title: Automatic algorithm for monitoring systolic pressure variation and difference in pulse pressure.
abstract: BACKGROUND
  Difference in pulse pressure (dPP) reliably predicts fluid responsiveness in patients. We have developed a respiratory variation (RV) monitoring device (RV monitor), which continuously records both airway pressure and arterial blood pressure (ABP). We compared the RV monitor measurements with manual dPP measurements.
  
  
  METHODS
  ABP and airway pressure (PAW) from 24 patients were recorded. Data were fed to the RV monitor to calculate dPP and systolic pressure variation in two different ways: (a) considering both ABP and PAW (RV algorithm) and (b) ABP only (RV(slim) algorithm). Additionally, ABP and PAW were recorded intraoperatively in 10-min intervals for later calculation of dPP by manual assessment. Interobserver variability was determined. Manual dPP assessments were used for comparison with automated measurements. To estimate the importance of the PAW signal, RV(slim) measurements were compared with RV measurements.
  
  
  RESULTS
  For the 24 patients, 174 measurements (6-10 per patient) were recorded. Six observers assessed dPP manually in the first 8 patients (10-min interval, 53 measurements); no interobserver variability occurred using a computer-assisted method. Bland-Altman analysis showed acceptable bias and limits of agreement of the 2 automated methods compared with the manual method (RV: -0.33% +/- 8.72% and RV(slim): -1.74% +/- 7.97%). The difference between RV measurements and RV(slim) measurements is small (bias -1.05%, limits of agreement 5.67%).
  
  
  CONCLUSIONS
  Measurements of the automated device are comparable with measurements obtained by human observers, who use a computer-assisted method. The importance of the PAW signal is questionable.
authors.affiliation: Department of Anesthesiology, Johannes Gutenberg-University, Mainz, Germany.
authors.forename: Gunther
authors.initials: G
authors.lastname: Pestel
authors.forename: Kimiko
authors.initials: K
authors.lastname: Fukui
authors.forename: Volker
authors.initials: V
authors.lastname: Hartwich
authors.forename: Peter M
authors.initials: PM
authors.lastname: Schumacher
authors.forename: Andreas
authors.initials: A
authors.lastname: Vogt
authors.forename: Luzius B
authors.initials: LB
authors.lastname: Hiltebrand
authors.forename: Andrea
authors.initials: A
authors.lastname: Kurz
authors.forename: Yoshihisa
authors.initials: Y
authors.lastname: Fujita
authors.forename: Daniel
authors.initials: D
authors.lastname: Inderbitzin
authors.forename: Daniel
authors.initials: D
authors.lastname: Leibundgut
mesh_terms: D000005:Abdomen / Q000601:surgery; D000328:Adult; D000368:Aged; D000403:Airway Resistance / Q000502:physiology; D000465:Algorithms; D001331:Automation; D001794:Blood Pressure / Q000502:physiology*; D001810:Blood Volume / Q000502:physiology; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016343:Monitoring, Intraoperative / Q000379:methods*; D015588:Observer Variation; D011674:Pulse; D012015:Reference Standards; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology