Using Area Under the Curve as a Decision Tool for Cytomegalovirus Viral Load Management for Kidney Transplant Patients Open Access

Gibby, Adriana C (2016)

Permanent URL: https://etd.library.emory.edu/concern/etds/qz20ss865?locale=en
Published

Abstract

Chronic kidney disease (CKD) can lead to end-stage renal disease (ESRD), which is the form of CKD where life can be maintained only by dialysis or transplantation.1 Transplantation has more benefits compared with chronic disease treatment. There is a significantly lower mortality associated with transplantation, and quality of life is better among transplant recipients.2 However, the current organ shortage is a limiting factor and it is crucial to ensure and protect the graft from rejection.3 Cytomegalovirus (CMV) is one of the most prevalent virus after transplantation that can cause significant morbidity, organ rejection, and adverse transplant outcomes.4 Donor and Recipient CMV status are risk factors for CMV infection by primary infection or by reactivation.5,6 Patients with Donor+/Recipient- match have shown being at the higher risk to develop CMV.7,8 To understand the CMV dynamics on kidney transplant patients, this study stratified risk groups based on CMV Donor/Recipient status (Donor (+)/Recipient (-): High Risk and Donor (+)/Recipient (-) or (+): Moderate Risk) and compared different immunosuppressive treatments and CMV viral load (amount of virus) in this population using area under the curve (AUC). AUC is the result of multiplying the individual CMV results and the different time points using a trapezoidal rule.9 AUC analysis allows establishing the magnitude of the quantity of CMV. A data dictionary has been designed as part of the data capture tool using REDCap to support clinical operations monitoring transplant patients focusing on Cytomegalovirus high-risk. Our study found a significant association between CMV high risk (Donor positive/Recipient negative) having a higher AUC in comparison to moderate risk (Donor negative/Recipient positive or Donor positive/Recipient positive). Results indicate no statistical significance among the different immunosuppressive treatments: Belatacept 1.0/1.1, Belatacept 2.0, Belatacept 2.2, Belatacept 2.3, and Tacrolimus 1.5 related, to CMV measurements. The different immunosuppressive treatments might not be a risk factor for the occurrence of CMV. In summary, developing AUC and applying data capture, as an analytical tool will support clinical operations to monitor transplant patients focusing on the high-risk groups and having efficient resource allocation.

Table of Contents

Chapter I: Introduction 8

Introduction and Rationale 8

Problem Statement 9

Specific Aims 9

Purpose Statement 9

Definitions of Acronyms 10

Chapter II: Literature Review 10

Introduction 10

CMV Occurrence and Impact in Transplantation 10

Strategies and Treatment Options 11

Area Under the Curve - Exploring New Methods 12

REDCap - A Data Capture Tool 13

Chapter III: Methodology 14

Introduction 14

Population and Sample 14

Research Design 15

Procedures 16

Instruments 16

Area Under the Curve (AUC) 17

REDCap as Data collection tool 19

Chapter IV: Results 19

Area Under the Curve (AUC) 19

Data Dictionary 23

Chapter V: Discussion 23

Appendix A 26

References 31

About this Master's Thesis

Rights statement
  • Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.
School
Department
Degree
Submission
Language
  • English
Research Field
Keyword
Committee Chair / Thesis Advisor
Committee Members
Partnering Agencies
Last modified

Primary PDF

Thumbnail Title Date Uploaded Actions
Using Area Under the Curve as a Decision Tool for Cytomegalovirus Viral Load Management for Kidney Transplant Patients () 2018-08-28 12:19:18 -0400

Supplemental Files

Thumbnail Title Date Uploaded Actions