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Using Machine Learning to Predict Acute Kidney Injuries Among Patients Treated with Empiric Antibiotics

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자료유형	E-Book
개인저자	Rutter, W. Cliff.
단체저자명	University of Kentucky.
서명/저자사항	Using Machine Learning to Predict Acute Kidney Injuries Among Patients Treated with Empiric Antibiotics.
발행사항	[S.l.] : University of Kentucky., 2018
발행사항	Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항	242 p.
소장본 주기	School code: 0102.
ISBN	9780438239302
일반주기	Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. Advisers: David S. Burgess
요약	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
요약	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.
요약	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
요약	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
요약	Chapter 4 describes a study in which patients receiving TZP or ampicillinsulbactam (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 betal
요약	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. A
요약	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.
일반주제명	Pharmaceutical sciences.
언어	영어
기본자료 저록	Dissertation Abstracts International79-12B(E). Dissertation Abstract International
대출바로가기	http://www.riss.kr/pdu/ddodLink.do?id=T15001223