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Background: Myocardial perfusion SPECT (MPS) and exercise electrocardiography (Ex‐ECG) results are of prognostic importance for short‐term follow up duration. However, the value of MPS or Ex‐ECG findings for long‐term risk assessment is less evident as underlying risk factors for ischemic heart disease (IHD) gain in importance. Objectives: To assess the short‐ and long‐term prognostic value of MPS and Ex‐ECG in relation to known risk factors. Methods and Materials: An observational study of 908 patients (age 63 years, 49% male, 45% prior IHD) referred for MPS and Ex‐ECG. Follow‐up was divided into two periods (short‐term: <5 years and long‐term: >5 years). Cardiac events were defined as a composite of acute myocardial infarction, unstable angina, unplanned revascularization and cardiovascular death. Results: The composite endpoint occurred in 95 patients (short‐term follow up) and in 94 patients (long‐term follow up). In multivariable models stress testing had a strong predictive value for short‐term follow up (HR for MPS = 2.9, CI = 1.9–4.5, p < 0.001 and HR for Ex‐ECG = 2.1, CI 1.3–3.3, p = 0.002), but no predictive value for long‐term follow up (HR for MPS = 0.9, CI = 0.5–1.5, p = 0.70 and HR for Ex‐ECG = 1.0, CI = 0.6–1.6, p = 0.92). Male sex and prior IHD were significant predictors regardless of follow up duration. Age, diabetes and decreased exercise capacity were risk factors for long‐term follow up. Conclusions: The prognostic value of MPS and Ex‐ECG results are strong for short‐term follow up but diminish over time and do not contribute significantly in multivariable models after 5 years. Long‐term prognosis is primarily governed by underlying risk factors and exercise capacity. [ABSTRACT FROM AUTHOR]

Artificial neural networks can be used to recognize lead reversals in the 12-lead electrocardiogram at very high specificity, and the sensitivity is much higher than that of a conventional interpretation program. The neural networks developed in this and an earlier study for detection of lead reversals, in combination with an algorithm for the right arm/right foot lead reversal, would recognize approximately 75% of lead reversals encountered in clinical practice. [ABSTRACT FROM AUTHOR]

Abstract Background An early sign of heart failure (HF) is a decreased cardiac reserve or inability to adequately increase cardiac output during exercise. Under normal circumstances maximal cardiac output is closely related to peak oxygen uptake (VO2peak) which has previously been shown to be closely related to total heart volume (THV). Thus, the aim of this study was to derive a VO2peak/THV ratio and to test the hypothesis that this ratio can be used to distinguish patients with HF from healthy volunteers and endurance athletes. Thirty-one patients with HF of different etiologies were retrospectively included and 131 control subjects (60 healthy volunteers and 71 athletes) were prospectively enrolled. Peak oxygen uptake was determined by maximal exercise test and THV was determined by cardiovascular magnetic resonance. The VO2peak/THV ratio was then derived and tested. Results Peak oxygen uptake was strongly correlated to THV (r2 = 0.74, p < 0.001) in the control subjects, but not for the patients (r2 = 0.0002, p = 0.95). The VO2peak/THV ratio differed significantly between control subjects and patients, even in patients with normal ejection fraction and after normalizing for hemoglobin levels (p < 0.001). In a multivariate analysis the VO2peak/THV ratio was the only independent predictor of presence of HF (p < 0.001). Conclusions The VO2peak/THV ratio can be used to distinguish patients with clinically diagnosed HF from healthy volunteers and athletes, even in patients with preserved systolic left ventricular function and after normalizing for hemoglobin levels.

Abstract Background It is of great clinical importance to exclude myocardial infarction in patients with suspected coronary artery disease who do not have stress-induced ischemia. The diagnostic use of myocardial perfusion single-photon emission computed tomography (SPECT) in this situation is sometimes complicated by attenuation artifacts that mimic myocardial infarction. Imaging in the prone position has been suggested as a method to overcome this problem. Methods In this study, 52 patients without known prior infarction and no stress-induced ischemia on SPECT imaging were examined in both supine and prone position. The results were compared with cardiac magnetic resonance imaging (CMR) with delayed-enhancement technique to confirm or exclude myocardial infarction. Results There were 63 defects in supine-position images, 37 of which disappeared in the prone position. None of the 37 defects were associated with myocardial infarction by CMR, indicating that all of them represented attenuation artifacts. Of the remaining 26 defects that did not disappear on prone imaging, myocardial infarction was confirmed by CMR in 2; the remaining 24 had no sign of ischemic infarction but 2 had other kinds of myocardial injuries. In 3 patients, SPECT failed to detect small scars identified by CMR. Conclusion Perfusion defects in the supine position that disappeared in the prone position were caused by attenuation, not myocardial infarction. Hence, imaging in the prone position can help to rule out ischemic heart disease for some patients admitted for SPECT with suspected but not documented ischemic heart disease. This would indicate a better prognosis and prevent unnecessary further investigations and treatment.

Background Both myocardial perfusion single-photon emission computed tomography (MPS) and exercise ECG (Ex-ECG) carry prognostic information in patients with stable chest pain. However, it is not fully understood if combining the findings of MPS and Ex-ECG improves risk prediction. Current guidelines no longer recommend Ex-ECG for diagnostic evaluation of chronic coronary syndrome, but Ex-ECG could still be of incremental prognostic importance. Methods and Results This study comprised 908 consecutive patients (age 63.3±9.4 years, 49% male) who performed MPS with Ex-ECG. Subjects were followed for 5 years. The end point was a composite of cardiovascular death, acute myocardial infarction, unstable angina, and unplanned percutaneous coronary intervention. National registry data and medical charts were used for end point allocation. Combining the findings of MPS and Ex-ECG resulted in concordant evidence of ischemia in 72 patients or absence of ischemia in 634 patients. Discordant results were found in 202 patients (MPS-/Ex-ECG+, n=126 and MPS+/Ex-ECG-, n=76). During follow-up, 95 events occurred. Annualized event rates significantly increased across groups (MPS-/Ex-ECG- =1.3%, MPS-/Ex-ECG+ =3.0%, MPS+/Ex-ECG- =5.1% and MPS+/Ex-ECG+ =8.0%). In multivariable analyses MPS was the strongest predictor regardless of Ex-ECG findings (MPS+/Ex-ECG-, hazard ratio [HR], 3.0, P =0.001 or MPS+/Ex-ECG+, HR,4.0, P <0.001). However, an abnormal Ex-ECG almost doubled the risk in subjects with normal MPS (MPS-/Ex-ECG+, HR, 1.9, P =0.04). Conclusions In patients with chronic coronary syndrome, combining the results from MPS and Ex-ECG led to improved risk prediction. Even though MPS is the stronger predictor, there is an incremental value of adding data from Ex-ECG to MPS, especially in patients with normal MPS.

Introduction: We investigated if uptake pattern on myocardial perfusion SPECT (MPS) in patients with left bundle branch block (LBBB) is related to myocardial fibrosis, myocardial wall motion, and electrocardiography (ECG) characteristics., Methods: Twenty-three patients (9 women) with LBBB, examined with MPS and cardiac magnetic resonance (CMR), were included. Tracer uptake on MPS was classified by visual interpretation as typical LBBB pattern (Defect+, n = 13) or not (Defect-, n = 10) and quantitatively. CMR images were evaluated for wall thickness and for myocardial wall motion both by visual assessment and by regional myocardial radial strain from feature tracking, and for presence and location of myocardial fibrosis. ECGs were analyzed regarding QRS duration and the presence of strict criteria for LBBB., Results: Wall thickness was slightly lower in the septum compared to the lateral wall in Defect+ patients (5.6 ± 1.1 vs 6.0 ± 1.3 mm, P = 0.03) but not in Defect- patients (5.6 ± 1.0 vs 5.6 ± 0.9 mm, P = 0.84). Defect+ patients showed a larger proportion of dyskinetic segments in the septum and hyperkinetic segments in the lateral wall compared to Defect- patients (P = 0.006 and P = 0.004, respectively). Decreased myocardial radial strain was associated with decreased tracer uptake by MPS (R = 0.37, P < 0.001). Areas of fibrosis did not match areas with uptake defect on MPS. No differences in ECG variables were seen., Conclusion: The heterogeneous regional tracer uptake in some patients with LBBB is related to underlying regional myocardial dyskinesia, wall thickening, and wall thickness rather than stress-induced ischemia, myocardial fibrosis, or specific ECG characteristics., (© 2020. The Author(s).)

Background: This retrospective study aimed to determine the diagnostic performance of exercise-induced ST response in relation to findings by myocardial perfusion single photon emission computed tomography (MPS), with focus on gender differences, in patients with suspected or established stable ischemic heart disease., Methods: MPS findings of 1 021 patients (518 females) were related to the exercise-induced ST response alone (blinded and unblinded to gender) and ST response together with additional exercise stress test (EST) variables (exercise capacity, blood pressure and heart rate response)., Results: Exercise-induced ischaemia by MPS was found in 9% of females and 23% of males. Diagnostic performance of exercise-induced ST response in relation to MPS findings in females versus males was: sensitivity = 48%,70%; specificity = 67%, 64%; PPV = 13%, 38%; NPV = 93%, 87%. Adding more EST variables to the ST response interpretation yielded in females vs males: sensitivity = 44%, 51%; specificity = 84%, 83%; PPV = 22%, 48% and NPV = 93%, 85%., Conclusions: In patients who have performed EST in conjunction with MPS, there is a gender difference in the diagnostic performance of ST response at stress, with a significantly lower PPV in females compared to males. For both genders, specificity can be significantly improved, and a higher PPV can be obtained, while the sensitivity might be compromised by considering more EST variables, in addition to the ST response., (© 2017 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.)

Background: Evaluation of stress-induced ST deviations constitutes a central part when interpreting the findings from an exercise test. The aim of this analysis was to assess the pathophysiologic correlate of stress-induced ST elevation and ST depression with regard to presence, amount and location of myocardial ischemia as assessed by myocardial perfusion SPECT (MPS) in patients with suspected coronary artery disease., Methods and Results: 226 patients who had undergone bicycle stress test in conjunction with MPS were included. Of these, 198 were consecutive patients while 28 patients were included on the basis of having stress-induced ST elevation mentioned in their clinical report. The amount and location of ST changes were related to MPS findings. Summed stress scores (SSS) from MPS images were used to measure the amount of stress-induced ischemia. The positive predictive values for detecting stress-induced ischemia were 28% for the consecutive patients with ST depression and 75% for patients with ST elevation. The maximum and sum of stress-induced ST elevations correlated with SSS (r(2)=0.58, p<0.001 and r(2)=0.73, p<0.001), whereas the maximum and sum of significant ST depressions did not (r(2)=0.022, p=0.08 and r(2)=0.024, p=0.10). The location of ST elevation corresponded to the location of ischemia by MPS (kappa=1.0), whereas the location of ST depression did not (kappa=0.20)., Conclusions: Stress-induced ST elevation, with or without concomitant ST depression, is predictive of the presence, amount and location of myocardial ischemia assessed by MPS, whereas stress-induced ST depression without concomitant ST elevation is not., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Adenosine is widely used as a vasodilator agent in myocardial perfusion imaging. Caffeine inhibits the effect, but the time of caffeine abstinence needed is under discussion and varies from 12 to 24 h. Therefore, our aim was to examine whether the time of caffeine abstinence affects the hyperaemic response using quantification of coronary sinus flow (CS F) with cardiac magnetic resonance (CMR) during adenosine infusion., Methods: Healthy individuals (n = 16, eight females, age 41 ± 3 years) underwent two CMR examinations with 12 and 24 h of caffeine abstinence. CS F was quantified with phase-contrast velocity mapping (PC-)CMR during adenosine infusion (140 μg kg(-1)  min(-1) ) and rest and the CS F reserve between adenosine and rest was calculated. Myocardial perfusion (MP) was calculated as CS F × heart rate/left ventricular mass. Cardiac output (CO) was quantified using PC-CMR of the ascending aorta., Results: The CS F reserve was lower after 12 h abstinence compared to 24 h (4·31 ± 0·57 versus 5·32 ± 0·76, P = 0·03). In six of 16 subjects (38%), CS F reserve was >30% higher with longer caffeine abstinence. MP during adenosine was lower after 12 h compared to 24 h caffeine abstinence (3·59 ± 0·37 versus 4·23 ± 0·28 ml min(-1) g(-1) ; P = 0·046). The increase in CO during adenosine between the two occasions did not differ (55 ± 7% and 55 ± 6%, P = 0·11). Interobserver variability for CS F/heartbeat was -0·05 ± 1·00 ml., Conclusions: Hyperaemia during adenosine is lower in some patients with 12 h of caffeine abstinence compared to 24 h. Longer caffeine abstinence, that is 24 h, is of value before pharmacological stress testing as the individual response is not known and the individual variation is large., (© 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.)

Background: Studies of cardiovascular deconditioning are primarily carried out after experimental bed rest. No previous study has followed the cardiovascular effects of decreased and resumed physical activity in athletes after acute physical injury and convalescence. Anterior cruciate ligament (ACL) injury causes a significantly decreased activity level over a long period, making it an ideal model for studying effects of deconditioning and reconditioning. Therefore, the aim of this study was to investigate how cardiac dimensions and maximal exercise capacity change after an ACL-injury., Method: Seventeen athletes (5 women) were included. Cardiac magnetic resonance (CMR) was performed within 5 days of the injury (CMR1), before endurance training was resumed (CMR2) and 6 months after the second scan (CMR3). Maximal exercise testing was performed on the same day as CMR2 and 3., Results: The deconditioning phase between CMR1 and CMR2 was 59 ± 28 days. Total heart volume (THV) decreased with -3·1 ± 6·7%, P = 0·056. Between CMR2 and 3 (reconditioning), THV increased significantly (2·5 ± 4·6%, P<0·05). Left and right ventricular EDV decreased during deconditioning (-3·0 ± 5·6% and -4·7 ± 6·6%) and increased during reconditioning (1·7 ± 3·9% and 2·6 ± 6·2%) however not statistically significant. Left ventricular mass (LVM) remained unchanged. VO2 peak (mlmin(-1) kg(-1) ) increased significantly during the reconditioning phase (6·1 ± 5·3%, P<0·001)., Conclusion: Physiological cardiac adaptation to deconditioning and reconditioning caused by severe knee injury with maintained normal daily living during convalescence was smaller than previously shown in bed rest studies. Total heart volume and VO2 peak were significantly affected by reconditioning whilst LVEDV, RVEDV and LVM remained unchanged over the study period., (© 2013 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.)

Background: Many graphical methods for displaying ST-segment deviation in the ECG have been tried for enhancing decision-making in patients with suspected acute coronary syndromes. Computed electrocardiographic imaging (CEI), based on a mathematical inverse solution, has been recently applied to transform ST-J point measurements made in conventional 12-lead ECG into a display of epicardial potentials in bull's-eye format. The purpose of this study is to assess utility of CEI in the clinical setting., Methods: In 99 patients with stable coronary disease, 12-lead ECGs were recorded during elective percutaneous coronary intervention (PCI), first before balloon-catheter insertion and then when an intracoronary balloon blocked blood supply to a region of myocardium for more than 4minutes (typically 5minutes). Four groups of patients were additionally studied, namely those with preexcitation, pericarditis, early repolarization syndrome (ERS), and left ventricular hypertrophy (LVH) with strain. Comparisons between performances of published criteria for ST-elevation myocardial infarction (STEMI) and quantitative as well as visual assessment of CEI images were based on sensitivities and specificities., Results: Visual assessment of CEI outperformed STEMI criteria. This was especially evident for the capability of detecting LCx occlusion with sensitivities for STEMI criteria=35% and for visual assessment of CEI by 2 physicians=71%, i. e. twice as many patients were correctly identified by CEI. False positive rates for CEI were low in patients with LVH with strain as well as with preexcitation for both methods. For pericarditis and ERS, visual as well as quantitative assessment of CEI performed better than STEMI criteria., Conclusion: Visual assessment of CEI is a promising method for increasing the accuracy of ECG-based triage to PCI or conservative care., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: An early sign of heart failure (HF) is a decreased cardiac reserve or inability to adequately increase cardiac output during exercise. Under normal circumstances maximal cardiac output is closely related to peak oxygen uptake (VO2peak) which has previously been shown to be closely related to total heart volume (THV). Thus, the aim of this study was to derive a VO2peak/THV ratio and to test the hypothesis that this ratio can be used to distinguish patients with HF from healthy volunteers and endurance athletes. Thirty-one patients with HF of different etiologies were retrospectively included and 131 control subjects (60 healthy volunteers and 71 athletes) were prospectively enrolled. Peak oxygen uptake was determined by maximal exercise test and THV was determined by cardiovascular magnetic resonance. The VO2peak/THV ratio was then derived and tested., Results: Peak oxygen uptake was strongly correlated to THV (r2 = 0.74, p < 0.001) in the control subjects, but not for the patients (r2 = 0.0002, p = 0.95). The VO2peak/THV ratio differed significantly between control subjects and patients, even in patients with normal ejection fraction and after normalizing for hemoglobin levels (p < 0.001). In a multivariate analysis the VO2peak/THV ratio was the only independent predictor of presence of HF (p < 0.001)., Conclusions: The VO2peak/THV ratio can be used to distinguish patients with clinically diagnosed HF from healthy volunteers and athletes, even in patients with preserved systolic left ventricular function and after normalizing for hemoglobin levels.

Background: Previous studies have shown reduced high-frequency QRS components (HF-QRS) after acute myocardial infarction (MI). The purpose of this study was to investigate serial changes in HF-QRS during the first year following acute MI., Methods: A total of 75 patients were included. Standard- and high-frequency ECGs were recorded on five occasions during the year following the MI (a few days after the MI, after 6 weeks, and after 3, 6 and 12 months)., Results: There was a statistically significant increase in HF-QRS during the follow-up year (P = 0.002). There were no significant differences in HF-QRS when comparing either the infarct location or the presence or absence of reperfusive therapy. Large differences in HF-QRS were observed, both intra-individually and inter-individually, during the year., Conclusions: There was a statistically significant increase in HF-QRS during the year following acute MI.

The Anderson-Wilkins (AW) electrocardiographic (ECG) acuteness score complements time from pain onset in prognostic stratification of patients with acute myocardial infarction (AMI). However, for the AW acuteness score to be of practical use in the acute situation, it must be an integral component of a commercial automated ECG analysis program. The objective of this study was to determine the concordance between human and computer measurements and calculation of the AW acuteness score. The mean difference in AW acuteness score was 0.11 +/- 0.66 for anterior and -0.07 +/- 1.24 for inferior AMI. Ninety-nine percent of the differences were found to be 1.0 or less for the anterior AMI group, and 91.7% were 1.0 or less in the inferior AMI group. The differences were primarily caused by minor disagreements in measurements. In conclusion, the AW acuteness score established using manual ECG waveform measurements can be implemented into commercial automated ECG analysis programs to achieve practical use in clinical decision support for patients with AMI.

Background: Optimal treatment of acute myocardial infarction (AMI) depends on the duration of the ischemia. The Anderson Wilkins (AW) electrocardiographic acuteness score has been shown to complement the historical timing in estimating the time interval from acute thrombotic coronary occlusion in patients presenting with chest pain and evolving myocardial infarction. The purposes of this study were to (1) compare the distributions of the previously developed AW acuteness score in a training population with either anterior or inferior AMI and (2) propose modifications to the formula to achieve distributions similar to the observed distributions of historical times from onset of pain., Methods: Two hundred three and 177 patients were included as training and testing population, respectively. All patients had an anterior or an inferior AMI and were without confounding factors on the electrocardiogram., Results: The training population had similar distributions of historical times from onset of pain, but differences in distributions of AW acuteness scores, between patients with anterior and inferior AMI (P <.0001). Eighty percent of the inferior AMI group had the highest possible AW acuteness score. Modification of a Q-wave criterion from > or =30 to > or =20 ms resulted in similar distributions in patients with anterior and inferior AMI both in the training and an independent testing population., Conclusions: These results suggest that a modified AW acuteness score using a lower Q-wave duration criterion provides similar AMI timing information in patients with anterior and inferior locations. Clinical use of the AW acuteness score will only be practical if the calculation is automated.

An academic 12-lead electrocardiogram (ECG) core laboratory aims to provide the highest possible quality ECG recording, measurement, and storage to aid clinicians in research into important cardiovascular outcomes and to maximize the credibility of scientific results based solely, or in part, on ECG data. This position paper presents a guide for the structure and function of an academic ECG core laboratory. The key functional aspects are: 1) Data collection, 2) Staff composition, 3) Diagnostic measurement and definition standards, 4) Data management, 5) Academic considerations, 6) Economic consideration, and 7) Accreditation. An ECG Core Laboratory has the responsibility for rapid and accurate analysis and responsible management of the electrocardiographic data in multicenter clinical trials. Academic Laboratories, in addition, provide leadership in research protocol generation and production of research manuscripts for submission to the appropriate peer-review journals.

33 rheumatoid patients, treated with hemispherical cup resurfacing hemiarthroplasty of the shoulder without medullary fixation (6 bilaterally), were reviewed after mean 4.4 (2-6) years. The median Constant score was 30 (15-79), mean proximal migration of the humerus 55 (SD 5.2) mm and mean glenoid erosion 2.6 (SD 1.7) mm. Proximal migration and glenoid erosion did not correlate with shoulder function or pain. Radiographic signs of loosening (changes in cup inclination combined with changes in cup distance above the greater tuberosity) occurred in one quarter of the shoulders. At follow-up, 26 patients were satisfied with the procedure, despite poor shoulder function and radiographic deterioration.

Background: The 12-lead ECG, together with patient history and clinical findings, remains the most important method for early diagnosis of acute myocardial infarction. Automated interpretation of ECG is widely used as decision support for less experienced physicians. Recent reports have demonstrated that artificial neural networks can be used to improve selected aspects of conventional rule-based interpretation programs. The purpose of this study was to detect acute myocardial infarction in the 12-lead ECG with artificial neural networks., Methods and Results: A total of 1120 ECGs from patients with acute myocardial infarction and 10,452 control ECGs, recorded at an emergency department with computerized ECGs, were studied. Artificial neural networks were trained to detect acute myocardial infarction by use of measurements from the 12 ST-T segments of each ECG, together with the correct diagnosis. After this training process, the performance of the neural networks was compared with that of a widely used ECG interpretation program and the classification of an experienced cardiologist. The neural networks showed higher sensitivities and discriminant power than both the interpretation program and cardiologist. The sensitivity of the neural networks was 15.5% (95% confidence interval [CI], 12.4 to 18.6) higher than that of the interpretation program compared at a specificity of 95.4% (P<.00001) and 10.5% (95% CI, 7.2 to 13.6) higher than the cardiologist at a specificity of 86.3% (P<.00001)., Conclusions: Artificial neural networks can be used to improve automated ECG interpretation for acute myocardial infarction. The networks may be useful as decision support even for the experienced ECG readers.

Objectives: The purpose of this study was to compare the diagnoses of healed myocardial infarction made from the 12-lead electrocardiogram (ECG) by artificial neural networks and an experienced electrocardiographer., Background: Artificial neural networks have proved of value in pattern recognition tasks. Studies of their utility in ECG interpretation have shown performance exceeding that of conventional ECG interpretation programs. The latter present verbal statements, often with an indication of the likelihood for a certain diagnosis, such as "possible left ventricular hypertrophy." A neural network presents its output as a numeric value between 0 and 1; however, these values can be interpreted as Bayesian probabilities., Methods: The study was based on 351 healthy volunteers and 1,313 patients with a history of chest pain who had undergone diagnostic cardiac catheterization. A 12-lead ECG was recorded in each subject. An expert electrocardiographer classified the ECGs in five different groups by estimating the probability of anterior myocardial infarction. Artificial neural networks were trained and tested to diagnose anterior myocardial infarction. The network outputs were divided into five groups by using the output values and four thresholds between 0 and 1., Results: The neural networks diagnosed healed anterior myocardial infarctions at high levels of sensitivity and specificity. The network outputs were transformed to verbal statements, and the agreement between these probability estimates and those of an expert electrocardiographer was high., Conclusions: Artificial neural networks can be of value in automated interpretation of ECGs in the near future.

Misplacement of electrodes during the recording of an electrocardiogram (ECG) can cause an incorrect interpretation, misdiagnosis, and subsequent lack of proper treatment. The purpose of this study was twofold: (1) to develop artificial neural networks that yield peak sensitivity for the recognition of right/left arm lead reversal at a very high specificity; and (2) to compare the performances of the networks with those of 2 widely used rule-based interpretation programs. The study was based on 11,009 ECGs recorded in patients at an emergency department using computerized electrocardiographs. Each of the ECGs was used to computationally generate an ECG with right/left arm lead reversal. Neural networks were trained to detect ECGs with right/left arm lead reversal. Different networks and rule-based criteria were used depending on the presence or absence of P waves. The networks and the criteria all showed a very high specificity (99.87% to 100%). The neural networks performed better than the rule-based criteria, both when P waves were present (sensitivity 99.1%) or absent (sensitivity 94.5%). The corresponding sensitivities for the best criteria were 93.9% and 39.3%, respectively. An estimated 300 million ECGs are recorded annually in the world. The majority of these recordings are performed using computerized electrocardiographs, which include algorithms for detection of right/left arm lead reversals. In this study, neural networks performed better than conventional algorithms and the differences in sensitivity could result in 100,000 to 400,000 right/left arm lead reversals being detected by networks but not by conventional interpretation programs.

Artificial neural networks are computer-based expert systems that learn by example, in contrast to the currently used rule-based electrocardiographic interpretation programs. For the purpose of this study, 1,107 electrocardiograms (ECGs) from patients who had undergone cardiac catheterization were used to train and test neural networks for the diagnosis of myocardial infarction. Different combinations of QRS and ST-T measurements were used as input to the neural networks. In a learning process, the networks automatically adjusted their characteristics to correctly diagnose anterior or inferior wall myocardial infarction from the ECG. Two thirds of the ECGs were used in this process. Thereafter, the performance of the networks was studied in a separate test set, using the remaining third of the ECGs. The results from the networks were also compared with that of conventional electrocardiographic criteria. The sensitivity for the diagnosis of anterior myocardial infarction was 81% for the best network and 68% for the conventional criteria (p < 0.01), both having a specificity of 97.5%. The corresponding sensitivities of the network and the criteria for the diagnosis of inferior myocardial infarction were 78% and 65.5% (p < 0.01), respectively, compared at a specificity of 95%. The results indicate that artificial neural networks may be of interest in the attempt to improve computer-based electrocardiographic interpretation programs.