Biomedical subjects

Sophia H Zhou

Publications and source records attributed to Sophia H Zhou.

4 recordsLinked to original sources

PubMed2006

An algorithm for continuous real-time QT interval monitoring.

QT interval measurement in the patient monitoring environment is receiving much interest because of the potential for proarrhythmic effects from both cardiac and noncardiac drugs. The American Heart Association and American Association of Critical Care Nurses practice standards for ECG monitoring in hospital settings now recommend frequent monitoring of QT interval when patients are started on a potentially proarrhythmic drug. We developed an algorithm to continuously measure QT interval in real-time in the patient monitoring setting. This study reports our experience in developing and testing this automated QT algorithm. Compared with the environment of resting ECG analysis, real-time ECG monitoring has a number of challenges: significantly more amounts of muscle and motion artifact, increased baseline wander, a varied number and location of ECG leads, and the need for trending and for alarm generation when QT interval prolongation is detected. We have used several techniques to address these challenges. In contiguous 15-second time windows, we average the signal of tightly clustered normal beats detected by a real-time arrhythmia-monitoring algorithm to minimize the impact of artifact. Baseline wander is reduced by zero-phase high-pass filtering and subtraction of isoelectric points as determined by median signal values in a localized region. We compute a root-mean-squared ECG waveform from all available leads and use a novel technique to measure the QT interval. We have tested this algorithm against standard and proprietary ECG databases. Our real-time QT interval measurement algorithm proved to be stable, accurate, and able to track changing QT values.

Algorithms↗

PubMed2006

Relation of QT interval measurements to evolving automated algorithms from different manufacturers of electrocardiographs.

QT-interval measurements have clinical importance for the electrocardiographic recognition of congenital and acquired heart disease and as markers of arrhythmogenic risk during drug therapy, but software algorithms for the automated measurement of electrocardiographic durations differ among manufacturers and evolve within manufacturers. To compare automated QT-interval measurements, simultaneous paired electrocardiograms were obtained in 218 subjects using digital recorders from the 2 major manufacturers of electrocardiographs used in the United States and analyzed by 2 currently used versions of each manufacturer's software. The 4 automated QT and QTc durations were examined by repeated-measures analysis of variance with post hoc testing. Significantly larger automated QT-interval measurements were found with the most recent software of each manufacturer (12- to 24-ms mean differences from earlier algorithms). Systematic differences in QT measurements between manufacturers were significant for the earlier algorithms (11-ms mean difference) but not for the most recent software (1.3-ms mean difference). Similar relations were found for the rate-corrected QTc, with large mean differences between earlier and later algorithms (15 to 26 ms). Although there was a <2-ms mean difference between the most recent automated QTc measurements of the 2 manufacturers, the SD of the difference was 12 ms. In conclusion, reference values for automated electrocardiographic intervals and serial QT measurements vary among electrocardiographs and analysis software. Technically based differences in automated QT and QTc measurements must be considered when these intervals are used as markers of heart disease, prognosis, or arrhythmogenic risk.

Algorithms↗

PubMed2002

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↗

PubMed2002

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↗