Electrocardiographic Recognition Research Articles

Registered nurses' knowledge and interpretation of ECG rhythms: A cross-sectional study.

Electrocardiographic (ECG) monitoring and recording are seen as the most commonly used non-invasive diagnostic tool to identify cardiac arrhythmia and myocardial damage in the clinical setting. There is an expectation that critical care nurses are ideally trained to interpret abnormalities and morphology in the ECG more proficiently than nurses from general ward areas. However, the ability to interpret and recognise ECG abnormalities is dependent on which critical care area nurses are currently working in and their level of experience. The aim of this study was to investigate registered nurses' knowledge in being able to identify and interpret select electrocardiographic rhythms. This was a cross-sectional study that evaluated registered nurses' knowledge of electrocardiogram rhythm identification and interpretation. A convenience sample of 105 registered nurses currently enrolled in a 2-year Master's programme leading to critical care specialism and advanced practice nurse award were recruited. A 20-item multiple choice questionnaire that provided examples of electrocardiogram rhythm (n=14) abnormalities and rhythm abnormalities caused by electrolyte disturbances (n=6) RESULTS: The study included registered nurses from critical care and general ward areas. The overall results were poor with only 55% of questions answered correctly. Coronary care nurses scored the highest in identifying ECG rhythms (12/20 ± 1.58; p < .001). When ECG abnormalities associated with electrolyte imbalances were analysed, both groups were unable to identify the effects of hypokalaemia and hypomagnesaemia effectively (p = .748). Length of time as a registered nurse (r = -0.304, p = .002) and length of time in current work environment were weakly correlated (r = -0.328, p = .001). Having a critical care background showed a positive relationship with nursing knowledge of ECG rhythm identification (r = 0.614, p < .001). The results of this study demonstrate that nurses have a poor knowledge of ECG rhythm identification and interpretation, a consistent finding from other work. A possible solution is a revamp of education and training associated with ECG recognition and morphology. Monitoring and assessing ECG morphology provide important details about cardio-electroconductive stability, especially with fluctuations in serum electrolyte levels seen in critical illness or trauma. For this, critical nurses must improve their proficiency through education/training or internal quality improvement activities in detecting abnormalities associated with ECG changes beyond those most easily recognizable rhythms such as atrial fibrillation or ventricular tachycardia.

Artificial Intelligence in Acute Ischemic Stroke Subtypes According to Toast Classification: A Comprehensive Narrative Review

The correct recognition of the etiology of ischemic stroke (IS) allows tempestive interventions in therapy with the aim of treating the cause and preventing a new cerebral ischemic event. Nevertheless, the identification of the cause is often challenging and is based on clinical features and data obtained by imaging techniques and other diagnostic exams. TOAST classification system describes the different etiologies of ischemic stroke and includes five subtypes: LAAS (large-artery atherosclerosis), CEI (cardio embolism), SVD (small vessel disease), ODE (stroke of other determined etiology), and UDE (stroke of undetermined etiology). AI models, providing computational methodologies for quantitative and objective evaluations, seem to increase the sensitivity of main IS causes, such as tomographic diagnosis of carotid stenosis, electrocardiographic recognition of atrial fibrillation, and identification of small vessel disease in magnetic resonance images. The aim of this review is to provide overall knowledge about the most effective AI models used in the differential diagnosis of ischemic stroke etiology according to the TOAST classification. According to our results, AI has proven to be a useful tool for identifying predictive factors capable of subtyping acute stroke patients in large heterogeneous populations and, in particular, clarifying the etiology of UDE IS especially detecting cardioembolic sources.

Differential electrocardiographic changes related to the culprit coronary artery in patients with acute myocardial infarction and left bundle branch block

Abstract Background The electrocardiographic (ECG) recognition of acute myocardial infarction (AMI) in patients with concurrent left bundle branch block (LBBB) is hampered by background changes in QRS complex duration and ST segment, potential directly caused by LBBB. Currently available ECG algorithms were constructed to suspect the presence of AMI but they not take into a count the culprit coronary artery and this fact could explain their low sensitivity. Objectives To analyze the influence of the culprit coronary artery on the ECG changes and on the diagnostic yielding of ECG algorithms in patients with acute myocardial infarction and LBBB. Methods We analyzed the index ECG of 240 patients with acute chest pain and LBBB referred to emergent coronary angiography. Patients were classified in 3 groups according their coronary anatomy: a) acute coronary occlusion (n=48); b) critical non occlusive lesion (n=45); and c) absence of coronary lesions (n=76). In all ECGs we measured the ST-segment shifts and QRS duration and compared the pattern of changes in relation to the culprit coronary artery. Results Location of the culprit coronary artery induced differential ECG patterns: a) mean ST segment elevation ≥3mm in leads V2-V3 in patients with LAD occlusion (n=27); b) absence of ST segment depression in leads V5-V6 in LCX occlusion (n=11); and c) mean ST segment elevation ≥1.5 mm in leads III-aVF and attenuation of the ST elevation in leads V1-V2 (mean &amp;lt;1mm) in cases of RCA occlusion (n=10). Patients with critical non occlusive lesions (n=45) did not show particular ECG changes. QRS complex duration was longer in patients with LCX occlusion. Sensitivity of the Sgarbossa score was around 50%, sensitivity of the Smith score was &amp;gt;70% in all coronary groups and sensitivity of Barcelona score was really good for LCX and RCA occlusion. The combination of the three algorithms increased the sensitivity in all groups (&amp;gt;74%) but more markedly in patients with LCX occlusion (90.9%) and RCA occlusion (90%). All the ECG algorithms lose sensitivity for the critical non occlusive lesions group. Conclusions Patients with acute myocardial infarction and LBBB present distinct patterns of QRS and ST segment changes and different diagnostic yielding of ECG algorithms in relation to the location of the occluded coronary artery. Data suggest that ECG prediction of the culprit coronary artery in patients with AMI and LBBB might be possible using artificial intelligence systems in larger series of patients. Funding Acknowledgement Type of funding sources: None.

Clinico-histopathological correlation of symptomatic left main coronary artery electrocardiographic ischemia pattern in a young child with hypertrophic cardiomyopathy

The specific electrocardiographic (ECG) pattern of left main coronary artery ischemia is exceptionally rare in children and under recognized. Occasional reports are bereft of a detailed mechanistic ECG description and limited to dissection, spasm, or anomalous origin of the left main coronary artery. An association with pediatric hypertrophic cardiomyopathy (HCM) is hitherto unreported. We furbish a detailed electrocardiographic description of this entity in the unusual setting of a 4-year-old child with HCM with a restrictive phenotype and exertional symptoms consistent with myocardial ischemia. Heart transplant was performed for this rare indication. Histopathology of the explanted heart in particular revealed left main coronary artery narrowing and provided us with a unique window of opportunity to correlate with clinical findings. The pathophysiology was also likely exacerbated by diffuse sub endocardial ischemia in the milieu of left ventricular hypertrophy with elevated end diastolic pressures. We anticipate that this illustrative case will help contextualize this as well as pediatric scenarios in which the ‘left main ischemia’ ECG pattern can be encountered and foster an accurate electrocardiographic recognition of this entity in children.

Unmasking an acute coronary occlusive myocardial infarction in patients with right ventricular paced rhythm

Electrocardiographic recognition of an acute myocardial infarction in the setting of a right ventricular paced rhythm (VPR) represents a unique diagnostic challenge. The classical ST-segment patterns of myocardial ischemia can become obscured by the abnormal repolarization changes caused by a right VPR. Consequently, longer door-to-balloon reperfusion times and a higher mortality have been reported among these patients mostly due to a delayed diagnosis. In this population, the use of the modified Sgarbossa Criteria (SC) can aid the clinician in the diagnosis of an acute coronary occlusive myocardial infarction (OMI), as an ST-segment elevation myocardial infarction (STEMI) equivalent. However, there are only a few validating studies and no specific guidelines endorsing their use in patients with VPR. We present three cases with right VPR in which the use of the modified SC was diagnostic of OMI, as well as predictive of the occluded coronary vessel. Our review of the current evidence favors that identification of at least one modified SC in patients with right VPR represents an OMI finding with a similar accuracy as when these are used in patients with LBBB.

Enhancing AI-guided STEMI detection algorithms by incorporating higher quality fiduciary EKG elements

Abstract Background As EKG interpretation paradigms to a physician-free milieu, accumulating massive quantities of distilled pre-processed data becomes a must for machine learning techniques. In our pursuit of reducing ischemic times in STEMI management, we have improved our Artificial Intelligence (AI)-guided diagnostic tool by following a three-step approach: 1) Increase accuracy by adding larger clusters of data. 2) Increase the breadth of EKG classifications to provide more precise feedback and further refine the inputs which ultimately reflects in better and more accurate outputs. 3) Improving the algorithms' ability to discern between cardiovascular entities reflected in the EKG records. Purpose To bolster our algorithm's accuracy and reliability for electrocardiographic STEMI recognition. Methods Dataset: A total of 7,286 12-lead EKG records of 10-seconds length with a sampling frequency of 500 Hz obtained from Latin America Telemedicine Infarct Network from April 2014 to December 2019. This included the following balanced classes: angiographically confirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Labels of each record were manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. Order 5 digital low pass filters with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: Determined classes were “STEMI” and “Not-STEMI” (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training &amp; Testing: A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90/10, respectively. The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. Additional testing was performed with a subset of the original complete dataset of unconfirmed STEMI. Performance indicators (accuracy, sensitivity, and specificity) were calculated for each model and results were compared with our previous findings from past experiments. Results Complete STEMI data: Accuracy: 95.9% Sensitivity: 95.7% Specificity: 96.5%; Confirmed STEMI: Accuracy: 98.1% Sensitivity: 98.1% Specificity: 98.1%; Prior Data obtained in our previous experiments are shown below for comparison. Conclusion(s) After the addition of clustered pre-processed data, all performance indicators for STEMI detection increased considerably between both Confirmed STEMI datasets. On the other hand, the Complete STEMI dataset kept a strong and steady set of performance metrics when compared with past results. These findings not only validate the consistency and reliability of our algorithm but also connotes the importance of creating a pristine dataset for this and any other AI-derived medical tools. Funding Acknowledgement Type of funding source: None

Influence of Left Bundle Branch Block on the Electrocardiographic Changes Induced by Acute Coronary Artery Occlusion of Distinct Location and Duration.

Background: Electrocardiographic (ECG) diagnosis of acute myocardial ischemia is hampered in the presence of left bundle branch block (LBBB).Objectives: We analyzed the influence of location and duration of myocardial ischemia on the ECG changes in pigs with LBBB.Methods: LBBB was acutely induced in 14 closed chest anesthetized pigs by local electrical ablation. Thereafter, episodes of 5 min catheter balloon occlusion followed by 10 min reperfusion of the left anterior descending (LAD), left circumflex (LCX), and right (RCA) coronary arteries were done sequentially in 5 pigs. Additionally, a 3-h occlusion of these arteries was performed separately in the other 9 pigs. A 15-lead ECG including leads V7 to V9 was continuously recorded.Results: Ablation induced LBBB showed QRS widening, loss of r wave in V1, and predominant R waves in V2 to V9. After 5 min of ischemia the occluded artery could be identified in all cases: the LAD by R waves and ST elevation in V1–V3; the LCX by both ST segment elevation in II, III, aVF, V7 to V9 and ST segment depression in V1 to V4; and the RCA by ST depression and new S-waves in all precordial leads. Three hours after coronary occlusion, ST segment changes declined progressively and only the LAD occlusion could be reliably recognized.Conclusion: LBBB did not mask the ECG recognition of the occluded coronary artery during the first 60 min of ischemia, but 3 h later only the LAD occlusion could be reliably identified. ST elevation in leads V7 to V9 is specific of LCX occlusion and it could be useful in the diagnosis of acute myocardial ischemia in the presence of LBBB.

Atypical advanced interatrial blocks: Definition and electrocardiographic recognition

The diagnosis of advanced interatrial block (A-IAB) is done by surface ECG analysis when the P-wave ≥120 ms with biphasic (±) morphology in leads II, III and aVF. In this brief communication, we advance a new concept involving atypical patterns of A-IAB due to changes about the morphology or duration of the P-wave. It remains to be determined its real prevalence in different clinical scenarios, and whether these atypical ECG patterns should be considered as predictors of atrial fibrillation/stroke.

Atypical bypass tracts: can they be recognized during sinus rhythm?

Atypical bypass tracts or variants of ventricular pre-excitation are rare anatomic structures often with rate-dependent slowing in conduction, called decremental conduction. During sinus rhythm, electrocardiographic recognition of those structures may be difficult because unlike in the Wolff-Parkinson-White syndrome where usually overt ventricular pre-excitation is present, the electrocardiogram (ECG) often shows a subtle pre-excitation pattern because of less contribution to ventricular activation over the slow and decrementally conducting bypass. Following the structure described by Ivan Mahaim and Benatt corresponding to a fasciculoventricular pathway, several other new variants of ventricular pre-excitation were reported. In this review, we aim to discuss the electrocardiographic pattern of the different subtypes of variants of ventricular pre-excitation, including the atriofascicular pathway, long and short decrementally conducting atrioventricular pathways, fasciculoventricular pathway, the atrio-Hisian bypass tract, and nodoventricular and nodofascicular fibres. Emphasis will be on the ECG findings during sinus rhythm.

Epicardial ventricular tachycardia

In ventricular tachycardia (VT) arising in the myocardial tissue, the site of origin may be the endocardium, mid-myocardium or epicardium. The incidence of epicardial origin varies with the underlying heart disease, and is probably not more than 20% in ischemic heart disease and higher in non-ischemic cardiomyopathies. Percutaneous subxiphoid access to the pericardial space has enabled a non-surgical approach to catheter mapping and ablation of epicardial VT. Several algorithms are available for electrocardiographic recognition of epicardial origin. Idiopathic epicardial VTs are rare but may be curable by catheter ablation. The electrophysiologic principles guiding the mapping and ablation of epicardial VTs are similar to those used for endocardial VTs, but the biophysics of energy delivery may be different. Complications of the epicardial approach are also different from those of endocardial ablation, and specific precautions have to be taken to protect the coronary arteries and phrenic nerves and to avoid pericardial tamponade.

Using Simulation and Patient Role Play to Teach Electrocardiographic Rhythms to Physical Therapy Students

THE AIMS OF THE STUDY WERE TO DIFFERENTIATE: (1) physical therapy (PT) students' preferred method for learning electrocardiographic (ECG) recognition utilizing standardized patient (SP) and human patient simulation (HPS) approaches, (2) the impact of HPS or SP on confidence in interpreting ECG, and 3) the effect of HPS or SP on students' ability to make clinical decisions based upon ECG interpretation. "Three educational methods were employed to teach ECG recognition to two different years of novice PT students enrolled in a cardiopulmonary physical therapy class. First, all students had a traditional lecture on ECG. Following the lecture, two problem-based learning (PBL) approaches were utilized. One approach used a SP and paper ECG strips, and the second approach utilized HPS with simulated ECG monitoring."(1) Following the two PBL approaches, a post instructional survey regarding the learning experiences was conducted. Following instruction, each cohort (n = 24, n = 29) of PT students was given a mixed methods survey about their experience. Survey return rate amongst both cohorts was 77%. Independent sample of individual cohort and paired t-tests of combined data comparing HPS to SP revealed a strong preference for HPS (p = 0.003 (2008 cohort) and p = 0.0001 (2010 cohort)) and combined cohort (p = 0.0001). There were no significant differences in responses between cohorts or preference between the HPS method and the use of SP and HPS combined. Additionally, 75% of respondents either strongly agreed or agreed that they felt confident with their skill in ECG interpretation as presented with HPS or SP. 90% either strongly agreed or agreed that they understood how the ECG relates to patient treatment. Summative assessment utilizing HPS revealed that students were competent in their performance in ECG recognition and clinical decision making related to patient treatment.(1) Data support that HPS was the preferred method to improve student confidence in ECG recognition and interpretation.

Electrocardiographic recognition and ablation of outflow tract ventricular tachycardia

Electrocardiographic recognition and ablation of outflow tract ventricular tachycardia

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.

Software complex for the recognition of diagnostically significant ECG changes

A software complex for the automation of functional electrocardiographic (ECG) studies is presented. The algorithms of ECG signal processing and recognition of diagnostically significant ECG changes are considered. Methods of 3D visualization are proposed to increase the informativeness of electrocardiographic data and improve diagnostic accuracy.

Fuzzy-Hybrid Neural Network Based ECG Beat Recognition Using Three Different Types of Feature Sets

This paper represents the application on the fuzzy-hybrid neural network for electrocardiographic (ECG) beat recognition and classification. We proposed the approach to ECG beat recognition that is based on QRS complex classification. Instead of the original QRS waveform, we have used three different types of QRS features sets. The main objective of this work was to develop a technique which was less sensitive to the morphological variation of the QRS waveform. Linear predictive coefficients (LPC), third-order cumulant-based auto regressive coefficient (AR), and the variance of the wavelet transform detail coefficients of the isolated QRS complexes are used as the features. It will be shown that the wavelet transform based approach is better than the other techniques. The main properties of the proposed method are simplicity, moderate recognition rate, and fast computation time.

Use of adenosine in patients hospitalized in a university medical center

Purpose: Adenosine is a useful agent for the diagnosis and termination of tachycardias. The purpose of this study was to identify the rhythms for which adenosine is prescribed in hospitalized adults and to identify the reasons for its misuse. Patients and Methods: Data were collected from the medical records of 100 patients who received intravenous adenosine while hospitalized at a university medical center. The characteristics of the patients, rhythms treated with adenosine, and dosages of adenosine were analyzed. In addition, internal medicine house officers were administered a questionnaire referring to an electrocardiogram of atrial fibrillation with a rapid ventricular response. Results: The arrhythmias for which adenosine was administered consisted of regular, narrow-QRS complex tachycardias in 33% of patients; atrial fibrillation in 32% of patients; regular, wide-QRS complex tachycardias in 23% of patients; atrial flutter in 10% of patients, and multifocal atrial tachycardia in 2% of patients. The mean (± SD) number of doses of adenosine given to each patient was 1.6 ± 0.8, and the mean dose of adenosine was 7.8 ± 2.8 mg. Internal medicine house officers prescribed 70% of the doses of adenosine and were as likely to use it for patients with atrial fibrillation as were surgical house officers. There was a 2% incidence of proarrhythmia, including asystole and polymorphic ventricular tachycardia. Thirty-one percent of the 100 house officers in our survey misdiagnosed a 12-lead electrocardiogram of rapid atrial fibrillation as paroxysmal supraventricular tachycardia, suggesting that adenosine may have been misused for atrial fibrillation because of errors in rhythm diagnosis. Only 5% of those who correctly diagnosed atrial fibrillation also answered that adenosine would be likely to terminate the arrhythmia, suggesting that a misunderstanding that adenosine terminates atrial fibrillation is not a common reason for its misuse. Conclusions: Approximately 40% of hospitalized adults who are treated with adenosine receive the medication unnecessarily for atrial fibrillation or atrial flutter, and this misuse results in unnecessary expenses and risks of adverse effects. The primary reason that adenosine is misused for atrial fibrillation is the inability to recognize that rhythm on an electrocardiogram. House officers need additional education on the electrocardiographic recognition of atrial fibrillation.

Electrocardiographic criteria for diagnosis of left ventricular hypertrophy in the presence of complete right bundle branch block

The usual electrocardiographic criteria recommended for left ventricular (LV) hypertrophy may be unreliable in the presence of complete right bundle branch block (BBB). Thirty-six standard electrocardiographic criteria for LV hypertrophy were evaluated in 100 patients (mean age ± standard deviation 67 ± 11 years) with right BBB and technically satisfactory echocardiograms. Eight additional electrocardiographic criteria derived from this study also were evaluated. LV mass index was determined from the echocardiogram using the Penn method. LV hypertrophy defined as LV mass index >132 g/m 2 in men and 109 g/m 2 in women was present in 56 of the 100 patients. Electrocardiographic criteria with the highest sensitivity were SIII + (R + S) maximal precordial lead ≥30 mm (sensitivity 68%, specificity 66%), left axis deviation of −30 ° to −90 ° (sensitivity 59%, specificity 71%) and combination of left axis deviation and SIII + (R + S) maximal precordial lead ≥30 mm (sensitivity 52%, specificity 84%). The electrocardiographic criteria with the highest sensitivity and specificity >90% were left axis deviation of −30 ° to −90 ° and SV 1 > 2 mm (sensitivity 34%), point-score system, RaVL > 12 mm and RI + SIII > 25 mm (each with a sensitivity of 27%). In general, limb lead voltage criteria such as RaVL > 11 mm (sensitivity 29%, specificity 86%) had higher sensitivities than criteria using right precordial lead S-wave voltage criteria such as SV 1 + RV 5, V 6 > 35 mm (sensitivity 2%, specificity 100%). These data indicate that, in the presence of complete right BBB, electrocardiographic criteria for LV hypertrophy based on the magnitude of right precordial lead S waves have a very low sensitivity, and electrocardiographic recognition of LV hypertrophy will depend primarily on limb lead criteria or combinations of criteria.

Geometric determinants of electrocardiographic left ventricular hypertrophy.

Experimental studies have suggested that electrocardiographic recognition of left ventricular hypertrophy depends on geometric relationships involving wall thickness and chamber size. To determine the clinical significance of these observations, we studied the effects of echocardiographic LV mass (LVM), posterior wall thickness (PWT), interventricular septal thickness (IVST) and internal dimension (LVID) on ECG voltage in 360 patients. Standard voltage and nonvoltage manifestations of LVH correlated modestly with LVM (r = 0.33-0.44, p less than 0.001). Sokolow-Lyon precordial voltage (SLV) (SV1 + RV5 or V6) correlated moderately with LVM (r = 0.41, p less than 0.001), but correlated less well with IVST (r = 0.26), PWT (r = 0.24) or LVID (r = 0.22). Stepwise regression revealed that there was no relation, independent of LVM, between SLV and IVST (r = 0.03), PWT (r = 0.03) or LVID (r = 0.01). The 90 patients with increased LVM (greater than 215 g) but without LVH by SLV (false negatives) were compared with the 48 identified by SLV (true positives). False negatives differed from true positives in LVM (298 +/- 72 vs 339 +/- 98 g, p less than 0.01), age (55 +/- 18 vs 44 +/- 19 years, p less than 0.001), weight (70 +/- 16 vs 63 +/- 14 kg, p less than 0.02), and distance from skin to the interventricular septum (42 +/- 10 vs 38 +/- 8 mm, p less than 0.02). Thus, for a given LVM, ECG voltage criteria of LVH are independent of LV chamber dilatation or other geometric variables, but depend on age, weight and LV depth in the chest, suggesting that stratification of subjects by clinical variables has promise for improved electrocardiographic recognition of LVH.

The electrocardiographic recognition of cardiac states at high risk of ventricular arrhythmias. An experimental study in dogs.

SUMMARY Recognition of states in which the heart is vulnerable to arrhythmia would be a helpful guide to prophylaxis. The possibility of recognizing such states from the ECG is suggested by the already established relations between abnormally disparate recovery to both vulnerability to arrhythmia and ECG waveform. In this study, canine QRS, T, and QRST isoarea maps were determined from ECGs recorded at 192 body sites during control states and conditions of enhanced susceptibility to arrhythmia. Vulnerable states were produced by ouabain intoxication, hypothermia, premature beats, and epinephrine infusion. A hypothetical series of QRST isoarea maps that would be expected to occur without increased local inequalities of recovery was derived by adding the control QRS isoarea map to a fraction (a) of the control T isoarea map and allowing the fraction to vary from a = 1 to a = — 1. One QRST isoarea map selected from the derived series was subtracted from a QRST isoarea map during each state of enhanced arrhythmia vulnerability. Derived maps were selected to minimize the average amplitude of the residual maps. RMS values of the residual maps systematically increased with increasing prematurity of depolarization, with time after a toxic injection of a dose of ouabain, with increasing hypothermia, and during the first 3 minutes of epinephrine infusion. Also, the RMS values of the residual maps decreased in hypothermic dogs during rewarming. Our findings suggest that states of vulnerability to arrhythmia due to increased disparity of recovery can be identified by analysis of ECG waveforms recorded from lead systems sensitive to electrical activity in local cardiac regions.

Electrocardiographic recognition of sinus node dysfunction in children and young adults.

Twenty-four children and young adults with electrocardiographic evidence of sinus node dysfunction (SND) are described. The patients, whose ages ranged from three days to 25 years, were divided into three groups based on the type of SND. Ten patients had persistent and inappropriate sinus bradycardia (group I): twelve patients had episodes of prolonged sinus arrest (group II); and seven patients had repeated episodes of Mobitz type I or II sinoatrial exit block (group III). Eighteeen patients had significant heart disease and in 11 of these the SND followed corrective cardiac surgery. Seven were operations for atrial septal defect and transposition repair. Seven patients with SND were symptomatic, having either syncopal (3) or near syncopal episodes (4). All three with syncope have received permanent demand pacemakers. These data show that sinotrial exit block occurs in many young patients with SND (29% in this series). Its recognition, however, requires careful electrocardiographic analysis in order to differentiate sinus bradycardia and sinus arrhythmia. Although SND most commonly occurs in children with congenital or acquired heart disease, particularly following corrective cardiac surgery, it may occur in the absence of other cardiac abnormalities.