This proposal is designed to provide the necessary knowledge, skills, and experience required to facilitate the transition of Andrew Chou, MD, from junior to independent investigator in the field of antibiotic- resistant infections. Dr. Chou is a well-trained infectious diseases specialist with graduate-level education and postdoctoral training in microbiology and microbial genomics. He has been studying multidrug-resistant organisms (MDRO) since 2009 and has a demonstrated history of dedication to a career in research and to the Veterans Health Administration (VHA). Dr. Chou has identified a mentoring committee consisting of senior investigators who have demonstrated success in mentoring junior investigators to independence. Barbara W. Trautner, MD, PhD, associate professor of Medicine (Infectious Diseases) and faculty at the Center for Innovations in Quality, Effectiveness, and Safety (IQuESt) at the Houston VA and Baylor College of Medicine (BCM), will serve as the primary mentor. The co-mentors are: 1) Lynn Zechiedrich, PhD, an expert in mechanisms of antibiotic resistance and systems biology; 2) Elizabeth Chiao, MD, MPH, an expert in using large databases to study viral-associated malignancies and board-certified in both infectious diseases and oncology; 3) Richard Sucgang, PhD, an expert in bioinformatics of antibiotic resistance; and 4) Peter Richardson, PhD, an expert in mathematical statistics and probability modeling. Dr. Chou has a history of productivity with the primary mentor and multiple co-mentors, including publications in studying Klebsiella pneumoniae virulence factors within VHA, bloodstream infections due to gram-negative bacteria, and an outbreak of carbapenem-resistant Enterobacteriaceae (CRE). To expand his skill set, Dr. Chou will pursue a Master of Science in biostatistics, studying the data science track and biostatistics. Antibiotic resistance is an important health concern in the United States and within VHA. CRE is 1 of the most dangerous antibiotic-resistant organisms because nearly half of all patients with CRE bloodstream infections die. CRE infections are resistant to all or nearly all antibiotics, often are treated with last-line antibiotics that are associated with severe side-effects, and can lead to hospital outbreaks. CRE infections incur significant morbidity and mortality, yet optimal prevention and treatment of CRE are unknown. The published report, Establishing the Research Agenda for Preventing Transmission of MDRO in Acute-Care Settings in VHA, identified studying screening strategies to identify Veterans asymptomatically colonized with CRE as a research priority. Determining the optimum treatment of CRE is challenging because patients with CRE infections often have complex comorbidities that exclude them from clinical trials. The project objective is to combat CRE within VHA by (1) developing novel, targeted surveillance strategies that identify Veterans at high risk for CRE colonization; and (2) identifying which antibiotic regimens are associated with the most desirable clinical outcomes (ie, clinical cure without adverse events) in Veterans with CRE infections. Aim 1 will create the VHA CRE colonization risk-stratification tool for the national VHA population using bioinformatics to analyze large-scale clinical VHA databases. Aim 2 will develop best practices for treatment of CRE bloodstream infection by applying biostatistical techniques to VHA databases to compare newer antibiotics to standard therapy, monotherapy vs. combination antibiotic therapy, and short- course vs. prolonged-course duration of antibiotic therapy. Aim 3 will be to conduct a pilot intervention of 3 different CRE surveillance strategies: passive surveillance, surveillance targeted by clinical risk factors, and surveillance targeted to patients with Clostridioides difficile infection. The environment at BCM is ideal for fostering the training of junior physician investigators. Dr. Chou will benefit from strong institutional support, outstanding mentoring, and a clear path to independence.

Antibiotic-resistant bacteria are a major public health concern. These bacteria cause infections that are often difficult to treat and lead to serious infections. Carbapenem-resistant Enterobacteriaceae (CRE) is a severe type of antibiotic-resistant bacteria because it is resistant to almost all antibiotics and can be very deadly. It is very important to identify which patients are at risk for CRE and to identify the best treatment for CRE. We propose to develop and test a tool that predicts whether a person carries CRE, and to identify the best treatment options for CRE infections. We will use large databases to find patients at risk for CRE and patient who have CRE infections. We will use computer programming and biostatistics to identify which patients are at risk and which treatments work best. At the end of the proposed work, we will have identified new avenues to prevent person-to-person transmission of CRE and improve therapy of CRE infections.