Date Available
4-27-2018
Year of Publication
2018
Degree Name
Doctor of Philosophy (PhD)
Document Type
Doctoral Dissertation
College
Pharmacy
Department/School/Program
Pharmaceutical Sciences
First Advisor
Dr. David S. Burgess
Second Advisor
Dr. Jeffrey C. Talbert
Abstract
Acute kidney injury (AKI) is a significant adverse effect of many medications that leads to increased morbidity, cost, and mortality among hospitalized patients. Recent literature supports a strong link between empiric combination antimicrobial therapy and increased AKI risk. As briefly summarized below, the following chapters describe my research conducted in this area.
Chapter 1 presents and summarizes the published literature connecting combination antimicrobial therapy with increased AKI incidence. This chapter sets the specific aims I aim to achieve during my dissertation project.
Chapter 2 describes a study in which patients receiving vancomycin (VAN) in combination with piperacillin-tazobactam (TZP) or cefepime (CFP). I matched over 1,600 patients receiving both combinations and found a significantly lower incidence of AKI among patient receiving the CFP+VAN combination when controlling for confounders. The conclusion of this study is that VAN+TZP has significantly increased risk of AKI compared to CFP+VAN, confirming the results of previous literature.
Chapter 3 presents a study of patients receiving VAN in combination with meropenem (MEM) or TZP. This study included over 10,000 patients and used inverse probability of treatment weighting to conserve data for this population. After controlling for confounders, VAN+TZP was associated with significantly more AKI than VAN+MEM. This study demonstrates that MEM is clinically viable alternative to TZP in empiric antimicrobial therapy.
Chapter 4 describes a study in which patients receiving TZP or ampicillin-sulbactam (SAM) with or without VAN were analyzed for AKI incidence. The purpose of this study was to identify whether the addition of a beta-lactamase inhibitor to a beta-lactam increased the risk of AKI. This study included more than 2,400 patients receiving either agent and found that there were no differences in AKI among patients receiving SAM or TZP; however, AKI was significantly more common in the TZP group when stratified by VAN exposure. This study shows that comparisons of TZP to other beta-lactams without beta-lactamase inhibitors are valid.
Chapter 5 presents a study of almost 30,000 patients who received combination antimicrobial therapy over an 8-year period. This study demonstrates similar AKI incidence to previous literature and the studies presented in the previous chapters. Additionally, the results of the predictive models suggest that further work in this research area is needed.
The studies conducted present a clear message that patients receiving VAN+TZP are at significantly greater risk of AKI than alternative regimens for empiric coverage of infection.
Digital Object Identifier (DOI)
https://doi.org/10.13023/ETD.2018.176
Recommended Citation
Rutter, Wilbur Cliff IV, "USING MACHINE LEARNING TO PREDICT ACUTE KIDNEY INJURIES AMONG PATIENTS TREATED WITH EMPIRIC ANTIBIOTICS" (2018). Theses and Dissertations--Pharmacy. 86.
https://uknowledge.uky.edu/pharmacy_etds/86