Raúl Correa

Novel set of vectorcardiographic parameters for the identification of ischemic patients

New signal processing techniques have enabled the use of the vectorcardiogram (VCG) for the detection of cardiac ischemia. Thus, we studied this signal during ventricular depolarization in 80 ischemic patients, before undergoing angioplasty, and 52 healthy subjects with the objective of evaluating the vectorcardiographic difference between both groups so leading to their subsequent classification. For that matter, seven QRS-loop parameters were analyzed, i.e.: (a) Maximum Vector Magnitude; (b) Volume; (c) Planar Area; (d) Maximum Distance between Centroid and Loop; (e) Angle between XY and Optimum Plane; (f) Perimeter and, (g) Area-Perimeter Ratio. For comparison, the conventional ST-Vector Magnitude (ST(VM)) was also calculated. Results indicate that several vectorcardiographic parameters show significant differences between healthy and ischemic subjects. The identification of ischemic patients via discriminant analysis using ST(VM) produced 73.2% Sensitivity (Sens) and 73.9% Specificity (Spec). In our study, the QRS-loop parameter with the best global performance was Volume, which achieved Sens=64.5% and Spec=74.6%. However, when all QRS-loop parameters and ST(VM) were combined, we obtained Sens=88.5% and Spec=92.1%. In conclusion, QRS loop parameters can be accepted as a complement to conventional ST(VM) analysis in the identification of ischemic patients.

Novel technique for ST-T interval characterization in patients with acute myocardial ischemia

BACKGROUND The novel signal processing techniques have allowed and improved the use of vectorcardiography (VCG) to diagnose and characterize myocardial ischemia. Herein, we studied vectorcardiographic dynamic changes of ventricular repolarization in 80 patients before (control) and during Percutaneous Transluminal Coronary Angioplasty (PTCA). METHODS We propose four vectorcardiographic ST-T parameters, i.e., (a) ST Vector Magnitude Area (aSTVM); (b) T-wave Vector Magnitude Area (aTVM); (c) ST-T Vector Magnitude Difference (ST-TVD), and (d) T-wave Vector Magnitude Difference (TVD). For comparison, the conventional ST-Change Vector Magnitude (STCVM) and Spatial Ventricular Gradient (SVG) were also calculated. RESULTS Our results indicate that several vectorcardiographic parameters show significant differences (p-value<0.05) before starting and during PTCA. Statistical minute-by-minute PTCA comparison against the control situation showed that ischemic monitoring reached a sensitivity=90.5% and a specificity=92.6% at the 5th minute of the PTCA, when aSTVM and ST-TVD were used as classifiers. CONCLUSIONS We conclude that the sensitivity and specificity for acute ischemia monitoring could be increased with the use of only two vectorcardiographic parameters. Hence, the proposed technique based on vectorcardiography could be used in addition to the conventional ST-T analysis for better monitoring of ischemic patients.

Analysis of QRS loop changes in the beat-to-beat Vectocardiogram of ischemic patients undergoing PTCA

In the present work, we have studied dynamic changes of QRS loop in the Vectocardiogram (VCG) of 80 patients that underwent Percutaneous Transluminal Coronary Angioplasty (PTCA). The VCG was obtained for each patient using the XYZ orthogonal leads of their electrocardiographic (ECG) records acquired before, during and after PTCA procedure. In order to analyze the variations of VCG, it has been proposed in this study the following parameters a) Maximum module of the cardiac depolarization vector, b) Volume, c) and Area of vectocardiographic loop corresponding to the QRS complex of each beat, d) Maximum distance between Centroid and the Loop, e) Angle between the XY plane and the Optimum Plane, f) Relation between the Area and Perimeter. The results obtained indicate that the parameters proposed show significant statistics differences (p-value<0.05) before, during (with some exceptions at the first minute of balloon inflation) and after PTCA. We conclude that the variations observed in the proposed parameters correctly represent not only the morphological changes in the depolarization VCG but also they reflect the modifications in the levels of cardiac ischemia induced by PTCA.

Acute myocardial ischemia monitoring before and during angioplasty by a novel vectorcardiographic parameter set

BACKGROUND This work evaluates the vectorcardiographic dynamic changes in ischemic patients before and during Percutaneous Transluminal Coronary Angioplasty (PTCA). METHODS Four QRS-loop parameters were computed in 51 ischemic and 52 healthy subjects with the objective of assessing the vectorcardiographic differences between both groups: maximum vector magnitude (QRS(mVM)), planar area (QRS(PA)), maximum distance between centroid and loop (QRS(mDCL)) and perimeter (QRS(P)).The conventional ST-change vector magnitude (STC(VM)), QRS-vector difference (QRS(VD)) and spatial ventricular gradient (SVG) were also calculated. RESULTS Statistical minute-by-minute PTCA comparison against a healthy population showed that ischemic patients monitoring is greatly enhanced when all the QRS-loop parameters, in combination with the standard STC(VM), QRS(VD) and SVG indexes, are used in the classification. Sensitivity and Specificity, in turn, reached rather high values, 95.4% and 95.2%, respectively. CONCLUSIONS These new vectorcardiographic set of complementary QRS-loop parameters, when combined with the classics STC(VM), QRS(VD) and SVG indexes, increase sensitivity and specificity for acute ischemia monitoring.

Analysis of QRS loop in the Vectorcardiogram of patients with Chagas' disease

In the present work, we have studied the QRS loop in the Vectorcardiogram (VCG) of 95 chronic chagasic patients classified in different groups (I, II and III) according to their degree of myocardial damage. For comparison, the VCGs of 11 healthy subjects used as control group (Group O) were also examined. The QRS loop was obtained for each patient from the XYZ orthogonal leads of their High-Resolution Electrocardiogram (HRECG) records. In order to analyze the variations of QRS loop in each detected beat, it has been proposed in this study the following vectorcardiographic parameters a) Maximum magnitude of the cardiac depolarization vector, b) Volume, c) Area of QRS loop, d) Ratio between the Area and Perimeter, e) Ratio between the major and minor axes of the QRS loop and f) QRS loop Energy. It has been found that one or more indexes exhibited statistical differences (p<0.05) between groups 0-II, O-III, I–II, I–III and II–III. We concluded that the proposed method could be use as complementary diagnosis technique to evaluate the degree of myocardial damage in chronic chagasic patients.

Identification of Patients with Myocardial Infarction

BACKGROUND The largest morbidity and mortality group worldwide continues to be that suffering Myocardial Infarction (MI). The use of vectorcardiography (VCG) and electrocardiography (ECG) has improved the diagnosis and characterization of this cardiac condition. OBJECTIVES Herein, we applied a novel ECG-VCG combination technique to identifying 95 patients with MI and to differentiating them from 52 healthy reference subjects. Subsequently, and with a similar method, the location of the infarcted area permitted patient classification. METHODS We analyzed five depolarization and four repolarization indexes, say: a) volume; b) planar area; c) QRS loop perimeter; d) QRS vector difference; e - g) Area under the QRS complex, ST segment and T-wave in the (X, Y, Z) leads; h) ST-T Vector Magnitude Difference; i) T-wave Vector Magnitude Difference; and j) the spatial angle between the QRS complex and the T-wave. For classification, patients were divided into two groups according to the infarcted area, that is, anterior or inferior sectors (MI-ant and MI-inf, respectively). RESULTS Our results indicate that several ECG and VCG parameters show significant differences (p-value<0.05) between Healthy and MI subjects, and between MI-ant and MI-inf. Moreover, combining five parameters, it was possible to classify the MI and healthy subjects with a sensitivity = 95.8%, a specificity = 94.2%, and an accuracy = 95.2%, after applying a linear discriminant classifier method. Similarly, combining eight indexes, we could separate out the MI patients in MI-ant vs MI-inf with a sensitivity = 89.8%, 84.8%, respectively, and an accuracy = 89.8%. CONCLUSIONS The new multivariable MI patient identification and localization technique, based on ECG and VCG combination indexes, offered excellent performance to differentiating populations with MI from healthy subjects. Furthermore, this technique might be applicable to estimating the infarcted area localization. In addition, the proposed method would be an alternative diagnostic technique in the emergency room.

Analysis of vectorcardiographic dynamic changes in patients with acute myocardial ischemia

This work evaluates the vectorcardiographic dynamic changes in ischemic patients before and during Percutaneous Transluminal Coronary Angioplasty (PTCA). Four vectorcardiographic parameters were computed in 51 ischemic and 52 healthy subjects with the objective of assessing the differences between both groups: ST Vector Magnitude Area (STVMa), T Vector Magnitude Area (TVMa), ST Vector Difference (STVD), and T Vector Difference (TVD). The conventional ST-Change Vector Magnitude (STCVM) and Spatial Ventricular Gradient (SVG) were also calculated. Results indicate that the most of them show significant differences between healthy and ischemic subjects. Since, the statistical minute-by-minute PTCA comparison against a healthy population shows that ischemic patients monitoring reached values of Sensitivity = 99.5% and Specificity = 99.4%, when STVD, TVD and SVG were used in the classification. In conclusion the sensitivity and specificity for acute ischemia monitoring could be increase with the used of only three vectorcardiographic parameters.

VCG and ECG indexes for classification of patients with Myocardial Infarction

We proposed aclassification technique for patients with Myocardial Infarction (MI), based on an Electrocardiographic (ECG) and Vectorcardiographic (VCG) signals analysis. We suggest and statistically analyzetwo VCGsandnine orthogonal ECG indexes, i.e., a) QRS loop Perimeter, b) Angle between QRS and T loops, c-e) the area under the QRS,T-wave and ST segment in X, Y and Z leads.

New VCG and ECG Indexes for Early Identification of Acute Myocardial Infarction Patients

A novel electrocardiographic (ECG) and vectorcardiographic (VCG) signal processing technique is proposed for identification of patients with Acute Myocardial Infarction (AMI). To this end, we propose a method based on two QRSloops features: a) Volume, and b) Planar Area; along with five orthogonal ECG indexes: c) ST-T vector difference, d) T vector difference, and e-g) the area under the T-wave in X, Y and Z leads. Our method was tested using ECG recordings of 97 AMIs and 52 healthy subject from the PhysioNet PTB database. The results indicate that these indexes show significant statistical differences (p-values <0.05) between the two populations (Healthy versus AMI population, with the exception of c). To validate the suggested index a 70/30 cross validation technique was used. Moreover, combining all parameters (with the exception of the T-wave area in Y and Z leads), it was possible to classify the AMI and healthy subjects with a sensitivity = 93.90%, a specificity = 93.44% and an accuracy = 93.73%, applying a linear discriminant classifier method. We conclude that the proposed technique could be used as an alternative diagnostic technique in the emergency room.

Cardiac Risk Assessment: When and Who? [Retrospectroscope]

Think about the above lines taken from the Old Testament: At 130 years of age, Adam begat a son and at 800 he kept going, quitting this earthly life at 930. These numbers surpass by far the limits our current experience teaches us, however, perhaps a life span into the hundreds of years is ? What if, in the future, science were to do away with disease? What then would cause people to die: accidents, killings, wars? How old would old age be? Aging has always been a hot topic for research (with considerable quackery, too). For example, animals with a slow metabolism tend to live longer than those with a fast metabolism. Compare the average life span of a mouse with that of a turtle. Apparently, meditators are able to slow their metabolism down [1].