title: Digitization of Electrocardiogram From Telemetry Prior to In-hospital Cardiac Arrest: A Pilot Study.
abstract: BACKGROUND
  Analyzing telemetry electrocardiogram (ECG) data over an extended period is often time-consuming because digital records are not widely available at hospitals. Investigating trends and patterns in the ECG data could lead to establishing predictors that would shorten response time to in-hospital cardiac arrest (I-HCA). This study was conducted to validate a novel method of digitizing paper ECG tracings from telemetry systems in order to facilitate the use of heart rate as a diagnostic feature prior to I-HCA.
  
  
  METHODS
  This multicenter study used telemetry to investigate full-disclosure ECG papers of 44 cardiovascular patients obtained within 1 hr of I-HCA with initial rhythms of pulseless electrical activity and asystole. Digital ECGs were available for seven of these patients. An algorithm to digitize the full-disclosure ECG papers was developed using the shortest path method. The heart rate was measured manually (averaging R-R intervals) for ECG papers and automatically for digitized and digital ECGs.
  
  
  RESULTS
  Significant correlations were found between manual and automated measurements of digitized ECGs (p < .001) and between digitized and digital ECGs (p < .001). Bland-Altman methods showed bias = .001 s, SD = .0276 s, lower and upper 95% limits of agreement for digitized and digital ECGs = .055 and -.053 s, and percentage error = 0.22%. Root mean square (rms), percentage rms difference, and signal to noise ratio values were in acceptable ranges.
  
  
  CONCLUSIONS
  The digitization method was validated. Digitized ECG provides an efficient and accurate way of measuring heart rate over an extended period of time.
authors: School of Nursing, San Diego State University, San Diego, CA, USA mattin@mail.sdsu.edu.
authors: Mina
authors: M
authors: Attin
authors: College of Engineering, Bioengineering Program, San Diego State University, San Diego, CA, USA.
authors: Lu
authors: L
authors: Wang
authors: Department of Emergency Medicine, Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI, USA.
authors: S M Reza
authors: SM
authors: Soroushmehr
authors: Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA.
authors: Chii-Dean
authors: CD
authors: Lin
authors: Graduate School of Public Health, San Diego State University, San Diego, CA, USA.
authors: Hector
authors: H
authors: Lemus
authors: College of Literature, Science and Arts, University of Michigan, Ann Arbor, MI, USA.
authors: Maxwell
authors: M
authors: Spadafore
authors: Department of Computational Medicine and Bioinformatics, Department of Emergency Medicine, Department of Computer Science and Engineering, Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI, USA.
authors: Kayvan
authors: K
authors: Najarian
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004562:Electrocardiography / Q000379:methods*; D057286:Electronic Health Records; D005260:Female; D006323:Heart Arrest / Q000175:diagnosis*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D012815:Signal Processing, Computer-Assisted; D013686:Telemetry / Q000379:methods*
keywords: digitization; electrocardiogram; in-hospital cardiac arrest; telemetry