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Journal of Electrocardiolo

Prognostic significance of inverse spatial QRS-T angle circadian patternin myocardial infarction survivors

Georgios Giannopoulos, MD,a Polychronis Dilaveris, MD, FESC,a,⁎

Velislav Batchvarov, PhD, MD,b Andreas Synetos, MD,a Katerina Hnatkova, PhD,b

Konstantinos Gatzoulis, MD,a Marek Malik, PhD, MD, DSc, DScMed, FACC, FESC,b

Christodoulos Stefanadis, MD, FESC, FACCa

a1st Department of Cardiology, University of Athens Medical School, Hippokration Hospital, Athens, GreecebDepartment of Cardiac and Vascular Sciences, St. George's University of London, London, UK

Received 18 May 2008

Abstract Background: We investigated the predictive value of the spatial QRS-T angle (QRSTA) circadian

⁎ Corresponding aE-mail address: hr

0022-0736/$ – see frodoi:10.1016/j.jelectroc

variation in myocardial infarction (MI) patients.Methods: Analyzing 24-hour recordings (SEER MC, GE Marquette) from 151 MI patients(age 63 ± 12.7), the QRSTA was computed in derived XYZ leads. QRS-T angle values werecompared between daytime and night time. The end point was cardiac death or life-threateningventricular arrhythmia in 1 year.Results: Overall, QRSTA was slightly higher during the day vs. the night (91° vs. 87°, P = .005).However, 33.8% of the patients showed an inverse diurnal QRSTAvariation (higher values at night),which was correlated to the outcome (P = .001, odds ratio 6.7). In multivariate analysis, afterentering all factors exhibiting univariate trend towards significance, inverse QRSTA circadianpattern remained significant (P = .036).Conclusion: Inverse QRSTA circadian pattern was found to be associated with adverse outcome(22.4%) in MI patients, whereas a normal pattern was associated (96%) with a favorable outcome.© 2009 Elsevier Inc. All rights reserved.

Keywords: Myocardial infarction; Risk stratification; QRS-T angle; Circadian variation

Introduction

Risk stratification of post–myocardial infarction (MI)patients is a particularly relevant clinical issue, especially inthe era of device cardiology, which requires special measuresin order to target interventions and allocate efficiently theavailable resources. The heterogeneity of repolarization ofthe ventricular myocardium has been shown to be related tomechanisms of ventricular arrhythmias.1 In addition to otherelectrocardiographic (ECG) variables, such as the muchpromising heart rate turbulence2 and deceleration capacity,3,4

various descriptors of repolarization have been evaluated forrisk stratification, including QT variability, QT dispersion,and microvolt T-wave alternans, with various results.5-7

The spatial QRS-T angle (QRSTA) is a measure of thedeviation between the main QRS and T vectors calculated

uthor. Tel.: +30 2106531377; fax: +30 2106531377.odil1@yahoo.com

nt matter © 2009 Elsevier Inc. All rights reserved.ard.2008.07.002

from the net QRS and T wave areas,8 which reflects thevariations of the shape and durations of actions potentialsthroughout the ventricular myocardium, that is, the spatialrepolarization heterogeneity.9,10 It has been shown, inhealthy subjects, that this angle exhibits a circadian variation,being higher during the morning hours and lower during thenight.11 We report the potential prognostic significance ofalterations in this circadian pattern prospectively observed ina post-MI cohort.

Methods

Patient population and analysis of the Holter recordings

A 24-hour, 12-lead ambulatory digital ECG recording(SEER MC, GE Marquette) was obtained, before hospitaldischarge, in 151 consecutive patients with MI (age, 63 ±12.7; range, 37-93, 107 men), who were admitted to theUniversity Cardiology Department of Hippokration Hospital

80 G. Giannopoulos et al. / Journal of Electrocardiology 42 (2009) 79–84

in Athens. Eligible patients were those with an admissionand discharge diagnosis of either ST-elevation or non–ST-elevation MI, using standard clinical criteria. Patients with apacemaker (temporary or permanent) or Killip class IV onadmission or New York Heart Association functional statusIV after mobilization or in permanent atrial fibrillation wereexcluded. A 10-second, 12-lead digital ECG was obtainedevery 10 seconds, for a 24-hour period, after stabilization andmobilization of the patient and before discharge; the obtaineddigital data were automatically processed (ECG ResearchWorkstation, GE Marquette). No manual processing of ECGdata took place. The QRS and T-wave areas in predeterminedorthogonal XYZ leads were derived from the 12-lead QRSand T-wave areas using the transfer coefficients ofEdenbrandt and Pahlm,12 after which, the QRSTA wascomputed as an angle between the maximal spatial QRS andT vectors. Heart rate corrected QT (QTc) interval (Frider-icia's formula)13 and QRS duration were also computed foreach ECG. In each patient, the medians of the valuesrecorded in each 10-second ECG for 3 hours during daytime(8-11 AM) and night time (12-3.00 AM) were computed forheart rate, QT, QTc, and QRSTA. The standard deviation ofthe R-R intervals (SDNN) was also computed for eachpatient (SDNN was calculated straightforwardly from the24-hour recordings). These parameters, along with back-ground epidemiological and clinical features, were summar-ized as means for continuous variables and as percentages forcategorical variables.

All patients were submitted to standard 2-dimensionaland Doppler echocardiography shortly after their admissionand just before discharge. Left ventricular ejection fractionwas calculated following the recommendations of theAmerican Society of Echocardiography, and predischargemeasurements were used in the subsequent analysis.

All patients provided informed consent and theprotocol was approved by the competent Athens Uni-versity Review Board.

Follow-up

Patients were followed-up for a year after the index MI bymedical doctors, who were blinded as to the results of theECG analysis and the patients' clinical and epidemiologicaldata. The follow-up consisted in telephone contact andconsultation with the attending physicians and/or review ofthe medical files, where deemed necessary in order tocategorize the cause of death and/or the nature of suspectedmajor arrhythmic events. The composite end point of thestudy included cardiac death and/or sustained life-threateningarrhythmia (ventricular tachycardia or ventricular fibrillation)during the first year after the index MI. The procedure ofpatient follow-up and determination of end points in eachpatient was performed by consensus of 2 experiencedphysicians who did not participate or have any knowledgeof the data analysis and patient ECG or other clinical data.

Statistical analysis

Continuous variables are expressed as mean ± SEM.Continuous and categorical variables were compared using

the t test and the χ2 test, respectively. The percent day-night difference of the QRSTA in each patient wascalculated as the day-night difference of the medianQRSTA values (8-11 AM median minus 12-3 AM median)divided by the 8-11 AM median and multiplied by 100%. Areceiver's operating characteristic curve was plotted toestimate the ability of the percent day-night difference topredict the end point and determine the best cutoff value.An inverse circadian pattern was defined by a higher nightQRSTA median than day QRSTA median. The patientswere stratified according to the QRSTA circadian pattern,and Kaplan-Meier analysis was applied. We applied amultivariate Cox regression analysis model, enteringepidemiological, clinical, and ECG factors, which exhib-ited a univariate trend for significant correlation to theoutcome (P b .10). A P value of less than .05 wasconsidered statistically significant. SPSS 15.0 statisticalpackage (SPSS Inc, Chicago, Ill) was used.

Results

The event rate of the composite endpoint was 10.3%during the 1-year follow-up. Ten deaths were recorded, 3 ofwhich were due to noncardiac causes (metastatic coloncancer, cerebral hemorrhage, and extensive burns). Eightmore patients had episodes of documented sustainedventricular arrhythmia, so that a total of 15 patients metthe prospectively determined end point of our study. Sixpatients declined to answer follow-up questions at the1-year follow-up and were excluded from the final analysis(all six patients were alive 1 year after the index MI, but weconsidered their refusal to answer follow-up questions as ade facto withdrawal of consent; hence, we included them inthe survival analysis only up to the time point theyconsented to cooperate).

Overall, the QRSTA showed a statistically significant,although small (mean day-night difference, 4°), diurnalvariation, being higher during daytime (8-11 AM) thannighttime (12-3 AM): the averages of daytime vs night timemedians for all patients were 91° vs 87° (P = .005). Theaverage QRSTA in patients who met the end point was124.8°, which differed significantly from that in patients whodid not (84.6°, P = .001). The patients who met the end pointwere also significantly older, with lower left ventricularejection fraction, higher heart rate in the Holter recording,and lower heart rate variability (on the basis of SDNN) thanthose negative for the end point (Table 1).

The patients who met the end point had an averageQRSTA day-night difference of −12.9% (lower valuesduring the day) compared to +4.8% (higher values duringthe day) in those who did not meet the end point (P = .019).From the coordinates of the relevant receiver operatingcharacteristic curve, for the ability of the day-night QRSTAdifference to predict the end point, we were able to computethe cutoff value which provided for the best combination ofsensitivity and specificity. This cutoff value virtuallycoincided with zero (between −0,2% and +0,3%), and as aresult, we considered it appropriate to treat the day-nightQRSTA pattern as a dichotomous parameter and segregate

Table 2Population characteristics according to the QRSTA circadian pattern

QRSTA circadian pattern

Normal(n = 96)

Inverse(n = 49)

P

Age (y) 62.4 ± 1.3 64.8 ± 1.7 .279Sex (% men) 72 69 .755Left ventricular ejection fraction 0.46 ± 0.01 0.47 ± 0.01 .516Type of MI (% STEMI) 70 78 .488Thrombolysis (% positive) 51 57 .486Primary PCI (% positive) 25 24 .751β-blocker treatment (% positive) 81 80 .811Diabetes (% positive) 22 27 .531Smoking (% positive) 63 59 .698Hypertension (% positive) 40 55 .076Heart rate on admission(beats per min)

80 ± 2 80 ± 3 .934

Median heart rate (beats per min)a 67 ± 1 69 ± 1 .068SDNN (milliseconds) 115 ± 6 103 ± 6 .157Median QRSduration (milliseconds)a

95 ± 2 100 ± 6 .353

Median QTc (milliseconds)a 419 ± 2.4 408 ± 6.7 .056Median QRSTA (°)a 87.4 ± 4.7 91.4 ± 6.7 .629Endpoint rate (%) 4.1 22.4 .001

See Table 1 for abbreviations.a Median heart rate, QRS, QTc, and QRSTA refer to median values of

the 24-hour recording in each patient.

Table 3Cross-tabulation of results of the follow-up according to the observedQRS-T angle circadian variation pattern (the numbers represents counts)

End point

No death −no VT/VF

Deathor VT/VF

Total

Normal circadian pattern 92a 4b 96Inverse circadian pattern 38c 11d 49Total 130 15 145

a True negatives.b False negatives.c False positives.d True positives.

Table 1Overview of clinical and electrocardiologic variables in the study populationaccording to the outcome

End point

Negative(n = 130)

Positive(n = 15)

P

Age (y) 62.3 ± 1.1 70.7 ± 2.3 .014Sex (% men) 73 53 .110Left ventricular ejection fraction 0.47 ± 0.00 0.41 ± 0.02 .015Type of MI (% STEMI) 72 80 .488Thrombolysis (% positive) 51 73 .097Primary PCI (% positive) 24 27 .501β-blocker treatment (% positive) 82 67 .146Diabetes (% positive) 19 60 .001Smoking (% positive) 65 33 .018Hypertension (% positive) 43 60 .212Heart rate on admission(beats per min)

79 ± 2 86 ± 5 .160

Median heart rate (beats per min)a 67 ± 2 75 ± 1 .001SDNN (milliseconds) 114 ± 5 84 ± 9 .031Median QRSduration (milliseconds)a

96 ± 3 104 ± 6 .292

Median QTc (milliseconds)a 416 ± 3 412 ± 4 .659Median QRSTA (°)a 84.6 ± 4 124.8 ± 11 .001Inverse pattern (%) 29.2 73.3 .001

PCI indicates percutaneous coronary intervention; STEMI, ST-elevationmyocardial infarction.

a Median heart rate, QRS, QTc, and QRSTA refer to median values ofthe 24-hour recording in each patient.

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patients between those who had a normal QRSTA circadianpattern (lower values at night, positive day-night difference)and those with inverse circadian pattern (higher values atnight, negative day-night difference).

Inverse circadian pattern was observed in 49 patients(33.8%). Mean daytime and nighttime QRSTA valueswere 92.9° ± 5.0° and 79.8 ± 4,9°, respectively, inpatients with normal circadian pattern and 87.8 ± 6.7° and99.4 ± 6.9°, respectively, in patients with inverse pattern.There was no significant univariate correlation of theinverse pattern to patient age, sex, left ventricular ejectionfraction, heart rate on admission, heart rate in the 24-hourrecording, SDNN, QT and QTc, median QRSTA, the typeof MI (ST-elevation or non–ST-elevation MI), primaryreperfusion, β-blocker treatment; in addtion inverseQRSTA circadian pattern was observed independently ofthe presence of diabetes mellitus, smoking, dyslipidemia,arterial hypertension or family history of coronary heartdisease (see Table 2).

Significantly more patients among those with inversepattern met the end point (22.45 %) than among those withnormal pattern (4.17 %). In absolute counts, of the 96patients with normal QRSTA circadian pattern, only 4 metthe end point, whereas 11 patients of the 49 with inversepattern died or presented an episode of life-threateningventricular arrhythmia (see Table 3 for a cross-tabulation ofresults). Thus, the relative risk for those with inverse patternversus those with normal pattern was 5.5 and the univariateodds ratio 6.7 (95% confidence interval: 2.0-22.0). Thesensitivity of the inverse circadian pattern in predicting anevent was 73%, and its specificity was 71%. The negativepredictive value was 96%.

Multivariate analysis

In order to test whether the correlation of the QRSTAinverse circadian pattern to the outcome remained signifi-cant after accounting for clinical or epidemiological factorswith potential prognostic power, we applied a Coxregression analysis model, entering all parameters with aunivariate correlation to the outcome significant at a level ofat least 0.10 (P b .10). Therefore, we entered age, leftventricular ejection fraction, diabetes, smoking, heart rate inthe 24-hour recording, SDNN, thrombolytic treatment, andQRSTA circadian pattern. Inverse QRSTA circadian patternremained significant in the final equation (Wald statistic =4.7, P = .030). It even remained significant after the medianQRSTA was added to the model (Wald statistic = 4.4, P =.036), indicating an independent predictive value of thecircadian pattern. According to the multivariate analysis, thepresence of an inverse QRSTA circadian pattern indepen-dently increased hazard by a factor of 3.6 (95% confidence

Table 4Multivariate levels of significance and hazard ratios (Cox regression analysisentering all variables showing a univariate trend [P ≤ .10] towardssignificance) including (lower section) and not including (upper section) theabsolute QRSTA value in the analysis

Multivariate P Hazard ratio 95% CI

Age (y) .315 1.031 0.971-1.094Left ventricular

ejection fraction (%).722 0.988 0.923-1.057

Diabetes .242 2.316 0.566-9.473Smoking .747 1.258 0.312-5.072Median heart rate

(beats per min).146 1.051 0.983-1.125

SDNN (milliseconds) .634 0.996 0.980-1.013Thrombolysis .052 3.015 0.920-12.514Inverse QRSTA

circadian pattern.030 3.770 1.140-12.463

Multivariate P Hazard ratio 95% CI

Age (y) .354 1.030 0.967-1.098Left ventricular

ejection fraction (%).941 0.997 0.928-1.072

Diabetes .418 1.825 0.425-7.833Smoking .651 1.400 0.326-6.016Median heart rate

(beats per min).256 1.040 0.972-1.113

SDNN (milliseconds) .642 0.996 0.980-1.012Thrombolysis .054 3.010 0.912-12.851Inverse QRSTA

circadian pattern.036 3.597 1.084-11.937

Median QRSTA (°) .100 1.013 0.998-1.028

See Table 1 for abbreviations. CI indicates confidence interval.Median heart rate refers to median value of the 24-hour recording of eachpatient.For continuous variables, hazard ratio refers to the additional hazardconferred by an increase of 1 U of the variable. For categorical variables,hazard ratio refers to the hazard conferred by the presence of the variable, asopposed to absence.

82 G. Giannopoulos et al. / Journal of Electrocardiology 42 (2009) 79–84

interval, 1.08-11.9). See Table 4 for details of the multi-variate analysis.

Kaplan-Meier analysis

The Kaplan-Meier analysis showed a statistically sig-nificant difference in survival between patients with normaland inverse QRSTA circadian pattern (Mantel-Cox statistic =11.9, P = .001). The cumulative survival Kaplan-Meiercurves are shown in Fig. 1.

Fig. 1. Kaplan-Meier cumulative event-free survival curves of post-myocardial-infarction patients stratified according to their pattern ofcircadian spatial QRS-T angle variation (continuous line: normal pattern;broken line: inverse pattern).

Discussion

The present study prospectively demonstrates the prog-nostic value of an inverse circadian pattern of the QRSTA ina well-defined population of post-MI patients. To ourknowledge, this is the first report of such a finding. Ourobservations reiterate previous reports on the diurnalvariation of the QRSTA,11 identifying, at the same time, asignificant subgroup of post-MI patients with blunted andeven inversed day-night variation. This inverse patternappears to be a significant predictor of the one-year outcome,independently of a battery of clinical and epidemiologicalfactors and despite the use of beta-blocking agents in the vastmajority of these patients; this fact not only suggests that the

inverse QRSTA circadian pattern might be used in risk-stratifying MI survivors but also implies that it has deeperpathophysiological roots and does not simply represent a by-product of post-MI medical treatment and hospitalization,which might alter patient circadian rhythms in a transient andnonsignificant way.

The theoretical base of studying the QRSTA as a riskstratifier lies mainly in previous studies demonstrating aprognostic value, of various degrees of significance, either ofthe QRSTA14-16 or of the total cosine of R-to-T (TCRT,another mathematical expression of the concept of ventriculargradient, with a different methodology of calculation),17

either retrospectively18 or through post hoc analysis ofprospectively collected data,19,20 although there have beencontradicting reports.20

Circadian variations have been reported in repolarizationindices, mainly QT and QTc intervals,21 although it seemsthat QTc variation might be attributed, at least in part, toinconsistencies in QT-interval measurement and correctionfor heart rate,22 rather than reflect a true physiologicalsubstrate. The diurnal variation in global repolarizationheterogeneity, on the other hand, as represented by theTCRT, seems to be an undeniable fact in healthyindividuals.11 In post-MI patients, blunting of the diurnalvariation of repolarization indices has been reported.22

However, the circadian behavior of the QRSTA in post-MIpatients and, more importantly, its prognostic significancehave not been adequately studied so far.

An interesting point of our findings is that the inverseQRSTA circadian pattern retains its prognostic significanceeven when entering QRSTA values in the multivariate Coxmodel (ie, its predictive value is largely independent of theabsolute QRSTAvalues). This may be particularly importantin view of the fact that QRSTA has an inherent disadvantage:QRS- and T-wave loops are reconstructed in 3-dimensionalspace, defined by 3 predetermined XYZ axes; this method is

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adequate when the loops are regularly shaped and well-defined but becomes problematic when the loops are wideand convoluted in the three dimensional space, making theirrepresentation by a single dipole inadequate23—that is why adifferent methodology of calculating this angle, based on anonpredetermined system of reference axes,17 has beenintroduced (constituting the basis of calculation of TCRT).However, this should be less of a problem when using thediurnal variation of the QRSTA as a potential predictor ofevents, because, in this case, absolute angle values are notimportant: daytime and nighttime values from the samepatient are compared. Indeed, in our study, the value of theQRSTA did not differ between patients with inverse andnormal circadian pattern, which implies that the circadianpattern provides prognostic information largely unrelated toand independent of the absolute value of the angle itself.

A possible pathophysiologic basis of the observedprognostic significance may be associated to the alterationsin autonomic tone observed in post-MI patients, whichaffect repolarization and, thus, the QRSTA.22,24 QRSTAhas also been shown to be significantly different betweensexes,11 which implies that it is influenced by hormonaland humoral factors. An inverse circadian pattern of theQRSTA might thus be an indication of severe disruptionof normal autonomic function (known to be linked toincreased vulnerability to arrhythmia,25 especially whencoupled with repolarization abnormalities)26 and hormonalcircadian cycles in certain post-MI patients, who are, as aresult, at a relatively higher risk of an adverse outcome.

Repolarization descriptors as risk stratifiers

The repolarization phase of the cardiac excitation cyclehas received research attention in the form of severaldifferent approaches, such as T-wave loop dispersion, QTdispersion, QT variability, and T-wave alternans. Perkiomakiet al20 reported that T-wave loop dispersion predicts cardiacmortality, whereas Zabel et al27 showed prospectively thatQT dispersion does not carry independent prognostic value.As far as QT variability is concerned, in a subanalysis of theMulticenter Automatic Defibrillator Implantation Trial(MADIT) II study, increased QT variability was associatedwith higher risk of ventricular arrhythmia.28 On a moreapplied level, microvolt T-wave alternans has been shown topossess significant predictive value in post-MI patients, andBloomfield et al29 reported that in patients with systolicimpairment, an abnormal T-wave alternans test predicted a15% 2-year event rate, with a negative predictive value of97.5% at 2 years.

The most prominent point of insufficiency regarding theproposed repolarization descriptors as risk stratifiers is theirlimited specificity and positive predictive value, as opposedto their high negative predictive power. This fact may limittheir clinical utility, but also poses the question of whethersuch different methods of assessment of repolarization mightpossess complementary positive predictive value. This mayalso be suggested by the different pathophysiologic founda-tions of each of these indices. For example, QRSTA or TCRTare a measure of the global repolarization heterogeneity ofthe left ventricle, whereas T-wave residua represent regional

inconsistencies in the wavefront of ventricular repolariza-tion. Answers may be provided only by a comprehensivestudy which would investigate the relative merits and thecombined predictive value of these indices in the same post-MI population.

Study implications

The present study provides evidence regarding thepotential prognostic value of the circadian variation of awell-known electrocardiologic parameter (QRSTA). Thereported observation has certain appealing aspects: (i) therelevant computations were fully automated; (ii) there is noneed for additional equipment, since a 12-lead digital Holterrecording is sufficient to evaluate this parameter; (iii) theinverse circadian pattern did not show any significantcorrelation to either the heart rate in the 24-hour Holterrecording or the use of β-blockers (whereas QRSTA itselfhas been shown to increase with heart rate,30 which might beespecially important in the β-blocking era of post-MImanagement); and (iv) the present findings imply that theQRSTA circadian pattern could offer prognostic informationas early as a few days after the index MI (before patientdischarge from hospital), whereas other electrocardiologicnoninvasive risk markers have been shown to possessreliable predictive value only when evaluated several weeksafter the MI.

Study limitations

The main limitation of the present study is the relativelysmall number of events, which most likely reflects theefficacy of the modern management of post-MI patients, aswell as the fact that patients in grave clinical condition(whose prognosis is poor anyway) were excluded (seeMethods section) from the studied population. This maylimit generalization of the present observations; however,their prospective nature, as well as the fact that the observedcorrelations were shown to be independent of such factors asage, sex, ejection fraction, QRS and QTc duration, heart rate,heart rate variability, and others, render them quite reliable.In any case, these findings should only be considered asproof-of-concept data and will have to be reiterated in largerpost-MI cohorts.

Conclusion

QRS-T angle is an index of global ventricular repolariza-tion heterogeneity, the diurnal variation of which can beassessed from automatically analyzed 24-hour Holterrecordings. Relevant algorithms may be added to thesoftware of existing recording instruments, and its evaluationentails no significant additional burden on the patient or thephysician and minimal added cost. Our results, in aprospectively studied post-MI cohort, show that thisparameter may offer significant prognostic information; wethus conclude that QRSTA circadian pattern, within thelimitations of the present study, could be a parameter worthtaking into account, along with other clinical and laboratoryvariables, as an aid to management decision-making for post-MI patients.

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