Criteria for ECG detection of acute myocardial ischemia: Sensitivity versus specificity.

BACKGROUND: Criteria for electrocardiographic detection of acute myocardial ischemia recommended by the Consensus Document of ESC/ACCF/AHA/WHF consist of two parts: The ST elevation myocardial infarction (STEMI) criteria based on ST elevation (ST↑) in 10 pairs of contiguous leads and the other on ST depression (ST↓) in the same 10 contiguous pairs. Our aim was to assess sensitivity (SE) and specificity (SP) of these criteria-and to seek their possible improvements-in three databases of 12­lead ECGs. METHODS: We used (1) STAFF III data of controlled ischemic episodes recorded from 99 patients (pts) during percutaneous coronary intervention (PCI) involving either left anterior descending (LAD) coronary artery, right coronary artery (RCA), or left circumflex (LCx) coronary artery. (2) Data from the University of Glasgow for 58 pts with acute myocardial infarction (AMI) and 58 pts without AMI, as confirmed by MRI. (3) Data from Lund University retrieved from a centralized ECG management system for 100 pts with various pathological ST changes-other than acute coronary occlusion-including ventricular pre-excitation, acute pericarditis, early repolarization syndrome, left ventricular hypertrophy, and left bundle branch block. ST measurements at J-point in ECGs of all 315 pts were obtained automatically on the averaged beat with manual review and the recommended criteria as well as their proposed modifications, were applied. Performance measures included SE, SP, positive predictive value (PPV), and benefit-to-harm ratio (BHR), defined as the ratio of true-positive vs. false-positive detections. RESULTS: We found that the SE of widely-used STEMI criteria can be indeed improved by the additional ST↓ criteria, but at the cost of markedly decreased SP. In contrast, using ST↑ in only 3 additional contiguous pairs of leads (STEMI13) can boost SE without any loss of SP. In the STAFF III database, SE/SP/PPV were 56/98/97% for the STEMI, 79/79/79% for the STEMI with added ST↓ and 67/97/96% for the STEMI13. In the Glasgow database, corresponding SE/SP/PPV were 43/98/96%, 84/90/89%, and 55/98/97%. For the Lund database, SP was 56% for the STEMI, 24% for the STEMI with ST↓, and 56% for the STEMI13. CONCLUSION: Current recommended criteria for detecting acute myocardial ischemia, involving ST↓, boost SE of widely-used STEMI criteria, at the cost of SP. To keep the SP high, we propose either the adjustment of threshold for the added ST↓ criteria or a selective use of ST↓ only in contiguous leads V2 and V3 plus ST↑ in lead pairs (aVL, -III) and (III, -aVL).

Validation of the vessel-specific leads (VSLs) for detection of acute ischemia on a dataset with non-ischemic ST-segment deviation.

BACKGROUND: Existing criteria recommended by ACC/ESC for identifying patients with ST elevation myocardial infarction (STEMI) from the 12-lead ECG perform with high specificity (SP) but low sensitivity (SE). In our previous studies, we found that the SE of acute ischemia detection can be markedly improved without any loss of SP by calculating, from the 12-lead ECG, ST deviation in 3 "optimal" vessel-specific leads (VSLs). To further validate the method, we evaluated the SP performance using a dataset with non-ischemic ST-segment changes. METHODS: 12-lead ECGs of 100 patients (75 males/25 females, age range 12-83years, average age 52years) were retrieved from a centralized ECG management system at Skåne University Hospital, Lund, Sweden. These ECGs were chosen to represent five subgroups with various causes of pathological ST deviation, other than acute coronary occlusion: a) ventricular preexcitation (n=12), b) acute pericarditis (n=26), c) early repolarization syndrome (ERS) (n=14), d) left ventricular hypertrophy (LVH) with "strain" (n=26), and e) left bundle branch block (LBBB) (n=22). ECGs with inadequate signal quality, heart rate exceeding 120bpm and/or atrial flutter were not selected for this study population. Both STEMI criteria and VSLs criteria with and without a new augmented LVH-specific derived lead were tested. SP, calculated for each subgroup and combined, was used as the performance measure for comparison. RESULTS: SP test results for the STEMI criteria vs. the VSLs method without the augmented LVH lead were 100% vs. 92%, 4% vs. 88%, 29% vs. 100%, 100% vs. 77%, and 64% vs. 68% for the five subgroups with preexcitation, pericarditis, ERS, LVH, and LBBB, respectively. For the whole group, SP was 57% for the STEMI criteria and 83% for the VSLs criteria; this improvement was statistically significant (p<0.001). With the augmented LVH lead, SP for the VSLs improved from 77% to 96% for the LVH subgroup and SP for the other subgroups remained unchanged. For the whole study group, SP improved from 83% to 88%. CONCLUSION: Based on these results, we conclude that the VSLs criteria are not only more sensitive in detecting acute ischemia but also more specific in recognizing patients with non-ischemic ST deviation than the existing STEMI criteria. This finding needs to be further corroborated on a larger patient population with AMI prevalence typical of the population presenting to the emergency room.

Validation of improved vessel-specific leads (VSLs) for detecting acute myocardial ischemia.

BACKGROUND: Existing criteria recommended by ACC/ESC for identifying patients with ST elevation myocardial infarction (STEMI) from the 12-lead ECG perform with high specificity (SP), but low sensitivity (SE). In our previous studies, we found that the SE of ischemia detection can be markedly improved without any loss of SP by calculating, from the 12-lead ECG, ST deviation in 3 "optimal" vessel-specific leads (VSLs). Our original VSLs, based on ΔST body-surface potential maps (BSPMs), have been modified by using the more appropriate J-point BSPMs at peak ischemia (without subtraction of pre-occlusion distributions). The aim of the present study was to compare the performance of these new VSLs with that achieved by the STEMI criteria used in current practice. METHODS: Two independent datasets of 12-lead ECGs were used: the STAFF III dataset acquired during ischemic episodes caused by balloon inflation in LAD (n=35), RCA (n=47), and LCx (n=17) coronary arteries, and the Glasgow dataset comprising admission 12-lead ECGs of 116 patients who were hospitalized for chest pain and underwent contrast-enhanced cardiac MRI that confirmed AMI in 58 patients (50%). RESULTS: We found that, in the STAFF III dataset, the detection of ischemic state by the STEMI criteria attained SE/SP of 60/97%, whereas SE/SP values of VSLs were 72/98%. In the Glasgow dataset, STEMI criteria yielded SE/SP of 43/98%, whereas the VSLs improved SE/SP to 60/98%. The most significant increase in diagnostic performance appeared in patients with LCx coronary artery occlusion: in STAFF III data (n=17) SE achieved by STEMI criteria was improved by the VSLs from 35% to 71%; in Glasgow data (n=12) SE of 31% achieved by STEMI criteria was improved by the VSLs to 69%. CONCLUSION: In our study population, existing ACC/ESC STEMI criteria complemented by the new VSLs yielded much improved sensitivity of ischemia detection without any detrimental effect on specificity. This finding needs to be corroborated on a larger chest-pain patient population with typical prevalence of acute ischemia presented to the emergency rooms.

Decrease in health care resource utilization with MILD.

OBJECTIVE: To compare health care resource utilization before and after minimally invasive lumbar decompression (MILD) procedure. DESIGN: Case series. SETTING: Veteran's Administration health care system. SUBJECTS: All patients who underwent MILD at the author's institution. METHODS: The charts of 22 patients who underwent MILD procedure were reviewed. The primary comparison was between the amount of time spent in specialty care and the number of interventional procedures performed before and after MILD. Each patient's current status and need for continued specialty care were secondary measures. Patient satisfaction with MILD, and pre- and post-VAS were recorded as well. RESULTS: After MILD, there was close to 45% reduction in time spent in specialty care and an almost fourfold decrease in number of interventional pain procedures performed on patients with lumbar spinal stenosis (LSS). Over half the patients no longer required chronic pain management to treat their LSS symptoms. CONCLUSIONS: Not only is MILD a reliable method to treat LSS, MILD also appears to reduce the consumption of limited health care resources.

Discrimination of ST deviation caused by acute coronary occlusion from normal variants and other abnormal conditions, using computed electrocardiographic imaging based on 12-lead ECG.

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.

Comparison of epicardial potential maps derived from the 12-lead electrocardiograms with scintigraphic images during controlled myocardial ischemia.

Our aim was to cross-validate electrocardiographic (ECG) and scintigraphic imaging of acute myocardial ischemia. The former method was based on inverse calculation of heart-surface potentials from the body-surface ECGs, and the latter, on a single photon emission computed tomography (SPECT). A boundary-element torso model with 352 body-surface and 202 heart-surface nodes was used to perform the ECG inverse solution. Potentials at 352 body-surface nodes were calculated from those acquired at 12-lead ECG measurement sites using regression coefficients developed from a design set (n = 892) of body-surface potential mapping (BSPM) data. The test set (n = 18) consisted of BSPM data from patients who underwent a balloon-inflation angioplasty of either the left anterior descending coronary artery (LAD) (n = 7), left circumflex coronary artery (LCx) (n = 2), or the right coronary artery (RCA) (n = 9). Body-surface potential mapping distributions at J point for 352 nodes were estimated from the 12-lead ECG, and an agreement with those estimated from 120 leads was assessed by a correlation coefficient (CC) (in percent). These estimates yielded very similar BSPM distributions, with a CC of 91.0% ± 8.1% (mean ± SD) for the entire test set and 94.1% ± 1.4%, 96.7% ± 0.8%, and 87.4% ± 10.3% for LAD, LCx, and RCA subgroups, respectively. Corresponding heart-surface potential distributions obtained by inverse solution correlated with a lower CC of 69.3% ± 18.0% overall and 73.7% ± 10.8%, 84.7% ± 1.1%, and 62.6% ± 21.8%, respectively, for subgroups. Bull's-eye displays of heart-surface potentials calculated from estimated BSPM distributions had an area of positive potentials that qualitatively corresponded, in general, with the underperfused territory suggested by SPECT images. For the LAD and LCx groups, all 9 ECG-derived bull's-eye images indicated the expected territory; for the RCA group, 6 of 9 ECG-derived images were as expected; 2 of 3 misclassified cases had very small ECG changes in response to coronary-artery occlusion, and their SPECT images showed indiscernible patterns. In conclusion, our findings demonstrate that noninvasive ECG imaging based on just the 12-lead ECG might provide useful estimates of the regions of myocardial ischemia that agree with those provided by scintigraphic techniques.

The impact of numeric and graphic displays of ST-segment deviation levels on cardiologists' decisions of reperfusion therapy for patients with acute coronary occlusion.

The study purpose is to determine whether numeric and/or graphic ST measurements added to the display of the 12-lead electrocardiogram (ECG) would influence cardiologists' decision to provide myocardial reperfusion therapy. Twenty ECGs with borderline ST-segment deviation during elective percutaneous coronary intervention and 10 controls before balloon inflation were included. Only 5 of the 20 ECGs during coronary balloon occlusion met the 2007 American Heart Association guidelines for ST-elevation myocardial infarction (STEMI). Fifteen cardiologists read 4 sets of these ECGs as the basis for a "yes/no" reperfusion therapy decision. Sets 1 and 4 were the same 12-lead ECGs alone. Set 2 also included numeric ST-segment measurements, and set 3 included both numeric and graphically displayed ST measurements ("ST Maps"). The mean (range) positive reperfusion decisions were 10.6 (2-15), 11.4 (1-19), 9.7 (2-14), and 10.7 (1-15) for sets 1 to 4, respectively. The accuracies of the observers for the 5 STEMI ECGs were 67%, 69%, and 77% for the standard format, the ST numeric format, and the ST graphic format, respectively. The improved detection rate (77% vs 67%) with addition of both numeric and graphic displays did achieve statistical significance (P < .025). The corresponding specificities for the 10 control ECGs were 85%, 79%, and 89%, respectively. In conclusion, a wide variation of reperfusion decisions was observed among clinical cardiologists, and their decisions were not altered by adding ST deviation measurements in numeric and/or graphic displays. Acute coronary occlusion detection rate was low for ECGs meeting STEMI criteria, and this was improved by adding ST-segment measurements in numeric and graphic forms. These results merit further study of the clinical value of this technique for improved acute coronary occlusion treatment decision support.

Fabrication, calibration and evaluation of a phosphate ion-selective microelectrode.

To conduct the micro-environment study of flocs in an enhanced biological phosphorus removal (EBPR) process, a phosphate ion-selective microelectrode was developed. The cobalt-based microelectrodes have tip diameters of 5-20µm and respond to all the three forms of phosphate ions, namely, H(2)PO(4)(-), HPO(4)(2-), and PO(4)(3-). The calibration curve at pH 7.5 had a slope of 31.5mV per decade change of concentration and a R(2) value of 0.99. Other characteristics of this microelectrode, such as response time, interferences from pH, ion strength, DO and other anions were also evaluated.

Detection of myocardial ischemia by vessel-specific leads derived from the 12-lead electrocardiogram and its subsets.

Currently used electrocardiographic criteria for identifying patients with ST-elevation myocardial infarction (STEMI) perform with high specificity but low sensitivity. Our aim was to enhance ischemia-detection ability of conventional STEMI criteria based on 12-lead electrocardiogram (ECG) by adding new criteria using 3 vessel-specific leads (VSLs) derived from 12-lead ECG. Study data consisted of 12-lead ECGs acquired during 99 ischemic episodes caused by balloon inflation in, respectively, left anterior descending coronary artery (LAD; n = 35), right coronary artery (RCA; n = 47), and left circumflex coronary artery (LCx; n = 17). ST deviation was measured at J point in 12 standard leads, and for 3 VSLs, its value was derived from 12-lead ECG by using 8 independent predictor leads or just a pair of precordial leads combined with a pair of limb leads. Mean values of sensitivity (SE) and specificity (SP) of ischemia detection achieved with conventional STEMI vs VSL criteria were then obtained from bootstrap trials. We found that the detection of ischemic state by conventional criteria achieved the mean SE/SP of 60%/96% in the total set of ischemic episodes, 74%/97% in the LAD subgroup, 60%/94% in the RCA subgroup, and 36%/100% in the LCx subgroup. In comparison, the mean SE/SP values of VSLs derived from 8 independent leads of 12-lead ECG were, at 125-microV threshold, 76%(*)/96% in the total set, 91%(*)/97% in the LAD subgroup, 70%/94% in the RCA subgroup, and 71%(*)/100% in the LCx subgroup (with asterisk denoting a statistically significant increase). The mean SE/SP of VSLs derived from some of the 4-predictor lead sets (namely, those including lead V(3)) matched or exceeded values achieved by VSLs derived from 8 predictors; for instance, with predictor leads I, II, V(3), V(6) derived VSLs attained at 125-microV threshold the mean SE/SP of 80%(*)/95% in the total set, 91%(*)/97% in the LAD subgroup, 74%/92% in the RCA subgroup, and 71%(*)/100% in the LCx subgroup. Based on these results, we conclude that, in our data set, 3 VSLs derived from the complete standard 12-lead ECG-and even from its subsets-can identify acute ischemia better than existing STEMI criteria.

On designing and testing transformations for derivation of standard 12-lead/18-lead electrocardiograms and vectorcardiograms from reduced sets of predictor leads.

The aim of this study was to develop and evaluate transformation coefficients for deriving the standard 12-lead electrocardiogram (ECG), 18-lead ECG (with additional leads V7, V8, V9, V3R, V4R, V5R), and Frank vectorcardiogram (VCG) from reduced lead sets using 3 "limb" electrodes at Mason-Likar torso sites combined with 2 chest electrodes at precordial sites V1 to V6; 15 such lead sets exist and each can be recorded with 6-wire cable. As a study population, we used Dalhousie Superset (n = 892) that includes healthy subjects, postinfarction patients, and patients with a history of ventricular tachycardia. For each subject, 120-lead ECG recordings of 15-second duration were averaged, and all samples of the QRST complex for leads of interest were extracted; these data were used to derive--by regression analysis--general and patient-specific coefficients for lead transformations. These coefficients were then used to predict 12-lead/18-lead ECG sets and 3-lead VCG from 15 reduced lead sets, and the success of these predictions was assessed by 3 goodness-of-fit measures applied to the entire QRST waveform and to the ST deviation at J point; these 3 measures were similarity coefficient (SC in percentage), relative error (in percentage), and RMS error (in microvolts). Our results show that the best pair for predicting the standard 12-lead ECG by either general coefficients (mean SC = 95.56) or patient-specific coefficients (mean SC = 99.11) is V2 and V4; the best pair for deriving the 18-lead set by general coefficients (mean SC = 93.74) or by patient-specific coefficients (mean SC = 98.71) is V1 and V4; the best pair for deriving the Frank X, Y, Z leads is V1 and V3 for general coefficients (mean SC = 95.76) and V3 and V6 for patient-specific coefficients (mean SC = 99.05). The differences in mean SC among the first 8 to 10 predictor sets in each ranking table are within 1% of the highest SC value. Thus, in conclusion, there are several near-equivalent choices of reduced lead set using 6-wire cable that offer a good prediction of 12-lead/18-lead ECG and VCG; a pair most appropriate for the clinical application can be selected.

Atrial fibrillation detection using stationary wavelet transform analysis.

Atrial fibrillation (AF) is a common cardiac arrythmia that is usually developed for elder people with aging. AF may result in complications such as chest pain or even heart failure in later stage. Based on the characteristics of surface ECG, AF can be detected by several methods. A particular investigation on the fibrillatory waveform reveals the inherent structure of AF signals. As opposed to traditional frequency domain methods, we utilize the stationary wavelet transform to extract the information from ECG signal which differentiates AF and non-AF cases based on some feature extraction and selection processes. A linear classifier is then designed for computational efficiency. The proposed method eliminates the need for QRST cancellation step which is required for frequency domain methods and provides a more systematic approach for AF detection. Extensive experiments are tested on signals from the MIT-BIH Atrial Fibrillation Database to show the superior performance of the proposed algorithm.

An algorithm for QT interval monitoring in neonatal intensive care units.

QT surveillance of neonatal patients, and especially premature infants, may be important because of the potential for concomitant exposure to QT-prolonging medications and because of the possibility that they may have hereditary QT prolongation (long-QT syndrome), which is implicated in the pathogenesis of approximately 10% of sudden infant death syndrome. In-hospital automated continuous QT interval monitoring for neonatal and pediatric patients may be beneficial but is difficult because of high heart rates; inverted, biphasic, or low-amplitude T waves; noisy signal; and a limited number of electrocardiogram (ECG) leads available. Based on our previous work on an automated adult QT interval monitoring algorithm, we further enhanced and expanded the algorithm for application in the neonatal and pediatric patient population. This article presents results from evaluation of the new algorithm in neonatal patients. Neonatal-monitoring ECGs (n = 66; admission age range, birth to 2 weeks) were collected from the neonatal intensive care unit in 2 major teaching hospitals in the United States. Each digital recording was at least 10 minutes in length with a sampling rate of 500 samples per second. Special handling of high heart rate was implemented, and threshold values were adjusted specifically for neonatal ECG. The ECGs studied were divided into a development/training ECG data set (TRN), with 24 recordings from hospital 1, and a testing data set (TST), with 42 recordings composed of cases from both hospital 1 (n = 16) and hospital 2 (n = 26). Each ECG recording was manually annotated for QT interval in a 15-second period by 2 cardiologists. Mean and standard deviation of the difference (algorithm minus cardiologist), regression slope, and correlation coefficient were used to describe algorithm accuracy. Considering the technical problems due to noisy recordings, a high fraction (approximately 80%) of the ECGs studied were measurable by the algorithm. Mean and standard deviation of the error were both low (TRN = -3 +/- 8 milliseconds; TST = 1 +/- 20 milliseconds); regression slope (TRN = 0.94; TST = 0.83) and correlation coefficients (TRN = 0.96; TST = 0.85) (P < .0001) were fairly high. Performance on the TST was similar to that on the TRN with the exception of 2 cases. These results confirm that automated continuous QT interval monitoring in the neonatal intensive care setting is feasible and accurate and may lead to earlier recognition of the "vulnerable" infant.

An algorithm for continuous real-time QT interval monitoring.

QT interval measurement in the patient monitoring environment is receiving much interest because of the potential for proarrhythmic effects from both cardiac and noncardiac drugs. The American Heart Association and American Association of Critical Care Nurses practice standards for ECG monitoring in hospital settings now recommend frequent monitoring of QT interval when patients are started on a potentially proarrhythmic drug. We developed an algorithm to continuously measure QT interval in real-time in the patient monitoring setting. This study reports our experience in developing and testing this automated QT algorithm. Compared with the environment of resting ECG analysis, real-time ECG monitoring has a number of challenges: significantly more amounts of muscle and motion artifact, increased baseline wander, a varied number and location of ECG leads, and the need for trending and for alarm generation when QT interval prolongation is detected. We have used several techniques to address these challenges. In contiguous 15-second time windows, we average the signal of tightly clustered normal beats detected by a real-time arrhythmia-monitoring algorithm to minimize the impact of artifact. Baseline wander is reduced by zero-phase high-pass filtering and subtraction of isoelectric points as determined by median signal values in a localized region. We compute a root-mean-squared ECG waveform from all available leads and use a novel technique to measure the QT interval. We have tested this algorithm against standard and proprietary ECG databases. Our real-time QT interval measurement algorithm proved to be stable, accurate, and able to track changing QT values.