Cardiac memory is a common cause of deep T-wave inversions (TWI) in the anterior precordial leads and can be difficult to distinguish from alternative causes of TWI such as myocardial ischemia. Cardiac memory is generally a benign condition except in the setting of prolonged QT when it can contribute to the precipitation of torsades de pointes. Herein, we describe the presentation and clinical course of a case of cardiac memory due to intermittent left bundle branch block (LBBB) that presented asymptomatically to our outpatient cardiology clinic with deep anterior TWI. We discuss common causes of and mechanisms underlying cardiac memory and how to distinguish it from alternative causes of TWI based on 12-lead electrocardiogram. In conclusion, intermittent LBBB is an under-recognized cause of cardiac memory that can present as deep anterior TWI mimicking cardiac ischemia, and awareness of this clinical entity may help prevent unnecessary invasive and expensive testing on otherwise healthy patients. (C) 2020 Elsevier Inc. All rights reserved.

Introduction Inpatient telemetry monitoring is a commonly used technology designed to detect and monitor life-threatening arrhythmias. However, residents are rarely educated in the proper use and interpretation of telemetry monitoring. Methods We developed a training module containing an educational video, PowerPoint presentation, and hands-on interactive learning session with a telemetry expert. The module highlights proper use of telemetry monitoring, recognition of telemetry artifact, and interrogation of telemetry to identify clinically significant arrhythmias. Learners completed pre- and postcurriculum knowledge-based assessments and a postcurriculum survey on their experience with the module. In total, the educational curriculum had three 60-minute sessions. Results Thirty-two residents participated in the training module. Residents scored higher on the posttest (77% ± 12%) than on the pretest (70% ± 12%), t(31) = −4.3, p < .001. Wilcoxon signed rank tests indicated PGY-3s performed better on the posttest (Mdn = 0.86) than on the pretest (Mdn = 0.72), z = −2.19, p = .031. PGY-2s also performed better on the posttest (Mdn = 0.86) than on the pretest (Mdn = 0.76), z = −2.04, p = .042. There was no difference between pretest (Mdn = 0.66) and posttest (Mdn = 0.71) scores for PGY-1s, z = −1.50, p = .142. The majority of residents reported that the telemetry curriculum boosted their self-confidence, helped prepare them to analyze telemetry on their patients, and should be a required component of the residency. Discussion This module represents a new paradigm for teaching residents how to successfully and confidently interpret and use inpatient telemetry.

Permanent pacemakers (PPMs) are capable of recording tachyarrhythmic events including nonsustained ventricular tachycardia (NSVT), though the clinical significance of NSVT on routine PPM evaluation is unknown. Our goals: assess the prevalence of NSVT on routine PPM follow‐up and survival of PPM patients with NSVT, without NSVT, and with ventricular high rate (VHR) episodes of undefined origin.

Long term electrocardiographic (LTECG) recording is a method of recording the ECG over a designated period of time. This technology allows detection of intermittent arrhythmias, ST segment changes, and repolarization abnormalities. It provides a method for determining whether periodic symptoms are associated with cardiac arrhythmias. Technological advances in the past few years have provided a diversity of recording, transmitting, and analysis systems. Four general types of devices are currently available: continuous recorders, intermittent or event recorders, instruments for real-time recording and transmission of ECGs, and implantable recorders. Types of electrocardiographic recorders are shown in Table 18.1.

Background and Significance: The burden of symptoms for heart failure (HF) patients is often debilitating and severely limits quality of life. Because symptoms are generally not considered as clust...

The objective was to test whether the circadian variability of several electrocardiographic variables distinguishes sudden cardiac death survivors from heart disease patients without a history of cardiac arrest and from normal subjects. Heart rate, heart rate variability, and QT interval have been reported to identify survivors of sudden cardiac death. Computer-assisted continuous QT measurement and heart rate variability analysis were performed on 24-hour Holter records for three groups: (1) 14 sudden death survivors; (2) 14 control patients with diagnosis and therapy matched to survivors; and (3) 14 healthy subjects. There were no significant differences in 24-hour mean RR and QT intervals between groups. However, heart rate was significantly different between the three groups at night but not during the day because the expected nighttime decline was markedly blunted in survivors and somewhat blunted in control patients. The QT interval and frequency domain heart rate variability measures followed a similar circadian pattern. The mean QTc was significantly longer in control patients. The QTc had a wide range in all groups, but less in sudden death survivors. Of ten common time and frequency domain heart rate variability indices, only SDANN and SDNN were significantly lower in sudden death survivors. Reduced circadian variation of heart rate, with marked blunting of the nighttime heart rate decline, identifies sudden cardiac death survivors as well as does SDANN and SDNN, and, in contrast to heart rate variability measures, can easily be obtained from a Holter report without complex calculations.

BACKGROUNDOccupational stress may affect measured hemodynamic and electrocardiographic variables. Data describing the physiologic effects of work on the emergency physician (EP) are sparse.OBJECTIVETo determine whether blood pressure (BP) and heart rate variability (HRV) of the EP are affected during a night shift in the ED.METHODSThis prospective study evaluated BP and HRV in attending EPs at an urban academic medical center for a 24-hour period during which a night shift was scheduled. Participants were fitted with an oscillometric ambulatory BP device and a Holter monitor at 1500 hours on the day of a night shift. The monitors were worn continuously before, during, and after a night shift (2300-0700) in the ED and were removed at 1500. Systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), heart rate (HR), measures of HRV, and occurrence of cardiac dysrhythmias were evaluated. Comparisons were made for ED and non-ED awake periods and non-ED sleep periods.RESULTSTwelve participants completed the study. Eight (67%) subjects were men and 4 (33%) were women. Age ranged from 28 to 40 years (mean 34.1+/-4.1). Results were analyzed using repeated-measures ANOVA. An elevation of mean DBP (5.5 mm Hg+/-4.37; p < 0.05; 95% CI 1-10) during night shift activity was seen. A trend toward elevation of SBP, MAP, and HR was discernible. HRV measures indicated a significant relative increase in sympathetic vs parasympathetic tone and an increase in HR of prework and work compared with postwork. Dysrhythmias observed included sinus tachycardia, sinus bradycardia, sinus pause, atrial premature beats, atrial couplets and triplets, supraventricular tachycardia, and premature ventricular contractions.CONCLUSIONSThe elevation of DBP during a night shift suggests that these patterns of BP variability are activity- or stress-related rather than a result of a true diurnal variation. HRV analysis suggests that sympathetic tone is heightened both before work and during work. The implications of such findings to the health of the EP warrant further investigation.

Twenty-four-hour acquisition of QT dispersion (QTd) from the Holter and the circadian variation of QTd were evaluated in 20 survivors of sudden cardiac death (SCD), in 20 healthy subjects, and in 14 control patients without a history of cardiac arrest who were age, sex, diagnosis and therapy matched to 14 SCD patients. Computer-assisted QT measurements were performed on 24-hour Holter recordings; each recording was divided into 288 5-minute segments and templates representing the average QRST were generated. QTd was calculated as the difference between QT intervals in leads V1 and V5 for each template on Holter. The 24-hour mean QTd was significantly greater in SCD patients (40 ± 28 ms) than in healthy subjects (20 ± 10 ms) and control patients (15 ± 5 ms) (p <0.05). There was a circadian variation in QTd with greater values at night (0 to 6 a.m.) than at daytime (10 a.m. to 4 p.m.) in healthy subjects (25 ± 13 vs 15 ± 8 ms, p <0.001) and control patients (18 ± 10 vs 12 ± 4 ms p <0.05), whereas in SCD patients there was no significant difference between night and day values (45 ± 31 vs 37 ± 28 ms, p = NS). It is concluded that QTd measured by Holter was greater in SCD patients than in healthy subjects and matched control patients during the entire day. QTd has a clear circadian variation in normal subjects, whereas this variation is blunted in SCD patients. QTd measured on Holter differentiates survivors of cardiac arrest and may be a useful tool for risk stratification.

OBJECTIVES:This study sought to evaluate the range and variability of the QT and corrected QT (QTc) intervals over 24 h and to assess their pattern and relation to heart rate variability. BACKGROUND:Recent Holter monitoring data have revealed a high degree of daily variability in the QTc interval. The pattern of this variability and its relation to heart rate variability remain poorly characterized. METHODS:We developed and validated a new method for continuous measurement of QT intervals from three-channel, 24-h Holter recordings. Average RR, QT, QTc and heart rate variability were measured from 5-min segments of data from 21 healthy subjects. RESULTS:Measurement of 6,048 segments showed mean (+/- SD) RR, QT and QTc intervals of 830 +/- 100, 407 +/- 23 and 445 +/- 16 ms, respectively (mean QTc interval for men 434 +/- 12 ms, 457 +/- 10 ms for women, p < 0.0001). The average maximal QTc interval was 495 +/- 21 ms and the average QTc range 95 +/- 20 ms. The maximal QTc interval was > or = 500 ms in 6 subjects and > or = 490 ms in 13. The 95% upper confidence limit for the mean 24-h QTc interval was 452 ms (men 439 ms, women 461 ms). The RR, QT and QTc intervals and the high frequency component of heart rate variability were greater during sleep. Both the QTc interval and the variability between hourly minimal and maximal QTc intervals reached their circadian peak shortly after awakening, before declining to daytime levels. CONCLUSIONS:The maximal QTc interval over 24 h in normal subjects is longer than heretofore thought. Both QT and QTc intervals are longer during sleep. The QTc interval and QTc variability reach a peak shortly after awakening, which may reflect increased autonomic instability during early waking hours, and the time of the peak value corresponds in time to the period of reported increased vulnerability to ventricular tachycardia and sudden cardiac death. These findings have implications regarding the definition of QT prolongation and its use in predicting arrhythmias and sudden death.

To evaluate and compare QT correction formulas in healthy subjects, we used 24-hour Holter monitoring because it allows the assessment of QT intervals over a large range of rates. Computer-assisted QT-interval measurements were obtained from 21 subjects. QT-RR relations for individuals and the group were fitted by regression analysis to 5 QT prediction formulas: simple Bazett's, modified Bazett's, linear (Framingham), modified Fridericia's and exponential (Sarma's). There were no significant differences in mean squared residuals between formulas. When using individually calculated regression parameters, each formula gave good or acceptable QT correction over the entire range of RR intervals. Simple Bazett's formula (which uses no regression parameters) was unreliable at high rates. Akaike information criteria rank was: Sarma's, Framingham, modified Bazett's, Fridericia's, and simple Bazett's. When group-based regression parameters were applied to individuals, no formula had a clear advantage over simple Bazett's. We conclude that any formula that invokes regression parameters unique to each individual provides satisfactory QT correction. Determination of these parameters requires long-term recording to obtain an adequate range of rates. Group-based regression parameters give poor correction. When individual parameters cannot be determined, as in a 12-lead electrocardiogram, no formula provides an advantage over the familiar simple Bazett's.

When Taran and Szilagyi6 reexpressed the Bazett formula in its commonly used form, they eliminated the seemingly useless step of dividing by 1 second by requiring that RR be expressed in seconds. However, this produced the confusion with regard to the correct unit. Incorporation of the 1-second expression allows the QTc to be expressed in the unit that is both logical and arithmetically correct (namely that of the original QT), and eliminates any requirement regarding the units in which the original QT and RR are measured.

The ability to predict the RR-QT relation over a range of heart rates was evaluated in 10 patients with atrial fibrillation (AF) and in 10 control subjects in sinus rhythm. The data from each subject were fitted by regression into 3 QT prediction formulas (the square root formula of Bazett, the cube root formula of Fridericia and the exponential formula of Sarma) applied in standard form and modified with a weighted average of the preceding 5 RR intervals. The goodness-of-fit of each formula was evaluated using mean square residual and Akaike information criterion. For AF, the mean square residuals did not differ among the 3 standard QT prediction formulas (Bazett 624 +/- 274, Fridericia 625 +/- 274 and Sarma 611 +/- 267) and among the 3 modified QT prediction formulas (Bazett 507 +/- 325, Fridericia 496 +/- 255 and Sarma 495 +/- 328). The weighted average modification produced a significant decrease in mean square residuals for all 3 equations (p less than 0.05) in all patients. These findings were confirmed by Akaike information criterion. Goodness-of-fit in sinus rhythm was similar to previously published reports, and significantly better than the fit for AF (p less than 0.0001). For 9 of the 10 patients with AF, sinus rhythm electrocardiograms were obtained and the above regression equations were used to predict QT intervals.(ABSTRACT TRUNCATED AT 250 WORDS)