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James M Lindauer

Publications and source records attributed to James M Lindauer.

2 recordsLinked to original sources

Comparability of 12-lead ECGs derived from EASI leads with standard 12-lead ECGS in the classification of acute myocardial ischemia and old myocardial infarction.

We compared 12-lead electrocardiograms (ECGs) derived with an improved transformation matrix from EASI leads and standard 12-lead ECGs in the detection of acute myocardial ischemia and old infarction (MI). For the ischemia test, we used ECGs of 40 patients recorded prior to and at peak inflation during percutaneous transluminal coronary angioplasty, and for old MI we used test ECGs of 382 non-MI subjects and of 472 patients with prior MI documented by enzyme findings. Two experienced ECG readers served as separate, independent standards for lead-set comparisons, and the Philips ECG analysis program also classified the ECGs. The results showed no significant differences between the two lead sets in the detection of acute inflation-induced ischemia or of old MI according to coding by the electrocardiographers or the computer program. No significant differences were found between the electrocardiographers and the lead sets for acute ischemia. Classification differences between the electrocardiographers were larger than those between the lead sets for acute and old MI and were significant for the latter (P <.001). A more detailed comparison of the lead sets suggested a possible need for modified old-MI criteria and optimization of ST classification thresholds for acute ischemic injury, specific for the EASI 12-lead ECG. We conclude that the EASI-derived 12-lead ECG deserves serious consideration as an alternative to the standard 12-lead ECG in emergency situations and for monitoring in acute-care setting.

Electrocardiography↗

A software-based pacemaker pulse detection and paced rhythm classification algorithm.

A new pacemaker pulse detection and paced electrocardiogram (ECG) rhythm classification algorithm with high sensitivity and positive predictive value has been implemented as part of the Philips Medical Systems' (Andover, MA) ECG analysis program. The detection algorithm was developed on 1,108 paced ECGs with 16,029 individual pulse locations. It operates on 12-lead, 500 sample per second, 150 Hz low-pass filtered ECG signals. Even after low-pass filtering, this algorithm distinguishes between pacemaker pulses and narrow QRS complexes from newborns. An individual pulse detection sensitivity of 99.7% and positive predictive value of 99.5% was obtained by the multi-lead detector. A 10-second, 12-lead ECG database (n = 13,155) of paced (n = 2,190), non-paced adult (n = 8,070), non-paced pediatric (n = 1,209) and "noisy" ECGs with spike noise and muscle artifact (n = 1,686) was assembled and annotated by two readers. The overall performance in identification of an ECG as paced with any pacing present versus non-paced is 97.2% in sensitivity and 99.9% in specificity. The paced ECGs were classified by the mode in which the beats were paced, such as, atrial, ventricular, A-V dual, or dual/inhibited chamber (ie, combinations of atrial, ventricular and dual) pacing. An algorithm was developed for paced rhythm classification. The algorithm performance results show that accurate and robust pacemaker pulse detection and classification can be done in software on diagnostic bandwidth ECG signals.

Adult↗