKI. Listed diagnoses are covariates in the multivariable model (with calendar year as the primary predictor and dialysis-requiring AKI as the outcome), with each horizontal bar representing the odds ratio (OR; with 95% confidence interval [95% CI]) for the calendar year term after the corresponding diagnosis is dropped from the model. For example, after successively dropping external injuries and aspiration pneumonitis from the model, the OR for the year term remained <1, but after dropping mycoses, the model with the remaining six diagnoses resulted in the OR of the year term ≥1. The bracket indicates the six diagnoses selected for the final model. Error bars indicate 95% CIs. The embedded table displays the corresponding ORs with 95% CIs.