PROJECT SUMMARY/ABSTRACT
Catheter-related bloodstream infection (CRBSI), also called catheter-related sepsis, is one of the most frequent,
lethal, and costly complications of central venous catheterization. CRBSI affects hundreds of millions of people
worldwide; in the U.S. alone, it affects more than 250,000 patients yearly. These infections are mostly caused
by the migration of microorganisms found on the patient's skin flora at the catheter insertion site. Tremendous
efforts have been undertaken to reduce catheter-related sepsis, including improvements to the catheter insertion
guidelines and the development of dressings impregnated with antibiotics. These methods help reduce the
number of bacteria on the patient's skin but do not eliminate them. No available catheter dressing enables
automated and early detection of bacterial growth at the catheter insertion site. Such catheter dressing is a
critical need for early detection of CRBSI, allowing for the removal/replacement of the catheter, and, as needed,
for early treatment of patients with tailored antibiotic therapy. In addition, it remains a clinical challenge to detect
bacterial colonization on the skin at early stages without catheter removal due to the human skin's highly flexible
and topographical nature. Flexible biosensors that provide conformal and seamless adherence to the skin can
help, but previous studies on the merits of wearable and flexible sensors to detect bacterial infection have been
limited to wound infections measured by indirect parameters (e.g., pH) that are subject to change with dietary
restrictions and not specific to bacterial infection. Therefore, a significant knowledge gap exists in the use of
wearable and flexible sensors integrated with electronics for real-time monitoring of direct bacterial growth at the
catheter insertion site for the early detection of CRBSI-related infection risks. The overall objective of this
application is to address this need and knowledge gap by developing a fully integrated, wirelessly operated
catheter dressing that is capable of monitoring bacterial growth at the catheter insertion site in real-time and non-
invasively to enable automated early detection of infection originating from the skin. The central hypothesis is
that the electrochemical activity of live bacteria at the catheter insertion site can be directly measured, and
acquired data can be classified using machine learning, thereby allowing precise monitoring of extraluminal
contamination in real-time. To attain the overall objective, the following two specific aims will be pursued: Aim 1:
Develop an integrated catheter dressing (ICD) capable of real-time monitoring of bacterial growth at the catheter
insertion site. Aim 2: Validate and optimize the ICD for early detection of catheter-related sepsis on a skin
phantom and an animal model. These aims will be accomplished by a team of skilled experts and excellent
resources. The proposed research is significant because the ICD can transform the current point-of-care
practices, ultimately has the potential to reduce infection risks, health care costs, and morbidity and mortality
rates related to CRBSI, and monitor the infection status in real-time, non-invasively, and at the point of care.