title: Accurate automated apnea analysis in preterm infants.
abstract: OBJECTIVE
  In 2006 the apnea of prematurity (AOP) consensus group identified inaccurate counting of apnea episodes as a major barrier to progress in AOP research. We compare nursing records of AOP to events detected by a clinically validated computer algorithm that detects apnea from standard bedside monitors.
  
  
  METHODS
  Waveform, vital sign, and alarm data were collected continuously from all very low-birth-weight infants admitted over a 25-month period, analyzed for central apnea, bradycardia, and desaturation (ABD) events, and compared with nursing documentation collected from charts. Our algorithm defined apnea as > 10 seconds if accompanied by bradycardia and desaturation.
  
  
  RESULTS
  Of the 3,019 nurse-recorded events, only 68% had any algorithm-detected ABD event. Of the 5,275 algorithm-detected prolonged apnea events > 30 seconds, only 26% had nurse-recorded documentation within 1 hour. Monitor alarms sounded in only 74% of events of algorithm-detected prolonged apnea events > 10 seconds. There were 8,190,418 monitor alarms of any description throughout the neonatal intensive care unit during the 747 days analyzed, or one alarm every 2 to 3 minutes per nurse.
  
  
  CONCLUSIONS
  An automated computer algorithm for continuous ABD quantitation is a far more reliable tool than the medical record to address the important research questions identified by the 2006 AOP consensus group.
authors.affiliation: Division of Neonatology, Department of Pediatrics, University of Virginia, Charlottesville, Virginia.
authors.forename: Brooke D
authors.initials: BD
authors.lastname: Vergales
authors.affiliation: Division of Neonatology, Department of Pediatrics, University of Virginia, Charlottesville, Virginia.
authors.forename: Alix O
authors.initials: AO
authors.lastname: Paget-Brown
authors.affiliation: Department of Physics, The College of William and Mary, Williamsburg, Virginia.
authors.forename: Hoshik
authors.initials: H
authors.lastname: Lee
authors.affiliation: Department of Internal Medicine, University of Virginia, Charlottesville, Virginia.
authors.forename: Lauren E
authors.initials: LE
authors.lastname: Guin
authors.affiliation: Department of Internal Medicine, University of Virginia, Charlottesville, Virginia.
authors.forename: Terri J
authors.initials: TJ
authors.lastname: Smoot
authors.affiliation: Department of Internal Medicine, University of Virginia, Charlottesville, Virginia.
authors.forename: Craig G
authors.initials: CG
authors.lastname: Rusin
authors.affiliation: Department of Chemical Engineering, University of Virginia, Charlottesville, Virginia.
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Clark
authors.affiliation: Department of Physics, The College of William and Mary, Williamsburg, Virginia.
authors.forename: John B
authors.initials: JB
authors.lastname: Delos
authors.affiliation: Division of Neonatology, Department of Pediatrics, University of Virginia, Charlottesville, Virginia.
authors.forename: Karen D
authors.initials: KD
authors.lastname: Fairchild
authors.affiliation: Department of Internal Medicine, University of Virginia, Charlottesville, Virginia.
authors.forename: Douglas E
authors.initials: DE
authors.lastname: Lake
authors.affiliation: Department of Internal Medicine, University of Virginia, Charlottesville, Virginia.
authors.forename: Randall
authors.initials: R
authors.lastname: Moorman
authors.affiliation: Division of Neonatology, Department of Pediatrics, University of Virginia, Charlottesville, Virginia.
authors.forename: John
authors.initials: J
authors.lastname: Kattwinkel
mesh_terms: D000465:Algorithms; D001049:Apnea / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D007235:Infant, Premature, Diseases / Q000175:diagnosis*; D007363:Intensive Care Units, Neonatal; D008991:Monitoring, Physiologic / Q000379:methods*; D010992:Plethysmography, Impedance