Nonspecific ST-T Abnormalities Research Articles

Non-specific electrocardiographic ST-T abnormalities predict mortality in patients on peritoneal dialysis.

This study aimed to evaluate the predictive value of non-specific ST-segment and/or T-wave abnormalities in electrocardiography (ECG) for all-cause and cardiovascular mortality (CVM) in peritoneal dialysis (PD) patients. All patients who started PD between November 1, 2005, and February 28, 2017, at the First Affiliated Hospital of Nanchang University were enrolled. The primary outcomes were all-cause mortality and CVM. The Kaplan-Meier method and a log-rank test were used for the survival analysis. Multivariate Cox proportional hazards models were used to investigate the risk factors for all-cause mortality and CVM. A total of 724 eligible PD patients were enrolled, including 401 (55.4%) men. In total, 153 (21.1%) patients died during a mean follow-up period of 27 (interquartile range, 13-41) months, and cardiovascular death was responsible for 84 of these deaths. The patients with non-specific ST-T abnormalities (NSSTTAs) had lower overall and cardiovascular survival rates compared to those free from any ECG abnormalities. According to the multivariate Cox proportional hazards models, (NSSTTAs) are independent risk factors for all-cause mortality and CVM, the hazard ratios are 1.81 (95% confidence interval, 1.11-2.95; p = 0.017) and 2.86 (95% confidence interval, 1.52-5.37; p = 0.001), respectively. Non-specific ST-T abnormalities can serve as risk markers of all-cause and CVM in PD patients.

Abstract 11161: Thymic Hemorrhage – A Cause for Cardiac Arrest?

Introduction: Thymic hemorrhage is a rare cause of sudden cardiac death, particularly in adults. We present a 35- year- old with sudden “cardiac” death secondary to thymic hemorrhage. Case: A 35-year-old healthy man presented following witnessed cardiac arrest. CPR was initiated immediately. The initial rhythm was shockable, he was defibrillated, and ROSC was achieved. He was intubated on site and transferred to the hospital. Initial labs were negative for electrolyte derangements and drugs of abuse. His high-sensitivity troponin T was 238 ng/L (nl<23 ng/L) and subsequently trended downward. His electrocardiogram showed non-specific ST-T abnormalities. His echocardiogram showed an ejection fraction of 25 to 29% with global hypokinesis. He was extubated on day 4 and scheduled for coronary angiography. On day 5, when he attempted to get out of bed, he lost consciousness and became pulseless. His initial rhythm was PEA, but with episodes of ventricular fibrillation during CPR, he was shocked accordingly. He had prolonged CPR, therefore, obviating advanced therapies. His autopsy showed only thymic hemorrhage. His coronary arteries were normal, with no signs of myocardial injury or myocarditis. Conclusion: Massive acute thymic hemorrhage is extremely rare in adults but is a rare but recognized cause of sudden death in utero and infants. There are only two reported cases of thymic hemorrhage in adults in the literature. Both the patients were nearly 40-year-old men who presented with chest pain. Initial imaging was consistent with mediastinal widening requiring thoracotomy that demonstrated hemorrhagic thymus. Similar to our patient, the reported cases were young men with no prior history of trauma. In contrast, our patient presented with cardiac arrest, and initial imaging was negative for mediastinal widening. The underlying etiology of cardiac arrest from thymic hemorrhage is poorly understood. Right atrial compression from acute hemorrhage of a benign thymic tumor was postulated as the cause of sudden death in a previously healthy 15-year-old boy. Our patient is a rare case since there are, to our knowledge, no reported cases in the literature of thymic hemorrhage as the cause of death in adults.

Artificial intelligence-guided, single-lead EKG may be a game-changer for symptom-to-balloon time reduction in ST-elevated myocardial infarction

Abstract Background Over decades, efforts to shave off life-saving minutes from ST-Elevated Myocardial Infarction (STEMI) care centred on reducing door-to-needle and door-to-balloon times. We firmly believe that symptom-to-balloon time should prove a better focus to this end. Challenges come with this goal as it heavily relies on a patient's perception and initiative to seek care, which we deem intelligent and wearable Artificial Intelligence (AI)-driven Single Lead EKG technologies as an attractive solution in modern-day cardiology. Purpose To provide an accurate, accessible, and cost-effective AI-driven Single Lead STEMI detection algorithm that can be embedded into wearable devices and employed in a self-administered fashion. Methods Database: EKG records from Mexico, Colombia, Argentina, and Brazil from April 2014 to December 2019. Dataset: A total of 11,567 12-lead EKG records of 10[s] length with a sampling frequency of 500 Hz, including the following balanced classes: angiographically confirmed and unconfirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal and abnormal (200+ CPT codes, excluding those mentioned above). Cardiologists manually checked the label of each record to ensure precision. Pre-processing: We discard the first and last 250 samples as they may contain a standardisation pulse. The study applied a digital low pass filter of order 5 with a frequency cut-off of 35 Hz. The mean was subtracted from each Lead. Classification: The determined classes were “STEMI” (Including STEMI in different locations of the myocardium – anterior, inferior, and lateral); and “Not-STEMI” (Combination of randomly sample, branch blocks, non-specific ST-T changes, and abnormal records – 25% of each). Training and Testing: A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90/10, respectively. A different model was trained and tested for each Lead, using the central 4,500 samples of the records. The last dense layer outputs a probability for each report of being STEMI or Not-STEMI. Lead V2 showed the best overall results. The model was further tested through the same methodology using the best Lead with a subset of the previous data, excluding the unconfirmed STEMI EKG records (Total 7,230 12-lead EKG records for Confirmed Only STEMI dataset). Performance metrics were reported for each experiment and compared. Results Combined STEMI data: Accuracy: 91.2%; Sensitivity: 89.6%; Specificity: 92.9%. Confirmed STEMI Only dataset: Accuracy: 92.4%; Sensitivity: 93.4%; Specificity: 91.4% (Figure 1). Conclusion By assiduously improving the quality of the model's input, we continue to assess our algorithm's performance and reliability for future clinical validation as a potential remote monitoring and early STEMI detection device. Funding Acknowledgement Type of funding sources: None.

Baby steps in the path of modifying the role of cardiologists for interpreting EKG for AMI

Abstract Background EKG interpretation is slowly transitioning to a physician-free, Artificial Intelligence (AI)-driven endeavor. Our continued efforts to innovate follow a carefully laid stepwise approach, as follows: 1) Create an AI algorithm that accurately identifies STEMI against non-STEMI using a 12-lead EKG; 2) Challenging said algorithm by including different EKG diagnosis to the previous experiment, and now 3) To further validate the accuracy and reliability of our algorithm while also improving performance in a prehospital and hospital settings. Purpose To provide an accurate, reliable, and cost-effective tool for STEMI detection with the potential to redirect human resources into other clinically relevant tasks and save the need for human resources. Methods Database: EKG records obtained from Latin America Telemedicine Infarct Network (Mexico, Colombia, Argentina, and Brazil) from April 2014 to December 2019. Dataset: A total of 11,567 12-lead EKG records of 10-seconds length with sampling frequency of 500 [Hz], including the following balanced classes: unconfirmed and angiographically confirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal and abnormal (200+ CPT codes, excluding the ones included in other classes). The label of each record was manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: The first and last 250 samples were discarded as they may contain a standardization pulse. An order 5 digital low pass filter with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: The determined classes were STEMI (STEMI in different locations of the myocardium – anterior, inferior and lateral); Not-STEMI (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training & 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 dataset of angiographically confirmed STEMI. Results See Figure Attached – Preliminary STEMI Dataset Accuracy: 96.4%; Sensitivity: 95.3%; Specificity: 97.4% – Confirmed STEMI Dataset: Accuracy: 97.6%; Sensitivity: 98.1%; Specificity: 97.2%. Conclusions Our results remain consistent with our previous experience. By further increasing the amount and complexity of the data, the performance of the model improves. Future implementations of this technology in clinical settings look promising, not only in performing swift screening and diagnostic steps but also partaking in complex STEMI management triage. Funding Acknowledgement Type of funding source: None

Innovative techniques to construct powerful artificial intelligence algorithms for st-elevation myocardial infarction

Abstract Background With the sudden advent of Artificial Intelligence (AI), incorporation of these technologies into key aspects of our working environment has become an ever so delicate task, especially so when dealing with time-sensitive and potentially lethal scenarios such as ST-Elevation Myocardial Infarction (STEMI) management. By further expanding into our successful experiences with AI-guided algorithms for STEMI detection, we implemented an innovative ensemble method into our methodology as we seek to improve the algorithm's predictive capabilities. Purpose Through the ensemble method, we combined two ML techniques to boost our previous experiments' accuracy and reliability. Methods Database: EKG records obtained from Latin America Telemedicine Infarct Network (Mexico, Colombia, Argentina, and Brazil) from April 2014 to December 2019. Dataset: Two separate datasets were used to train and test two sets of AI algorithms. The first comprised of 11,567 records and the second 7,286 records, each composed of 12-lead EKG records of 10-second length with sampling frequency of 500 Hz, including the following balanced classes: unconfirmed & angiographically confirmed STEMI (first model); angiographically confirmed STEMI only (second model); and, for both models, we included branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Label per record was manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. An order 5 digital low pass filter with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: The 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 & Testing: The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. These probabilities were calculated for each model (Model 1 trained with Complete STEMI dataset and Model 2 trained with confirmed STEMI only dataset) and aggregated using the mean aggregation to generate the final label for each record. A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90%/10%; respectively. Results are reported for both testing datasets (Complete and confirmed STEMI only records). Results Complete STEMI Dataset: Accuracy: 96.5% Sensitivity: 96.2% Specificity: 96.9% – Confirmed STEMI only Dataset: Accuracy: 98.5% Sensitivity: 98.3% Specificity: 98.6%' Conclusion(s) While Model 1 and Model 2 achieved similar performances with promising results on their own, applying a combination of both through the ensemble model exhibits a clear improvement in performance when applied to both datasets. This provides a blueprint for advanced automated STEMI detection through wearable devices. Funding Acknowledgement Type of funding source: None

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 & 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

Clinical Implications of Ventricular Repolarization Parameters on Long-Term Risk of Atrial Fibrillation - Longitudinal Follow-up Data From a General Ambulatory Korean Population.

This study investigated 12-lead electrocardiogram (ECG) predictors associated with atrial fibrillation (AF) or flutter (AFL), specifically whether ventricular repolarization abnormalities in surface ECG (i.e., non-specific ST-T abnormalities [NSSTTA], QT prolongation, early repolarization [ER]) were associated with the development of AF or AFL.Methods and Results:This study included 16,793 ambulatory Koreans (mean age 48.2 years, 62.3% male) who underwent medical check-ups at Asan Medical Center in 2002 (NSSTTA, n=1,037 [6.2%]; ER, n=1,493 [8.9%]). The primary outcome was the incidence of ECG-documented AF or AFL. During follow-up, new-onset AF or AFL was documented in 334 subjects (2.0%). The incidence of AF or AFL at the 10-year follow-up was higher in patients with than without NSSTTA (3.5% vs. 1.6%; hazard ratio [HR] 1.79, 95% confidence interval [CI] 1.28-2.50). The QT interval was associated with a higher risk of AF or AFL (HR 1.12 [95% CI 1.07-1.17] per 10 ms), and the risk was even higher in patients with multiple-region NSSTTA (HR 2.30; 95% CI 1.64-3.21) and NSSTTA with QT prolongation (HR 4.06; 95% CI 2.14-7.69). ER was not associated with a higher risk of AF or AFL (HR 1.02; 95% CI 0.71-1.46). NSSTTA and QT prolongation, but not ER, were associated with a higher risk of future AF or AFL in a general ambulatory population after adjusting for parameters of atrial depolarization.

Clinical features of 9 cases of Brucella endocarditis

Objective: To explore the clinical characteristics of patients with Brucella endocarditis. Methods: The clinical data of 9 patients with Brucella endocarditis admitted to Beijing Ditan Hospital from October 2008 to August 2018 were retrospectively analyzed. Through the electronic medical record system of the hospital. Through assessing the electronic medical record system of the hospital, demographic data, main symptoms, vital signs, blood culture, Rose Bengal Plate Agglutination Test, echocardiography, electrocardiogram, chest imaging and other clinical data of included patients were inquired and recorded. Patients were followed up by telephone for medication, operation and outcome. Results: The 9 patients were all Han nationality, aged from 25 to 66 years, 7 out of 9 patients were male, and they came from Hebei, Shandong, Shanxi, Inner Mongolia and Beijing. Of the 9 patients, 5 were farmers, 2 were self-employed, 1 was a technician, and 1 was unemployed. Of the 9 cases, 8 had a history of close contact with cattle and sheep, and 5 had a history of eating beef and mutton. Rose-Bengal Plate Agglutination Test and blood culture were positive in all 9 patients. Aortic valve was involved in 7 out of 9 patients, mitral and tricuspid valve was involved in 1 patient, respectively, and aortic dissection occurred in 1 patient. Condition of 1 patient rapidly deteriorated after admission and finally died during hospitalization despite antibiotic therapy, the remaining patients received long-term antibiotic treatment. A total of 7 patients who underwent valve replacement were followed up. One patient died of cerebral hemorrhage 6 months after operation, and the remaining 6 patients recovered well after valve replacement. Heart failure occurred in all 9 patients, and pericardial effusion occurred in 8 patients. Electrocardiogram showed low voltage of the QRS complex in the limb in 3 cases and poor R-wave progression in V(1)-V(3) lead in 2 cases, and sinus tachycardia in 2 cases. One patient developed non-specific ST-T abnormalities. All patients had fever, 7 patients complained of weakness, and 6 patients complained of palpitations. Among the 9 patients, 7 cases had anemia, 7 patients had pneumonia, 6 had bilateral pleural effusion, 4 had thrombocytopenia. Creatinine was above normal in 4 patients, urine protein was positive in 3 patients, Delta Bilirubin was higher in 3 cases. Conclusions: Patients with Brucella endocarditis often suffer from heart failure and have severe complications. Adequate antibiotic therapy in combination with valve replacement is effective for the treatment of patients with Brucella endocarditis.

Association of isolated minor nonspecific ST-T abnormalities with left ventricular hypertrophy and diastolic dysfunction

The aim of this study was to examine the associations of isolated minor nonspecific ST-T abnormalities (NSSTTA) on 12-lead electrocardiogram (ECG) with left ventricular (LV) diastolic function and LV geometry on echocardiography. A cross-sectional study comprised of 74,976 Koreans who underwent ECG and echocardiography as part of a comprehensive health examination between March 2011 and December 2014. ECG was coded using Minnesota Code criteria. The frequencies of NSSTTA, impaired LV relaxation, and echocardiographic LVH were 1,139 (1.5%), 21,118 (28.2%), and 1,687 (2.3%) patients, respectively. The presence of NSSTTA was positively associated with the prevalence of impaired LV relaxation and LVH on echocardiography. In a multivariable-adjusted model, the odds ratio (95% CIs) comparing patients with NSSTTA to control patients was 1.55 (1.33–1.80) for impaired LV relaxation and 3.15 (2.51–3.96) for echocardiographic LVH. The association between NSSTTA and impaired LV relaxation was stronger in the intermediate to high cardiovascular disease-risk group than in the low-risk group according to Framingham Risk Score stratification (P for interaction = 0.02). NSSTTA were associated with increased prevalence of impaired LV relaxation and LVH, suggesting NSSTTA as an early indicator of subclinical cardiac dysfunction and geometric abnormalities.

Patients With Type A Acute Aortic Dissection Presenting With an Abnormal Electrocardiogram

The electrocardiogram (ECG) is often used in the diagnosis of patients presenting with chest pain to emergency departments. Because chest pain is a common manifestation of type A acute aortic dissection (TAAAD), ECGs are obtained in much of this population. We evaluated the effect of particular ECG patterns on the diagnosis and treatment of TAAAD. TAAAD patients (N= 2,765) enrolled in the International Registry of Acute Aortic Dissection were stratified based on normal (n= 1,094 [39.6%]) and abnormal (n= 1,671 [60.4%]) findings on presenting ECGs and further subdivided according to specific ECG findings. Time data are presented in hours as medians (quartile 1 to quartile 3). Patients with ECGs with abnormal findings presented to the hospital sooner after symptom onset than those with ECGs with normal findings (1.4 [0.8 to 3.3] vs 2.0 [1.0 to 3.3]; p= 0.005). Specifically, this was seen in patients with infarction with new Q waves or ST elevation (1.3 [0.6 to 2.7] vs 1.5 [0.8 to 3.3]; p= 0.049). Interestingly, the time between symptom onset and diagnosis was longer with infarction with old Q waves (6.7 [3.2 to 18.4] vs 5.0 [2.9 to 11.8]; p= 0.034) and nonspecific ST-T changes (5.8 [3.0 to 13.8] vs 4.5 [2.8 to 10.5]; p= 0.002). Surgical mortality was higher in patients with abnormal ECG findings (20.6% vs 11.9%, p < 0.001), especially in those with ischemia by ECG (25.7% vs 16.8%, p < 0.001) and infarction with new Q waves or ST elevation (30.1% vs 17.1%, p < 0.001). TAAAD patients presenting with abnormal ECG results are sicker, have more in-hospital complications, and are more likely to die. The frequency of nonspecific ST-T abnormalities and its association with delay in diagnosis and treatment presents an opportunity for practice improvement.

ECG non-specific ST-T and QTc abnormalities in patients with systemic lupus erythematosus compared with rheumatoid arthritis

ObjectivesCardiovascular disease (CVD) is a leading cause of death in systemic lupus erythematosus (SLE) and in rheumatoid arthritis (RA). Although only explored in one study, ECG non-specific ST-T abnormalities, in...

Prognostic value of non-specific ST-T changes and left ventricular hypertrophy electrocardiographic criteria in hypertensive patients: 16-year follow-up results from the MINACOR cohort.

BackgroundNon-specific electrocardiographic ST-T wave changes and voltage criteria for left ventricular hypertrophy (LVH) have been associated with cardiovascular morbidity and mortality. The aim of the cohort study was to evaluate the prognostic value of non-specific ST-T changes and LVH electrocardiographic criteria on cardiovascular events and mortality in hypertensive patients.MethodsA cohort study of 352 non-diabetic hypertensive patients, without associated cardiovascular disease, randomly selected from 1,780 hypertensive patients attended in a primary care center. An electrocardiogram was performed at the baseline visit (classified according to the Minnesota Code). Cardiovascular events and death from any cause during the follow-up period were evaluated. A multivariate analysis adjusted for gender, age and cardiovascular risk factors was performed.ResultsData of 273 patients were analyzed: 58.2% women, age 44.1 (7.9) years, 27.8% smokers, blood pressure at baseline 142.7 (15.3)/89.3 (9.6) mmHg. During the 197.5 (59.24) month follow-up, 62 patients (22.7%) had a cardiovascular event. On multivariate analysis, age, systolic blood pressure, incidence of diabetes, smoking and electrocardiographic LVH criteria (HR 2.66 [CI 95% 1.39 – 5.10]), were significantly associated with cardiovascular events, but the presence of non-specific ST-T abnormalities (HR 0.97 [CI 95% 0.49 -1.90]) was not significantly associated with cardiovascular morbidity and mortality.ConclusionsHypertensive patients with LVH electrocardiographic criteria have significantly higher cardiovascular mortality and morbidity, but non-specific electrocardiographic ST-T changes are not associated with cardiovascular morbidity and mortality.

Relationship between Nonspecific Electrocardiographic Abnormalities and Left Ventricular Performance in Coronary Atherosclerosis

Background: Nonspecific ST-T abnormalities (NSSTTA) have been associated with increased risk of cardiovascular mortality. The aim of this study was to investigate relationship between NSSTTA and left ventricular (LV) performance in coronary atherosclerosis. Methods: We reviewed 12-lead ECG in patients undergoing coronary angiography and echocardiography. NSSTTA (nonspecific ST-segment depression (≤−50 µV) and/or T-wave inversion (≤−100 µV) was interpreted by computerized analysis. The role of NSSTTA in atherosclerogenesis and LV performance was determined. Results: Inclusion criteria were met by 323 patients. LV mass was significantly greater in patients with NSSTA than those without (261.7 grams versus 217.9 grams, P=0.001). LV diastolic performance was significantly lower in patients with NSSTTA than those without (8.9 versus 7.0 represented by E/E′, P=0.014). However, there was no significant difference in LV ejection fraction between patients with and without NSSTTA (62.0% versus 63.2%, P=0.387). In addition, no significant association between NSSTTA and the severity of coronary stenosis was found (19.1 versus 17.9 expressed by Gensini score, P=0.762). Multivariate analysis identified that an independent determinants of NSSTTA was LV mass (P=0.008). Conclusions: NSSTTA was identified as a novel risk factor for initiating cardiovascular continuum.

Clinical correlates and prognostic significance of electrocardiographic abnormalities in apical ballooning syndrome (Takotsubo/stress-induced cardiomyopathy)

Apical ballooning syndrome (ABS) is a unique transient cardiomyopathy that mimics an acute myocardial infarction. The relative frequency of ST-segment elevation on the 12-lead electrocardiogram (ECG) and its prognostic significance is unknown. The aims of this study were to evaluate the frequency and the clinical correlates of ST- and T-wave abnormalities on the admission ECG in patients with ABS. Patients were retrospectively identified from the cardiac catheterization database--those who underwent coronary and left ventricular angiography and fulfilled the Mayo criteria for ABS during the period January 1988 to November 2006. They were divided into 3 groups according to the presence of (1) ST-segment elevation (>1 mm in 2 contiguous lead) or new left bundle branch block, (2) T-wave inversion (>3 mm in 3 contiguous leads) but no ST shift, and (3) nonspecific ST-T abnormalities or normal ECG at the time of admission. Clinical and echocardiographic findings were compared between groups. Among the 105 patients, 36 (34.2%), 32 (30.4%), and 37 (35.2%) patients were in the three respective groups. There were no differences in the clinical characteristics, ejection fraction, and outcomes between the 3 groups. Over a median follow-up of 2.5 years, there was no difference in the 5-year recurrence rate of ABS between the 3 groups (13%, 5%, 17% patients, respectively, P = .25). The 5-year mortality was similar in the 3 groups (24%, 7.3%, 10.8%, P = .58). ST-segment elevation is absent in two thirds of patients with ABS. Thus, the cardiomyopathy may mimic either ST-elevation or non-ST-elevation myocardial infarction. The ECG abnormalities at presentation do not correlate with the magnitude of ventricular dysfunction or outcomes.

Interarterial Course of the Right Coronary Artery

A 50-year-old well-trained cyclist reported increasing brief episodes of chest pain over the last 8 years at maximum exercise during alpine bicycle training. Previous cardiac stress testing on a supine bicycle ergometer revealed nonspecific ST-T abnormalities. In June 2007, the patient was referred for computed tomography coronary angiography, which revealed a coronary anomaly, with the right coronary artery originating from the left coronary sinus and taking an interarterial course between the ascending aorta and the pulmonary trunk. There were no atherosclerotic alterations in the coronary arteries. Subsequent bicycle exercise stress and myocardial perfusion imaging revealed no myocardial perfusion defect.

Left ventricular congenital submitral aneurysm

A few days after arrival in Italy from Ghana, a 20-year-old black male presented with a history of fever, headache, nausea, vomiting, and atypical chest pain. Clinical neurological evaluation, brain MNR, and cerebrospinal fluid analysis were negative for CNS disease. ECG showed normal sinus rhythm with non-specific ST-T abnormalities (Panel A). Owing to the presence of chest pain, fever …

Myocardial Infarction in Healthy Adolescents

Chest pain in children and adolescents is a frequent cause for office or emergency department visits. However, it is unclear whether myocardial infarction occurs in children with no anatomic abnormality presenting with chest pain. Clinical history, electrocardiography, echocardiography, and cardiac enzyme levels were evaluated in patients presenting to the emergency department over a period of 11 years (June 1995 to May 2006). Patients in whom findings were suggestive of acute myocardial infarction, in addition, underwent drug screening, serum lipid profile, and hypercoagulability workup and, when myocardial infarction was diagnosed, heart catheterization with coronary angiography. Nine patients (8 boys; age range: 12-20 years; mean: 15.5 years) met established criteria for myocardial infarction. Abnormal electrocardiograms were found in 8 patients (6 with ST elevation and 2 with nonspecific ST-T abnormalities), abnormal cardiac enzyme levels in all, and echocardiographic abnormalities in 3. Cardiac dysrhythmias were found in 4 patients, 3 with nonsustained ventricular tachycardia. Drug abuse, lipid profile, and hypercoagulability studies were negative in all. Left ventricular focal hypokinesia was seen by echocardiogram or angiography in 5 patients and abnormal coronary anatomy in none. Cardiac function normalized in 8 patients. One patient had a persistent focal inferior hypokinesis. Calcium channel blocker therapy was initiated in all of the patients with no recurrence of anginal chest pain on follow-up. One patient complained of chest pain distinct from anginal pain. Myocardial infarction can occur in adolescents with normal coronary arterial anatomy. Adolescents who present for emergency care with typical chest pain need electrocardiographic and cardiac enzyme workups. Those with results that are suggestive of acute infarction require additional workup. Coronary vasodilation therapy seems helpful, but given the lack of coronary thrombosis in these patients, thrombolytic therapy seems unwarranted. Long-term follow-up is necessary, and adjustments in therapy may be required with time.

Incremental prognostic value of exercise single-photon emission computed tomographic (SPECT) thallium 201 imaging in patients with ST-T abnormalities on their resting electrocardiograms

The incremental prognostic value of thallium 201 imaging in patients with nonspecific ST-T abnormalities on the resting electrocardiogram (ECG) may be different from those with a normal resting ECG. Nine hundred thirty-nine consecutive patients with nonspecific ST-T abnormalities on their resting ECG who had undergone exercise 201 Tl imaging were followed for a median duration of 7.0 y (94% complete). The Cox proportional hazards regression model was used in a stepwise fashion to generate (1) a clinical (Cl) model, (2) a clinical and exercise (Cl + Ex) model, (3) and a clinical, exercise, and thallium (Cl + Ex + Tl) model, for the prediction of cardiac death. Age, sex, and diabetes composed the Cl model (chi2 = 63, P < .0001). The Duke treadmill score added to the Cl + Ex model (chi2 = 71, P < .0001). Increased lung uptake (P < .0001) added significantly and summed reversibility score ( P = .03) added modestly to the Cl + Ex + Tl model (chi2 = 96, P < .0001). On the basis of the Cl + Ex + Tl model, the low-, intermediate-, and high-risk groups had a 7-y survival free of cardiac death of 99%, 88%, and 58%, respectively (P < .0001). Using the Cl + Ex + Tl model, only a small number of low-risk and high-risk patients by the Cl + Ex model were reclassified. However, 48% of the 230 patients in the intermediate-risk group by the Cl + Ex model were reclassified as low risk or high risk. 201 Tl imaging has incremental prognostic value in patients with nonspecific abnormalities on their resting ECG. However, patients classified as low risk or high risk by exercise testing using the Cl + Ex model do not require 201 Tl imaging. Intermediate-risk patients should be further risk-stratified by 201 Tl imaging.

Leg edema, ST-T abnormalities, and high BNP values are important signs of heart failure in the elderly

This study was aimed at the mechanism of the circulatory failure characteristic of the elderly through elucidating the cause of leg edema frequently found in patients under treatment in health care facilities for physical or mental handicaps. ECG and measurement of atrial (ANP) and brain (BNP) natriuretic peptides were carried out on 156 patients (mostly females aged 84 years on average) and echocardiographic assessment was done on 44 patients. Non-specific ST-T abnormalities were frequently found in patients with moderate or severe leg edema (61 vs. 37% in those with slight or no edema). BNP levels were markedly increased in patients with either leg edema or ECG abnormalities (Group B) and with both (Group C) compared with those without either (Group A), with averages of 35.5±23.9, 91.3±80.1, and 184.3±139.0 pg/ml, respectively, for Group A, B, and C. UCG examination revealed marked regurgitation of cardiac valves, more frequently in patients with BNP over 50 pg/ml than in those with less (14/24 vs. 2/20), with a difference in extent of 5.7 versus 1.6 on an arbitrary scale. In addition to left ventricular hypertrophy, dilatation of the left atrium and inferior vena cava was frequently observed in patients with higher BNP levels. It is concluded that both cardiac valve regurgitation and myocardial damage represented by ST-T abnormalities on ECG result in heart failure characteristic of the elderly, and that an increase in BNP is an important sign of such heart failure.

Association of Nonspecific Minor ST-T Abnormalities with Cardiovascular Mortality: The Chicago Western Electric Study

DAVIGLUS, MARTHA L.; LIAO, YOULIAN; GREENLAND, PHILIP; DYER, ALAN R.; LIU, KIANG; XIE, XIAOYUAN; HUANG, CHENG-FANG; PRINEAS, RONALD J.; STAMLER, JEREMIAH Author Information