心电12导联与心内向量转换的论文有关心电12导联与心内向量转换的最新论文14 D. Cortez e

文件名称: 心电12导联与心内向量转换的论文

所属分类: 其它

开发工具:

文件大小: 1mb

下载次数: 0

上传时间: 2019-04-19

提供者: weixin_********

下载 (1mb)

不能下载？报告错误

详细说明：有关心电12导联与心内向量转换的最新论文14 D. Cortez et al. /Journal of Electrocardiology 47(2014)12-19 for a recent myocardial infarction (MD); and 2)data from the entered into Microsoft Excel, as one might imagine a first 50 subjects in the PtB database whose demographics clinician also eventually doing. Both inter-observer and files characterized them as"healthy controls, beginning intra-observer variation in the visual measurements were ith PTB subject 104 In the recent Mi group, the mean sd also studied age was 58.8+11.3 years, and 72% were males. In the healthy For comparison purposes the raw binary data files from control group, the mean t SD age was 43.5+ 14.7 years, and the Ptb database were also processed in a fully automated 76%were males. A second analysis was performed excluding fashion (i. e, without any visual dependence) by using those patients and subjects with bundle branch blocks(PTB software developed by the senior authors laboratory at files 010, 025, 078, 083,,,,, 123,126, NASAS Johnson Space Center 3, 4, 18. Initial analyses 130,131) revealed that all of the selected files except file 079(which demonstrated a paced rhythm) had at a minimum 40 QRS Data analyse complexes that were acceptable for automated signal averaging in all channels when using a minimum cross For all visual analyses, the first 10 seconds of the raw correlation cutoff of 97% against the signal-averaged QrS binary 12-lead ECG data files from the ptb database was templates formed for each channel in each file, as previously first converted to standard communications protocol for described [3, 4, 18]. Thus, 40-beat signal averages were also computer-assisted electrocardiography(SCP)format. The ltimately constructed for each patient's file, the principal SCP files were then visualized and manually quantified purpose of signal averaging being to help to eliminate any independently by two authors in the standard 10-mm/mv transient or non-reproducible effects that would more likel and 25-mm/s format using a publicly available SCP ECG influence single beats than signal averages, such as the viewer(Erasmus MC ECG Viewer software)as shown in precise location in the respiratory cycle when the data were Fig. 1. For simplicity sake, the angles shown and subsequent obtained Fully automated results for the spatial peaks Qrs statistical calculations are from the first observer's measure- T angle were then also calculated both directly, from the ments, while those from the second observer were used for Frank XYZ-lead recordings themselves (which served as the inter-observer variability. Visual estimates of the tallest " gold standard"), and from the simultaneous 12-lead ECG wave or deepest s wave, respectively, whichever was recordings by using the regression-related method of Kors absolutely greater, were specifically made, as were similar et al.[17 estimates for each relevant t wave. each to the nearest 0. 05 mV. while blindness was maintained to the true frank Statistics lead-related and other automated results. When beat-to-beat Statistical evaluations were performed using PSPP variation was found in any given amplitude, the tallest peak statistics program(Free Software Foundation INC) as well (or deepest trough) was used while also seeking out the as IBMs SPSS Statistics software, separately for the 100 flattest possible baselines. Those R or S and T voltage values post-myocardial infarction patients and the 50 healthy with the greatest deviations from the baseline were then the subjects, both before and after all patients with bundle inputs used in the respective visual transformation methods, branch bl clocks (five post-MI patients and eight control specifically in: 1) the regression-related and also quasi subjects) were excluded. Analysis of variance (ANOVA) orthogonal-related methods described by Kors et al.[17]; 2) was used to study differences in results from the true Frank the quasi-orthogonal method described by bjerle and leads versus those from each of the visually estimated Arvedson [22]; 3) the inverse Dower method as described methods. Pearson correlation coefficients were used to test by Edenbrandt and Pahlm 23]; 4) the method of Hyttinen et correlation of the visually estimated methods against the aL. [24; 5)both the post-myocardial infarction(MI)and gold-standard values from the true Frank leads as well as to healthy control-specific methods described by dawson et al test correlation of the visually estimated Kors'regression- 1251, and 6) the QRS-optimized method described by related spatial peaks ORS-T angle values against those Guillem et al. [26]. All of the above methods generally de derived from the fully software-automated Kors'regression- require advanced computerized techniques to obtain the related procedure. For the two visual methods that ultimately waveform amplitudes. However for this study, purely visual performed with the greatest precision, namely the Kors estimates of amplitudes from the scalar ECG from within the regression-related and Kors quasi-orthogonal methods, lines Erasmus mc ecg viewer software were used as the basis of concordance were also graphed comparing values of the for evaluating all of the above methods (with the online spatial peaks qrs-t angles derived from each against those appendix addendum, Table 1, summarizing the specific derived from the true frank lead gold standard. bland coefficients called for by cach individual visual method) Altman plots were also used to assess limits of agreement Calipers were not used but rather purely visual estimations to between angles derived from each aforementioned method within 0.05 mV, to best approximate results when calipers and the true Frank lead values [27] would not be available. A standard gain of 10 mm/mv was generally used, but when further clarity was necessary, the gain was adjusted as needed in the Erasmus MC ECO Results Viewer software, for example when the voltages from two different leads impinged upon one another at the 10-mm/mV Pearson correlation coefficients for the variability of the gain setting. These visually estimated amplitudes were visual estimates of the spatial peaks Qrs-t angle for the D. Cortez et al. /Journal of Electrocardiology 47(2014)12-19 Table 1 Spatial Pcaks QRS-T angle valucs, all cascs includcd Spatial peakS QRS-T Pearson correlation Bland-Altman 95% angle(), mean+ SD coefficient 2-tailed limits of agreement Control group(N= 50) Frank lead 41.7±27.1 1.00 Kors regression-related 40.7±23.5 0.78 0.01 isual Kors'regression-related 45.4±24.5 0. 0.01 38.9t031.8 Visual Kors quasi-orthogonal 46.4±23.0 0.76 39.0to30.1 Visual guillen 54.7±27.9 0.70 51.1to36.0 Visual Bjerle quasi-orthogonal 49.2±26.3 0.66 0.01 51.1to36.0 Visual hytinnen 41.6±219 0.61 0.01 43.1to43.8 Visual Dawson (for control) 77.7士37.4 0.62 0.01 94.8to22.5 Visual inverse dower 52.8±32.9 0.59 <0.01 70.1to43.3 Post-MI(N= 100) rat 68.9±40.9 00 Kors' regression-related 76.4±42.1 <0.01 Visual Kors’ regression-related中 756±39.4 0.82 <0.01 54.7to38.5 Visual Kors quasi-orthogonal 79.7±43.0 0.73 0.01 70.8to47.4 Visual guillem 80.2±42.2 0.74 0.01 72.5to462 Visual Bjerle quasi-orthogonal 5⊥4 0.51 <0.01 93.9to68.8 Hytinnen 69.3±38.2 0.70 0.01 60to57.5 Visual Dawson(for post-MD) 81.8±49.7 0.61 97.6to67.6 Visual Inverse Dower 73.5±42.3 0.71 0.01 70.2to57.2 Total group(N= 150) Frank lead 598±389 Kors regression -related 64.5±40.6 0.85 <0.01 Visual Kors regression-related 65.5士37.9 0.84 <0.01 498to36.7 Visual Kors quasi-orthogonal 68.6±40.6 0.7 0.01 6l.8to43.4 Visual guillem 71.7±40.2 0.76 0.01 67.1to40.8 Visual Bjerle quasi-orthogonal 70.8±40.1 0.60 0.01 Visual llytinnen 60.0⊥36.1 0.73 <0.01 56.3to53.4 Visual Dawson (post-MI I control) 80.4⊥459 0.59 <0.01 998to55.8 Visual invcrsc dower 66.6±40.5 0.71 0.01 69.0to52.7 Denotes fully automated method through specialized software b Denotes visual method with Pearson correlation coefficient closest to I Kors'regression-related and Kors quasi-orthogonal methods agreement, and with the smallest correlation coefficient were98 and 0.97(intra-observer variability ), and 0.95 and (0.59), was the visual Inverse Dower method 0.98(inter-observer variability ), respectively. Associated The Pearson correlation coefficients for the same Bland-Altman 95% confidence intervals were relatively control group but excluding those with bundle branch blocks narrow with lower to upper limits of-15.6 to+13.7(intra (Table 2) showed a similar order of corrclation and 95% limit observer) and-209 to +24. 1 (inter-observer), respectively. of agreement by method, but with mildly improved precision Table I shows the mean sD results for the spatial peal for the Kors' regression-related and quasi-orthogonal QRS T angle as well as the two-tailed p-values and pearson methods( correlation coefficients of0.80 correlation coefficients, against the gold-standard results for For the post-MI group again all methods produced results each transform in the control, post-MI and overall groups. for the spatial peaks Qrs-T angle that were not significantl Table 2 shows similar information but excluding all cases different from those produced by the true Frank leads. The with bundle branch blocks. Tables 1 and 2 also show the visual Kors'regression-related and Guillem et al. methods Bland-Altman limits of agreement for each visual method yielded the highest Pearson correlation coefficients at 0.82 compared to the true frank lead-related results for the spatial and 0.74, respectively while the least correlated method for QRS-T angle the post-MI patients was Bjerle and Arvedson's quasi Surprisingly, for the control group, all visually derived orthogonal method(correlation coefficient of 0.51). The spatial peaks QRS-T angles were not statistically signifi- narrowest Bland-Altman 95% limits of agreement were from cantly different than those automatically derived from the the Kors' regression-related followed by the Kors'quasi- true Frank leads. The visual estimation methods with largest orthogonal methods. The Pearson correlation coefficients fo Pearson correlation coeffi for the control group were the same post-MI group but excluding those with bundle Kors'regression-related and quasi-orthogonal methods, with branch blocks showed a similar order by visual method, again correlation coefficients of0. 76. The visual Kors' regression with improved correlation for the Kors'regression-related related and visual Kors quasi-orthogonal methods also and Guillem et al. methods(coefficient values of 0.88 and yielded the narrowest and second narrowest Bland-Altman 0.79, respectively), while the visual Kors quasi-orthogonal 95% limits of agreement, respectively The visual estimation (0.76)and Bland-Altman 95% limits of agreement Efficient method also produced a respectable correlation co method with the widest Bland-Altman 95% limits of D. Cortez et al. Journal of Electrocardiology 47(2014)12-19 Table 2 Spatial pcaks QRS-T angle valucs, excluding cascs with bundle branch blocks Spatial peakS QRS-T Pearson correlation p-Value Bland-Altman 95% angle(),mean±SD coefficient 2-tailed limits of agreement Control group(N=42) Frank lead 42.6±24.8 1.00 <0.01 -35.3to27.8 Kors'regression-related 42.1±24.7 0.90 <0.01 -51.1to36.20 Visual Kors'regression-related 46.6±25.4 0.80 0.01 -32.5to26.5 Ⅴ isual guillen 45.7±22.0 0.75 0.01 50.6to26.3 Visual Bjcrlc quasi-orthogonal 47,8±24.0 0.61 0.01 48.2to37.1 Visual hytinnen 43.6±22.4 <0.01 67.1to36.7 Ⅴ isual dawson control 76.7±39.7 0.69 0.01 -91.6to229 Ⅴ isual inverse dower 53.7±35.0 0.01 64.3to42.0 Post-MI (N=95) Frank lead 693±41.0 100 Kors regression-related 744士414 0.90 0.0)1 Ⅴ isual Kors’ regression- related 736±38.3 0.88 -44.3to32.5 Visual Kors quasi-orthogonal 78.3±42.0 0.76 64.4to444 Visual guillem 78.5±42.1 0.79 0.01 64.5to41.9 Visual berle quasi-orthogonal 80.4±40.3 0.54 0.01 88.7to644 Visual llytinnen 68.4⊥38.0 0.75 57.1to53.9 Visual dawson mi 79.9±48.9 0.64 <0.01 91.0to65.3 Visual inverse dower 72.0±41.7 0.75 <0.01 -63.3to54.0 Total (N=137) Frank lead a 61.1±38.7 1.00 Kors'regression-related 64.5±399 0.9 <0.01 Visual Kors'regression-related 65.3±36.9 0.88 41.7to31.2 Visual Kors quasi-orthogona 68.3±39.9 0.80 <0.01 56.3to40.6 Visual guillem 71.2±40.1 0.80 0.01 60.6to375 Visual Berle quasi-orthogonal 70.4±39.0 78.2to579 Visual Hytime 60.8±35.8 0.77 0.01 51.6to4192 Visual Dawson(controls I post-MD) 789⊥46.2 94.2to554 Visual inverse dower 664⊥40.5 0.74 0.01 63.8to504 Denotes fully automated method through specialized software b Denotes visual method with Pearson Correlation Coefficient closest to 1 For the total group(combined post-MI and controls), the control patients. This cutoff was chosen only for conve visual Kors regression-related and quasi-orthogonal nience, specifically as one other way of evaluating the methods again yielded the most correlated results, with relative methodological performance of the various visual correlation coefficients against the gold standard of 0. 84 and methods, in this case for distinguishing between the control 0.77, respectively, and with commensurate results for the and post-MI patients as determined by the true Frank leads Bland-Altman limits of agreement. As applied visually, the within the study data set itself. (It is not meant to provide methods described by Dawson et al.(combined control- any suggested cutoff value for clinical usage at large.) specific and post-MI-specific) yielded the lowest overall Pearson correlation coefficient (0.59) for the total group as Table 3 well as widest Bland-Altman 95%u limits of agreement. The Sensitivities and specificities for each vi method for detecting Pearson correlation coefficients for the total group without a spatial QRS-T angle value 2 standard deviations above the mean in bundle branch blocks showed a similar order of correlation by controls method, with improved coefficient values for the visual Kors Group Sensitivily(95% Specilicity(95% regression-related, Kors quasi-orthogonal, and Guillen et al confidence intervals confidence intervals) methods of 0.88, 0.80, and 0.80 respectively. As with the Frank lead 1.00(0.841.00) 1.00(0.961.0) individual groups more narrow limits of agreement were also Kors'regression-related 0.81(0.60-0.93) 0.93(0.86-0.96) noted when bundle branch blocks were excluded Visual Kors 0.89(069-0.97) 09400.87-0.97) Results from the overall most precise and accurate regression-related Visual Kors' 0.81(0.60-0.93) visual method(the visual Kors' regression-related method) 0.87(0.80-0.92) also showed good correlations with those from the Kor Visual guillem 0.81(0.60-0.9 0.90(0.82-0.94) regression- related method as derived fully automatically in Visual bjerke 0.77(0.56-0.90) 0.82(0.74-0.88 software (Pearson correlation coefficients between 0.92 quasi-othogonial and 0.93, exact values depending on the specifically Visual hytinnen 0.73(0.52-0.88) 0.94(0.87-0.97) Visual dawson studied group) 0.8100.60-0.93) 0.69(0.60-0.76) (MI+ control) Table 3 shows the methodological sensitivity and Visual inverse Dower 0.81(0.60-0.93) 0.86(0.78-0.91) specificity of each visual estimation method for detecting a true Frank lead-derived spatial peaks qrs-t angle value Mean t SD spatial peaks QRS-T angle from the true Frank leads in controls =41.7+27. 1 degrees >2 standard deviations above the mean value for the Two SD above that mean=95.8 degrees D. Cortez et al. /Journal of Electrocardiology 47(2014)12-19 17 r=076 Ba0 0.76 120 120 a100 a100 而,∽∝0 80 k80 的品O兰 120 140 100 120 Kors'regression-related spatial QRS-Tangle(degrees) Kors' quasi-orthogonal spatial QRS-Tangle(degrees 200 200 r=0.73 180 180 r=082 160 160 d140 140 120 120 100 旨曰80 60 3 2、 40·"32 20 020406080100120140160180200 020406080100120140160180200 Kors'regression-related spatial QRS-Tangle(degrees) Kors'quasi-orthogonal spatial QRS-Tangle( degrees Fig. 2. Lines of concordance for spatial peaks QRS-T angle results from the true Frank leads against those from the: (A)visually applied Kors' regression-related transform in controls; (B) visually applied Kors'quasi-orthogonal transform in controls; (C)visually applied Kors regression- related transform in post-MI patients; and(D) visually applied Kors' quasi-orthogonal transform in post-MI patients When methodological performance against the Frank lead rammed to apply Korset al 's transforms. Of the two related gold-standard results was quantified in this fashion visual-based estimates, the results from Kors'quasi- (Table 3), the visual Kors regression-related method again orthogonal method clearly showed more undesirable scatter had the best methodological performance of all visual around the line of best fit for both the controls and even methods tested more so for the post-MI patients Fig. 2A-D depicts concordance correlation plots. The values of the spatial peaks QRS-T angles from the true Frank leads are plotted with a line of best fit for each graph Discussion For each particular group of patients, control or post-MI the values for the gold-standard spatial peakS QRs-l The most important finding from this study is that spatial angles are shown against those derived from the two most peak QRS-T angle results derived from a purely visual overall precise visual methods, specifically from the visual application of Kors' regression-related transform can, with Kors regression-related and the visual Kors' quasi- reasonable accuracy and precision, estimate simultaneous, orthogonal methods, respectively. For all of the depicted automatically derived results from the true Frank leads plots, the spatial peaks QRS-T angles from the Kors- Correlation coefficients are typically the 0.78-0.90 range related procedures were visually estimated by first quickly but with exact values depending on the specific clinical group calculating the appropriate peak and/or trough r or S and being studied. Not unexpectedly, correlation coefficients T-wave voltages from the scalar ECG, and then inputting against the gold standard are slightly lower with purely visual those values into a simple Excel spreadsheet pre-pro- estimates than with estimates obtained by a fully automated D. Cortez et al. /Journal of Electrocardiology 47(2014)12-19 Kors'regression-related transform(0.90-0.91). Moreover would seem that when one utilizes a quasi-orthogonal these coefficients deteriorate slightly further whenever method in order to save time and maximize convenience, that bundle branch block cases are included in the analyses for now Kors et al. 's method would be the quasi-orthogonal The purely visually based implementations of other method of choice. Improvements to all transforms will likely transforms-specifically of Kors' simpler quasi-orthogonal require further studies that are iterative in nature, possibly method, Guillem et al.'s method (the coefficients of which starting with the best transforms currently in hand (i.e are advantaged by having been originally derived from the Kors,)and adding further"tweaks, " but in any case ideal same Physionet data set), Bjerle and Arvedson's quasi- employing both the standard and true Frank leads in orthogonal method, the inverse Dower method, Hytinnen et increasingly large populations. For now an alternative is al 's method and Dawson et al.'s methods performed that certain cell phone applications may eventually be able to with lesser (and varying) degrees of accuracy for both calculate the angle with even greater precision and accuracy healthy control subjects and post-MI patients, regardless of from a simple photo of the eCG, for example by using Kors whether patients with bundle branch blocks are included full eight-channel regression transform in conjunction with Bland-Altman 95% limits of agreement also followed a an image processing technique Simiar order Potentially the finding of greatest interest in relation to these other transforms was the fact that Kors quasi- Conclusion orthogonal method, which is arguably very simple (i.e, not is possible to visually estimate, with reasonable time consuming) to visually perform, gave the second highest Pearson's correlation coefficient for the control and precision and accuracy, the spatial peaks Qrs-T angle all groups, performing especially well when individuals from any standard scalar 12-lead eCg tracing. While with bundle branch blocks were excluded. This particular results from a visual application of Kors' full eight-channel regression transform most closely estimate simultaneous transform would only require that clinicians visually estimate the amplitudes of the Qrs and t waveform peaks results from the true frank leads (and even more closely and/or troughs in conventional leads Il. v2 and V6. and then estimate simultaneous results from a fully automated enter those estimates into a phone-, tablet- or other computer. implementation of Kors' regression transform), Kors'et based calculator al 's other transform--i.e, the quasi-orthogonal one--also Not surprisingly, most methods yielded slightly lower offers a potentially more convenient, albeit slightly less correlation coefficients when studying the post-MI group precise, method for visually accomplishing the same goal compared to the control group. Excluding subjects with Of note though is that especially with respect to purely bundle branch blocks from the analyses also tended to visual estimates, the precision of all methods improves improve pearson correlation coefficients and tighten bland when patients with bundle branch blocks are excluded. For Altman 95% limits of agreement for all methods. Such this reason when performing visual estimates of the spatial improvement might be expected from any visual method peaks QRS T angles on 12-lead ECGs, we would that closely approximates the true spatial peaks Qrs-tangle commend for now that patients with bundle branch blocks be excluded inasmuch as bundle branch blocks as well as the acuteness of such blocks, typically affect the maximum amplitudes of the An Excel spreadsheet application containing implementa- QRS and T-wave complexes [28]. Both the presence and tions of the Kors' regression-related and quasi-orthogonal dynamics of bundle branch blocks therefore likely add methods has been made available for free download at variability to visually based estimates. but clearly either with https://di.droPbox.com/u/45234083/spatial%20qrs- or without bundle branch blocks. the Kors'regression-related T%%20worksheet xIs and Kors'quasi-orthogonal methods yielded overall the best Supplementary data to this article can be found online at results for visually estimating the true Frank-related spatial http://dx.doi.org/10.1016/j-jelectrocard.2013.09.003 peaks QRs T angle from the scalar 12-lead ECG. However more "scatter" was observed for the visual Kors' quasi Acknowledgments orthogonal transform than for the visual Kors regression- The authors thank physionet and erasmus Mc for related transform, especially at larger absolute angles Also of note and not unexpectedly, the visually provision, respectively, of the online database and the SCP implemented Kors'regression-related transform had even ECG viewer utilized in this study higher Pearsons correlation coefficients(between 0.92 and 0.93 for controls, post-MI and total patients) when its results References were compared against those from the same but fully [1] Dilaveris P, Gialafos E, Pantazis A, Synetos A, Triposkiadis F software-automated Kors regression-related transform. On Gialafos J. The spatial QRS-T angle as a marker of ventricular the other hand for the quasi-orthogonal transforms, the repolarisation in hypcrtcnsion. J Hum Hypcrtcns 2001; 15: 63-70 choice of which scalar leads to use to estimate the .y and Z 2 Lipton JA, Nelwan SP, van Domburg RT, Kors JA, Elhendy A, directions is rather inherently fraught with difficulty and Schinkel AF, et al. Abnormal spatial QRS-T angle predicts mortality imprecision. However based on the relatively superior performance of the Kors' quasi-orthogonal method(over suspected coronary artery disease. Coron Artery Dis 2010: 21: 26-32 33 Poplack Potter SI, Holmqvist F, Platonov PCi, Steding K, Rheden H even some of the full eight-channel transform methods ), it Pahlm O, et al. Detection of hypertrophic cardiomyopathy is improved D. Cortez et al. /Journal of Electrocardiology 47(2014)12-19 Then using advanced rathcr than strictly conventional 12-lcad [15 Yamazaki T, Froclichcr VF, Mycrs J, Chun S, Wang P Spatial QRS-T electrocardiogram. J Electrocardio 2010: 43: 713-8 angle predicts cardiac death in a clinical population. Heart Rhythm [4] Schlegel TT, Kulecz WB, Feiveson AH, Greco EC, DePalma JL, 2005;2:73-8 V, et al. Accuracy of advanced versus strictly conventional 12 [16 Femlund E, Schlegel TT, Liuba P. Tissue Doppler imaging combined ECG for detection and screening of coronary artery disease, left with advanced 12-lead ECG analysis might improve early diagnosis of ventricular hypertrophy and lett ventricular systolic dysfunction. BMC hypertrophic cardiomyopathy in childhood Association for European Cardiovasc disord 2010: 10: 28 Paediatric Cardiology (AEPC). Grenada, Spain; 201 1: P-224 [5 Voulgari C, Tentolouris N, Moyssakis I, Dilaveris P. Gialafos E, 7 Kors JA, van Herpen G, Sittig AC, van Bemmel JH. Reconstruction of Papadogiannis D, et al. Spatial QrS-T angle: association with diabetes the Frank vectorcardiogram from standard electrocardiographic leads and len ventricular per formance. Eur J Clin Invest 2006, 36: 608-13 diagnostic coInparison of di[ferent methods. Eur Heart J 1990, 11 [6 Borleffs CJ, Scherptong RW, Man SC, van Welsenes gil, Bax JJ, van 1083-92. Erven L, ct al. Predicting ventricular arrhythmias in paticnts with [18 Cortcz DL, Schlcgcl TT When deriving thc spatial QRS-T angle from ischemic heart disease: clinical application of the ECG-derived QRS the 12-lead electrocardiogram, which transform is more Frank T angle. Circ Arrhythm Electrophysiol 2009: 2: 548-54 regression or inverse Dower? J Electrocardiol 2010: 43: 302-9 [7 de Torbal A, Kors JA, van Herpen G, Meij S, Nelwan S, Simoons ML, [19 Schreurs CA, Algra AM, Man SC, Cannegieter SC, van der Wall EE, et al. The electrical T-axis and the spatial QRS-T angle are Schalij M3, et al. The spatial QRS-T angle in the Frank vectorcardio independent predictors of long-term mortality in patients admitted gram: accuracy of estimates derived from the 12-lead electrocardio- with acute ischemic chest pain. Cardiology 2004; 101: 199-207 gram. J Electrocardio 2010: 43: 294-301 [8 Kardys I, Kors JA, van der Meer IM, Hofman A, van der Kuip Da [20 Bousseljot R, Kreiseler D, Schnabel A. Nutzung der eKG-Signalda Witteman JC. Spatial QRS-T angle predicts cardiac death in a general tenbank cardiodat der ptb uber das internet. Biomed Tech 1995 population. Eur Heart J 20037 24: 1357-64 40:S317-8 9 Kors JA, Kardys l, van der Meer IM, van Herpen G, Hofman A, van [21 Moody GB, Koch H, Steinhoff U. The Physionet/Computers in dcr Kuip Da, ct al. Spatial QRS-T angle as a risk indicator of cardiac Cardiology Challenge 2006: QT interval mcasurcmcnt. Comput death in an cldcrly population J Elcctrocardiol 2003 36(Suppl): 1 13-4 Cardiol2006;33:313-6. [10] Rautaharju PM, Ge S, Nelson JC, Marino Larsen EK, Psaty BM, 22] Bjerle P, Arvedson O. Comparison of Frank vectorcardiogram with Furberg CD, et al. Comparison of mortality risk for electrocardio two different vectorcardiograms derived from conventional eCo graphic abnormalities in men and women with and without coronary leads. Proc Eng Found 1986; 11: 13-26 heart disease(from the Cardiovascular Health Study). Am J Cardiol [23 Edenbrandt L, PahlmO. Vectorcardiogram synthesized from a 12-lead 2006:97:309-15 ECG: superiority of the inverse Dower matrix. I Electrocardio 1 988 [Il Rautaharju PM, Kooperberg C, Larson JC, LaCroix A Electrocardio 21:361-7 graphic predictors of incident congestive heart failure and all-cause [24 Hyttinen J, Viik J. Eskola H, Malmivuo J. Optimization and mortality in postmenopausal women: the Womens Health Initiative comparison of derived Frank VECG lead systems employing an Circulation 2000: 113: 481-9 accurate thorax model. Comput Cardiol 1995: 385-8 [12] Rautaharju PM, Kooperberg C, Larson JC, LaCroix A. Electrocardio 25 Dawson D, Yang H, Malshe M, Bukkapatnam ST, Benjamin B graphic abnormalities that predict coronary heart disease events and Komanduri R. Linear affine transformations between 3-lead(frank mortality in postmenopausal women: the Women's Health Initiative YZ leads) vectorcardiogram and 12-lead electrocardiogram signals Circulation 2006: 113: 473-80 J Electrocardio 2009: 42: 622-30 [13] Rautaharju PM, Prineas RJ, Wood J, Zhang ZM, Crow R, Heiss G 26 Guillem Ms, Sahakian AV, Swiryn S Derivation of orthogonal leads Electrocardiographic predictors of new-onset heart failure in men and from the 12-Lead ecg. accuracy of a single transform for the in women free of coronary heart disease (from the Atherosclerosis in derivation of atrial and ventricular waves. Comput Cardiol 2006: 3.3 Communities [ARIC] Study ) Am J Cardiol 2007; 100: 1437-4 249-52. [14] Triola B, Olson MB, Reis SE, Rautaharju P, Merz Cn, Kelsey SF, et al [27 Bland JM, Altman DG. Statistical methods for assessing agreement Electrocardiographic predictors of cardiovascular outcome in women betwe ethods of clinical measurement Lancet 1986: 1: 307-10 the National Heart, Lung, and Blood Institute-sponsored Womens 28 Shvilkin A, Bojovic B, Vajdic B, Vajdic B, Gussak l, Ho KK, et al Ischemia Syndrome Evaluation(WISE)study. J Am Coll Cardiol Vectorcardiographic and electrocardiographic criteria to distinguish 2005:46:51-6 new and old left bundle branch block Ileart Rhythm 2010: 7: 1085-92

(系统自动生成,下载前可以参看下载内容)