title: Automated blood sampling and glucose sensing in critical care settings.
abstract: BACKGROUND
  Tight glycemic control (TGC) studies in intensive care units (ICU) have shown substantial improvements in clinical outcomes. However, implementation of TGC in ICU practice is partly constrained by the lack of automated continuous blood glucose monitoring systems that can facilitate clinically accurate feedback of glycemic data. The aim of this work is to develop a portable automated blood sampling system for integration with a glucose sensor for use in critical care settings.
  
  
  METHODS
  clinical prototypes for glucose sensing in blood were developed based on two distinct technologies: mid-infrared laser absorption spectroscopy and electrochemistry. Concurrently, an automated peripheral venous blood sampling system was developed for integration with the glucose sensing system.
  
  
  RESULTS
  The glucose sensing prototypes were validated clinically with various biological samples in a continuous mode. A customized micropump was employed in conjunction with a novel peripheral venous catheter system to automatically sample blood from the subject's forearm. Microvolumes of blood were sampled in continuous and intermittent modes at clinically relevant user-defined frequencies. The clinical feasibility of blood sampling, along with continuous glucose sensing, was demonstrated.
  
  
  CONCLUSIONS
  Cascade's automated peripheral venous blood sampling system, in combination with a flow-through glucose sensor system, offers several advantages over current state-of-the-art systems. This includes the potential for significantly improved workflow in the ICU, minimal discomfort to the patient, and accurate glucose measurement in whole blood, thus helping achieve tight glycemic control.
authors.affiliation: Cascade Metrix, Inc., Indianapolis, Indiana 46202, USA. kkunjan@cascademetrix.com
authors.forename: Kislaya
authors.initials: K
authors.lastname: Kunjan
authors.forename: Frank P
authors.initials: FP
authors.lastname: Lloyd