‘Hyper-Q’; technology or high-frequency QRS analysis (HF-QRS) is a relatively new non-invasive diagnostic method used for the detection of ischemic changes in electrocardiographic (ECG) traces, whether in the pre-hospital environment, during exercise testing, or during an attack of acute coronary syndrome [1][2]. Compared to conventional detection of myocardial ischemia, which is based on changes in the repolarization phase of the cardiac cycle (i.e., ST-segment), HF-QRS technology is based on the detection of these changes during depolarization of the myocardium (i.e., QRS wave) [3].

Electrophysiologically, the standard classic interpretation of ECG analyses the deviation of the repolarization phase of the cycle in the lower frequency spectrum between 0.05 Hz and 100 Hz, using signals of lower amplitude. However, it has recently been theoretically postulated and experimentally confirmed that ischemic changes can be detected earlier, during the depolarization phase of the cardiac cycle, which is represented by the so-called hyper QRS waveform of smaller amplitude and much higher frequency (i.e., in the range of 150–250 Hz ) [4][5]. To detect these subtle changes, it is necessary to apply a specially designed computer algorithm consisting of several steps, including identification and capture of appropriate QRS waves, and their filtration and analysis with the aforementioned algorithm. The variables that are usually analyzed are the so-called “Root Mean Squared” (RMS) voltage, and wave patterns known as a ‘reduced amplitude zone (RAZ)’. A decrease in the RMS and the presence of the RAZ are highly suggestive of acute myocardial ischemia [6].

First described in the 2000 [1], it has been extensively researched and clinically validated as an important diagnostic tool. So far, there is an evidence that:

• It has higher sensitivity in detecting acute coronary artery occlusion compared with conventional assessment of ST segment [6],
• It may improve noninvasive evaluation of coronary artery disease [7] ,
• It may improve the diagnosis of ischemia during exercise stress testing [8],
• In patients with chest pain, its valuable incremental prognostic role is particularly good in women [9].

However, little is known about the value of HF-QRS in pre-hospital setting. This study was performed to compare the results of HF-QRS and ST-segment changes derived from standard ECG test results between patients admitted to the accident and emergency (A&E) department for ischemic heart symptoms and a control group consisting of A&E departmental employees.

This prospective observational study was performed in two groups: a study group and a control group. The study group consisted of 24 patients, 21 of whom were admitted to the A&E department with some ischemic heart symptoms including chest pain and/or shortness of breath and palpitations. Remaining three patients came to A&E department for ‘non-cardiac symptoms’ that may have been a part of the silent coronary syndrome. The control group consisted of hospital employees who had undergone a health check-up within one year before participation in the study and had no symptoms of CAD. All of the participants provided written informed consent, and the study was approved by the hospital’s ethics committee. HF-QRS and ECG were performed in both patients and control subjects. HF-QRS data were recorded and analyzed by Cardiovit CS-200 Touch (Schiller, Switzerland) monitor. ST segment ECG changes were analyzed by authors 1 and 2, and the results were compared to the opinion of author 3. ST changes were: RS> 5 mm >rs, ST segment elevation or depression >1 mm and T wave changes. We also looked at a Q wave but there were no abnormal Q wave detected in any of our patients.

All of the demographic data, symptoms, and ECG changes/HF-QRS changes were examined for statistical significance using the chi-square test, Fisher’s exact test, or Student’s t-test as appropriate. Univariate logistic regression analyses were performed to find predictors of HF-QRS and ST-segment changes. The correlation between HF-QRS and ST-segment changes (Cramers V) was also calculated. P < 0.05 was taken to indicate statistical significance.

As given in (Table 1), control participants were an average of 10 years younger than the patients in the study group, and also had less history of diabetes mellitus and hypertension. However, both groups had similar family histories of cardiac disease, obesity, poor physical activity, stress, hyperlipidemia, and smoking. Patients in the control group had lower blood pressure and no cardiac or any other symptoms, as given in (Table 2). The incidence rates of ST-T changes and HF-QRS changes were not different between the control and study groups (Table 3). However, HF-QRS changes were more frequent than ST-T changes (29.3% vs 19.5%, p < 0. 0001). There were no correlations between ST-T and HF-QRS changes in the two groups (Cramers V 0.089, p = 0.568).

While abnormal ST-T changes were detected in only one patient in the control group (5.3%), abnormal HF-QRS was detected in four (23.5%) patients in this group. In univariate logistic regression analyses, the only predictor of positive HF-QRS was age (odds ratio [OR]: 1.112; 95% confidence interval [CI]: 1.019–1.213); each additional year of age was associated with an 11.2% increase in the risk of positive HF-QRS. For standardized age, the risk of HF-QRS increase was (OR: 4.436; 95% CI: 1.301–15.131), indicating a 4.43 higher risk of positive HF-QRS for one standard deviation increase in age. However, none of the variables was a predictor of ST-segment changes with significance level set at 0.05.

The examples of normal and abnormal HF-QRS analysis are respectively shown in (Figure 1) and (Figure 2).

To our knowledge, this is the first study looking at the HF-QRS in pre-hospital A&E setting. Our results are consistent with those of similar previous studies, looking at the HF-QRS changes in different settings. A previous study [10] compared the HF-QRS and conventional ECG analysis for diagnosis of stress-induced ischemia during exercise test, which was performed in a population of women with risk factors for CAD. Both tests were compared to coronarography as the gold standard. The results indicated that HF-QRS analyses were more sensitive and specific for the detection of significant coronary artery stenosis compared to classic ECG ST-T changes analysis. Other studies performed in women showed similar results [11][12]. In both of these studies, HF-QRS showed similar sensitivity and specificity compared to classic ECG analysis (78% and 86% vs. 77% and 83%, respectively). The results of these studies can easily be extrapolated to the general population because diagnosis is more difficult in women. the results of these studies can easily be extrapolated to the general population. Our results are also in accordance with those from a study by Conti et al. [9], who compared the diagnostic value of routine ST-T changes analysis of conventional ECG with HF-QRS analysis during exercise testing in a general population of patients with suspected CAD (i.e., chest pain and normal troponin tests, resting ECG, and echocardiography). In our study, each additional year of age was associated with an 11.2% increase in the risk of positive HF-QRS. Results of our pilot study suggest that HF-QRS analysis may find ts place for early detection of potential ischemic changes in A&E settings.

The main limitation of this study was the small size of the study population. Therefore, the results of the logistic regression analyses should be interpreted with caution. In addition, there was no patient follow-up, and we did not compare our ST-changes and HF-QRS results with clinical outcomes and coronary angiography results.

In our pilot study, HF-QRS analysis detected more electrocardiogram (ECG) changes indicating ischemia in acute settings than standard ECG ST segment changes. Larger studies are required to verify the role of HF-QRS technology in detecting early myocardial ischemia in pre-hospital setting.

1. www.bsp.co.il/hyperq-technology    
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