Detection of coronary artery disease using maximum value of ST/HR hysteresis over different number of leads

ST segment/heart rate hysteresis improves the diagnostic accuracy of ECG stress test for coronary artery disease in patients with left ventricular hypertrophy

BACKGROUND

The exercise electrocardiographic stress test (ExET) is the most widely used non-invasive diagnostic method to detect coronary artery disease. However, the sole ST depression criteria (ST-max) have poor specificity for coronary artery disease in patients with left ventricular hypertrophy. We hypothesised that ST-segment depression/heart rate hysteresis, depicting the relative behaviour of ST segment depression during the exercise and recovery phase of the test might increase the diagnostic accuracy of ExET for coronary artery disease detection in such patients.

METHODS

In three cardiology centres, we studied 113 consecutive patients (mean age 66 ± 2 years; 88% men) with hypertension-related left ventricular hypertrophy at echocardiography, referred to coronary angiography after an ExET. The following ExET criteria were analysed: ST-max, chronotropic index, heart rate recovery, Duke treadmill score, ST-segment depression/heart rate hysteresis.

RESULTS

We detected significant coronary artery disease at coronary angiography in 61 patients (53%). At receiver-operating characteristic analysis, ST-segment depression/heart rate hysteresis had the highest area under the curve value (0.75, P < 0.001 when compared with the 'neutral' receiver-operating characteristic curve value of 0.5). Area under the curve values were 0.68 (P < 0.01) for the chronotropic index, 0.58 (P = NS) for heart rate recovery, 0.57 (P = NS) for ST-max and 0.52 (P = NS) for the Duke treadmill score.

CONCLUSIONS

Among currently available ExET diagnostic variables, ST-segment depression/heart rate hysteresis offers a substantially better diagnostic accuracy for coronary artery disease than conventional criteria in patients with hypertension-related left ventricular hypertrophy.

Contributions of myocardial ischemia and heart rate to ST segment changes in patients with or without coronary artery disease

BACKGROUND

ST changes related to ischemia at different heart rates (HRs) have not been well described. We aimed to analyze ST dynamic changes by vectorcardiography (VCG) during pacing-induced HR changes for subjects with proven coronary artery disease (CAD) and without (non-CAD).

METHODS

Symptomatic CAD patients scheduled for elective surgery were enrolled along with a non-CAD group. During anesthesia, both groups were placed at multiple ascending levels. VCG ST data, and in particular in ST change vector magnitude (STC-VM) from baseline, along with arterial and great coronary artery vein (GCV) blood samples were collected to determine regional myocardial lactate production.

RESULTS

A total of 35 CAD and 10 non-CAD patients were studied over six incremental 10 beat/min HR increases. STC-VM mean levels increased in the CAD group from 9+/-5 to 131+/-37 microV (standard deviation) compared with non-CAD subjects with 8+/-3-76+/-34 microV. Myocardial ischemia (lactate production) was noted at higher HRs and the positive predictive value for STC-VM to detect ischemia was 58% with the negative predictive value being 88%. STC-VM at 54 microV showed a sensitivity of 88% and a specificity of 75% for identification of ischemia.

CONCLUSIONS

Both HR and ischemia at higher HRs contribute to VCG ST elevation. Established ST ischemia detection concerning HR levels is suboptimal, and further attention to the effects of HR on ST segments is needed to improve electrocardiographic ischemia criteria.

Best leads in the standard electrocardiogram for the emergency detection of acute coronary syndrome

BACKGROUND AND PURPOSE

The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department.

METHODS

Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECGs from chest pain patients in the emergency department at Lund University Hospital.

RESULTS

The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%.

CONCLUSIONS

Our results indicate that leads III, aVL, and V2 are sufficient for computerized prediction of ACS. The present results are likely important in situations where the 12-lead ECG is impractical and for the creation of clinical decision support systems for ECG prediction of ACS.

The Finnish Cardiovascular Study (FINCAVAS): characterising patients with high risk of cardiovascular morbidity and mortality

Background

The purpose of the Finnish Cardiovascular Study (FINCAVAS) is to construct a risk profile – using genetic, haemodynamic and electrocardiographic (ECG) markers – of individuals at high risk of cardiovascular diseases, events and deaths.

Methods and design

All patients scheduled for an exercise stress test at Tampere University Hospital and willing to participate have been and will be recruited between October 2001 and December 2007. The final number of participants is estimated to reach 5,000. Technically successful data on exercise tests using a bicycle ergometer have been collected of 2,212 patients (1,400 men and 812 women) by the end of 2004. In addition to repeated measurement of heart rate and blood pressure, digital high-resolution ECG at 500 Hz is recorded continuously during the entire exercise test, including the resting and recovery phases. About 20% of the patients are examined with coronary angiography. Genetic variations known or suspected to alter cardiovascular function or pathophysiology are analysed to elucidate the effects and interactions of these candidate genes, exercise and commonly used cardiovascular medications.

Discussion

FINCAVAS compiles an extensive set of data on patient history, genetic variation, cardiovascular parameters, ECG markers as well as follow-up data on clinical events, hospitalisations and deaths. The data enables the development of new diagnostic and prognostic tools as well as assessments of the importance of existing markers.

ST-segment deviations during pacing-induced increased heart rate in patients without coronary artery disease

INTRODUCTION

In order to interpret ST-segment changes as an indicator of ischemia in patients with higher heart rates (HRs), the relation between ST-segment levels and HR needs to be well defined in subjects without coronary artery disease.

METHODS

Eighteen patients with normal ECGs in the catheterization laboratory, after radiofrequency ablation of AV nodal re-entry tachycardia or an accessory pathway were included. Computerized online vectorcardiography (VCG) was performed during step-wise atrial pacing-induced increases in HR up to 150 beats min(-1) (bpm). The ST-vector magnitude (ST-VM) and the relative ST change vector magnitude (STC-VM) were analysed at the J point, J + 20 and J + 60 ms.

RESULTS

There was no divergence in the course of ST-VM or STC-VM based on J point + 0, 20, or 60 ms during increasing HR. The STC-VM mean values increased progressively during increases in HR above 100 bpm, with an average increase in STC-VM of 15-20 microV per 10 bpm increases in HR. The ST-VM response during HR increases showed a heterogeneous and unpredictable pattern.

CONCLUSION

The STC-VM increases linearly with rising HRs above 100 bpm. The STC-VM can exceed widely recognized ischemic thresholds during higher HRs in the absence of ischemia. The choice of J point time to ST-VM measurements as tested here is not important for the STC-VM relation to HR at these HR levels. Further clinical testing is needed to improve the diagnostic specificity of STC-VM measurements during increased HRs.

Better decisions through science: exercise testing scores

Statistical tools can be used to create scores for assisting in the diagnosis of coronary artery disease and assessing prognosis. General practitioners and internists frequently function as gatekeepers, deciding which patients must be referred to the cardiologist. Therefore, they need to use the basic tools they have available (ie, history, physical examination and the exercise test) in an optimal fashion. Scores derived from multivariable statistical techniques considering clinical and exercise data have demonstrated superior discriminating power compared with diagnosis only using the ST segment response. In addition, by stratifying patients as to probability of disease and prognosis, they provide a more practical management strategy than a response of normal or abnormal. Although computers, as part of information management systems, can calculate complicated equations and derive these scores, physicians are reluctant to trust them. However, when represented as nomograms or simple additive discrete pieces of information, scores are more readily accepted. The scores have been compared with physician judgment and have been found to estimate the presence of coronary disease and prognosis as well as expert cardiologists and often better than nonspecialists. However, the discriminating power of specific variables from the medical history and exercise test remains unclear because of inadequate study design and differences in study populations. Should expired gases be substituted for estimated METs? Should ST/heart rate index be used instead of putting ST depression and heart rate separately into the models? Should right-sided chest leads and heart rate in recovery be considered? There is a need for further evaluation of these easily obtained variables to improve the accuracy of prediction algorithms, especially in women. The portability and reliability of scores must be ensured because access to specialized care must be safeguarded. Assessment of the clinical and exercise test data and application of the newer scores can empower the clinician to assure the cardiac patient access to appropriate and cost-effective cardiologic care.