title: Statistics for critical clinical decision making based on readings of pairs of implanted sensors.
abstract: Low error rates are essential if lives of patients are to depend on readings of implanted sensors, such as glucose sensors in insulin-dependent diabetic patients. To verify the operation and to calibrate on demand an implanted sensor, it is necessary that calibration through a single, independent measurement involving withdrawal of only one sample of blood and its independent analysis be feasible. Such a one-point calibration must be accurate. Borrowing from nuclear reactor safety assurance, where a likelihood ratio test is applied to readings of pairs of pressure sensors for shutdown/no shutdown decisions, we apply a similar test to sensor pairs implanted in rats. We show, for five sets of glucose sensor pairs, calibrated in vivo by withdrawal of a single sample of blood, that application of the likelihood ratio test increases the fraction of the clinically correct readings from 92.4% for their averaged readings to 98.8%.
authors.affiliation: Department of Chemical Engineering, University of Texas at Austin 78712-1062, USA.
authors.forename: D W
authors.initials: DW
authors.lastname: Schmidtke
authors.forename: M V
authors.initials: MV
authors.lastname: Pishko
authors.forename: C P
authors.initials: CP
authors.lastname: Quinn
authors.forename: A
authors.initials: A
authors.lastname: Heller
mesh_terms: D000465:Algorithms; D000818:Animals; D015374:Biosensing Techniques; D001786:Blood Glucose / Q000032:analysis*; D002138:Calibration; D003658:Decision Making, Computer-Assisted; D004567:Electrodes, Implanted; D008297:Male; D051381:Rats; D017207:Rats, Sprague-Dawley
chemical_list: D001786:Blood Glucose