Digitization of Electrocardiogram From Telemetry Prior to In-hospital Cardiac Arrest

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.

Keywords

electrocardiogram telemetry digitization in-hospital cardiac arrest

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