Digitization of Electrocardiogram From Telemetry Prior to In-hospital Cardiac Arrest: A Pilot Study. (March 2016)

• Record Type: Journal Article
• Authors: Attin, Mina; Wang, Lu; Soroushmehr, S. M. Reza; Lin, Chii-Dean; Lemus, Hector; Spadafore, Maxwell; Najarian, Kayvan
• Is Part Of: Biological research for nursing. Volume 18:Number 2(2016:Mar.)
• Page Start: 230
• Page End: 236
• Publication Date: 2016-03
• Subjects: electrocardiogram -- telemetry -- digitization -- in-hospital cardiac arrest; Clinical biochemistry -- Periodicals; Physiology, Pathological -- Periodicals; Nursing -- Periodicals; Nursing -- Research -- Periodicals; 610.73
• DOI: 10.1177/1099800415602092
• Languages: English
• ISSNs: 1099-8004

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. Conclusion: The digitization method was validated. Digitized ECG provides an efficient and accurate way of measuring heart rate over an extended period of time.