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. 2019 Jun 11;24(6):e12669. doi: 10.1111/anec.12669

New electrocardiographic score for the prediction of atrial fibrillation: The MVP ECG risk score (morphology‐voltage‐P‐wave duration)

Bryce Alexander 1, Julia Milden 1, Bachar Hazim 1, Sohaib Haseeb 1, Antoni Bayes‐Genis 2, Roberto Elosua 3,4,5, Manuel Martínez‐Sellés 6, Cynthia Yeung 1, Wilma Hopman 1, Antoni Bayes de Luna 7, Adrian Baranchuk 1,✉
PMCID: PMC6931412  PMID: 31184409

Abstract

Background

Atrial fibrillation (AF) is the most common arrhythmia and has significant morbidity. A score composed of easily measured electrocardiographic variables to identify patients at risk of AF would be of great value in order to stratify patients for increased monitoring and surveillance. The purpose of this study was to develop an electrocardiographic risk score for new‐onset AF.

Methods

A total of 676 patients without previous AF undergoing coronary angiography were retrospectively studied. Points were allocated based on P‐wave morphology in inferior leads, voltage in lead 1, and P‐wave duration (MVP). Patients were divided into three risk groups and followed until development of AF or last available clinical appointment.

Results

Mean age was 65 years, and 68% were male. The high‐ and intermediate‐risk groups were more likely to develop AF than the low‐risk group (odds ratio [OR] 2.4, 95% confidence interval [CI] 1.3–4.4; p = 0.006 and OR 2.1, 95% CI 1.4–3.27; p = 0.009, respectively). The high‐risk group had a significantly shorter mean time to development of AF (258 weeks; 95% CI 205–310 weeks) compared to the intermediate‐ (278 weeks; 95% CI 252–303 weeks) and low‐risk groups (322 weeks 95% CI 307–338 weeks), p = 0.005.

Conclusions

A simple risk score composed of easy‐to‐measure electrocardiographic variables can help to predict new‐onset AF. Further validation studies will be needed to assess the ability of this risk score to predict AF in other populations.

Keywords: atrial fibrillation, ECG, interatrial, risk score

1. INTRODUCTION

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice and has a cumulative global burden of more than 33.5 million people (Chugh et al., 2013). Atrial fibrillation carries a significant increase in the risk of major embolic events such as stroke as well as an increased risk of heart failure and death (Alonso et al., 2013; Chamberlain et al., 2011; January et al., 2014; Kokubo et al., 2017; Schnabel et al., 2009). A risk score to identify patients at risk for AF using simple, noninvasive, and easily obtainable electrocardiographic markers would be of great value to clinicians in order to determine the subset of patients who may warrant closer and extended monitoring. The purpose of this study was to test the hypothesis that a risk score composed of three easily obtainable electrocardiographic measurements had the ability to predict AF in a higher‐risk population of patients with known or suspected coronary artery disease.

2. METHODS

2.1. Patient selection

A total of 676 outpatients referred for coronary angiography to a single center (Kingston Health Science Center‐KHSC) were included. The study was granted approval by theinstitutional Health Sciences Research Ethics Board. Inclusion criteria were defined as: (a) age ≥18 years; (b) nonemergent outpatients referred for an angiogram due to nonspecific chest pain evaluation, stable or unstable angina pectoris, positive stress test, preoperative assessment, old or recent myocardial infarction (>2 days); (c) a follow‐up ECG conducted at KHSC within 12 months of the index ECG/angiogram. Exclusion criteria included any contraindication to angiography, AF on initial ECG, lack of measurable P waves in lead I or in the inferior leads, and any device pacing the atrium. All patients had a baseline ECG completed within 1 month prior to their angiogram which was used as the index ECG.

2.2. Risk score variable selection rationale

An ECG risk score was used to determine the risk of AF. The score was comprised of three P‐wave variables: morphology in inferior leads, voltage in lead 1, and P‐wave duration (MVP). The variables and point allocation of the MVP ECG risk score were based on a critical appraisal of the existing literature and the prevalence and predictive value of ECG indices for AF (Alexander, MacHaalany, et al., 2017; Alexander et al., 2016; O’Neal, Zhang, et al., 2016; Tse et al., 2017). Table 1 illustrates the MVP ECG risk score variables and the assigned weighting. The rationale for the inclusion of each risk score variable is discussed below:

Table 1.

Morphology‐Voltage‐P‐wave duration (MVP) ECG risk score for atrial fibrillation

Variable Value Score
Morphology in inferior leads Nonbiphasic (<120 ms) 0
Nonbiphasic (≥120 ms) 1
Biphasic 2
Voltage in lead I >0.20 mV 0
0.10–0.20 mV 1
<0.10 mV 2
P‐wave duration <120 ms 0
120–140 ms 1
>140 ms 2
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0–2: Low probability of AF.

3–4: Intermediate probability of AF.

5–6: High probability of AF.

2.3. Morphology

The ability of P‐wave morphology to predict AF has been extensively studied in the context of interatrial block (IAB). Partial IAB is defined as a normal or notched P‐wave morphology in the inferior leads with a prolonged P‐wave duration while advanced IAB is defined as a biphasic P wave in the inferior leads with a prolonged P‐wave duration (≥120 ms). Interatrial block is thought to represent fibrosis of the interatrial conduction pathways, more precisely the Bachmann region. In advanced IAB, there is a complete block of the normal interatrial conduction pathways and the left atrium is activated in a caudocranial direction producing a biphasic P wave in the inferior leads. Partial IAB represents an incomplete block of the normal conduction pathways such that the electrical impulse is delayed but travels through the normal conduction pathways. Both partial and advanced IAB are predictors of AF, with advanced IAB having a stronger predictive value (Baranchuk & Bayés de Luna, 2015; Sadiq Ali et al., 2015; Tse et al., 2017). Therefore, the MVP ECG Risk Score allocates one point for partial IAB and two points for advanced IAB.

2.4. Voltage

P‐wave voltage depends on the direction of electrical propagation relative to the axis of the lead being measured, myocardial mass, intervening substrates, and conductive properties of the myocardium. Reduced P‐wave voltage is thought to mirror altered atrial conduction patterns seen in IAB. Left atrial voltage activation maps have shown that in patients with reduced P‐wave voltage, the electrical impulse in the Bachmann region is displaced (2016). The MVP ECG Risk Score accounts for reduced P‐wave voltage with one point for P‐wave voltage in lead 1 (PVL1) = 0.20–0.10 mV and two points for PVL1 < 0.10 mV.

2.5. P‐wave duration

P‐wave duration of >120 ms has been shown to be an independent predictor of AF in many populations (Perez et al., 2009; Tse et al., 2017). Previous studies have shown an increased risk of AF with longer P‐wave durations (Nielsen et al., 2015). The MVP ECG Risk Score assigns one point to P‐wave duration (PWD) = 120–140 ms and two points to PWD > 140 ms.

2.6. ECG analysis

A standard 12‐lead ECG (filter 150 Hz, 25 mm/s, 10 mm/mV) was obtained in all patients, and images were amplified x8 and analyzed using ICONICO semi‐automatic calipers. Each ECG was blindly reviewed by two independent reviewers. P‐wave duration was measured according to the most recent consensus guidelines on IAB (Bayés de Luna et al., 2012). The P‐wave onset was defined as the point of initial upward or downward deflection from the isoelectric line, and the offset was defined as the return of the waveform to the initial baseline. This method has been previously described and validated with high interobserver and intraobserver correlation coefficients (Kizilirmak et al., 2016). P‐wave voltage was measured from the peak of the P wave to the isoelectric line of the T‐P interval in lead 1. Figure 1 illustrates the method of measurement of the MVP ECG risk score P‐wave variables.

Figure 1.

Figure 1

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Technique of measurement of P‐wave indices. P‐wave duration is measured from the first upward deflection of the P wave to return of the waveform to the isoelectric line in leads II, III, and aVF. P‐wave voltage is measured from the peak of the P wave to the isoelectric line of the T‐P interval in lead I

2.7. Clinical variables/follow‐up/atrial fibrillation

Patient charts were reviewed for baseline demographic and clinical data. All available clinical records, ECGs, and Holter monitors were reviewed for the presence of AF. Patients were followed until their last available clinic record. Atrial fibrillation was diagnosed if found to be present on an ECG documented at a clinic visit, an external physician record, hospital records, or Holter reports. No specific cut‐off was used to define AF.

2.8. Statistical methods

Data were collected in Excel and imported into IBM SPSS (version 24.0 for Windows) for statistical analysis. Patient characteristics were compared for patients with AF versus those without AF. Data were initially described using means and standard deviations for continuous data, and frequencies and percentages for categorical data. This was followed by a univariate analysis to assess the association of the collected data with the outcome using one‐way ANOVA and independent sample t tests for the normally distributed continuous data, Mann–Whitney for continuous data that was not normally distributed and chi‐square tests (Pearson or Fisher's exact as appropriate) for categorical data. Kaplan–Meier analysis was conducted to determine the difference in mean AF‐free survival between patients within different risk score categories, with survival curves generated to illustrate survival time between groups. Logistic regression analysis was performed to assess the ability of the risk score to predict new‐onset AF both by risk score categories.

3. RESULTS

3.1. Population demographics

The study population consisted of 676 patients with a mean age of 64.9 ± 11.1 years. The population was predominantly male (68.2%) with a mean BMI of 29.8 ± 6.4 kg/m (January et al., 2014). The incidence of new‐onset AF in this population was 20.8% during a mean follow‐up of 161 weeks. Baseline variables associated with development of AF included age, hypertension, congestive heart failure, and known coronary artery disease. Patients who developed AF also had a higher baseline CHADS2 and CHA2DS₂‐VASc scores and a greater left atrial diameter and volume (Table 2 ).

Table 2.

Population characteristics by incident atrial fibrillation (univariate analysis)

Variable Population (n = 676) Incident atrial fibrillation
Absent (n = 536) Present (n = 140) p value
Demographic variables
Age (years) 64.9 ± 11.1 64.8 ± 11.3 68.9 ± 9.3 <0.001
Male sex 462 (68.2%) 359 (67.0%) 103 (73.6%) 0.153
BMI (kg/m2) 29.8 ± 6.4 29.8 ± 6.5 29.9 ± 5.8 0.947
Diabetes mellitus 207 (30.6%) 158 (29.5%) 49 (34.8%) 0.259
Tobacco use 273 (40.3%) 224 (41.9%) 49 (34.8%) 0.124
Hypertension 482 (71.2%) 370 (69.3%) 112 (79.4%) 0.021
Hyperlipidemia 462 (68.2%) 364 (68.3%) 98 (69.5%) 0.893
Prior TIA or stroke 45 (6.6%) 30 (5.6%) 15 (10.6%) 0.055
Prior diagnosis of CHF 38 (5.6%) 22 (4.1%) 16 (11.3%) 0.003
Known coronary artery disease 291 (45.0%) 215 (40.1%) 76 (53.9%) 0.004
CHADS2 score 1.4 ± 1.1 1.3 ± 1.1 1.7 ± 1.2 <0.001
CHA2DS₂‐VASc score 3.1 ± 1.4 3.0 ± 1.4 3.5 ± 1.4 <0.001
Electrocardiographic variables
P‐wave duration
<120 ms 428 (63.2%) 360 (67.3%) 68 (48.2%) <0.001
120–140 ms 180 (26.6%) 127 (23.7%) 53 (37.6%)
>140 ms 68 (10%) 49 (9.0%) 20 (29.4%)
P‐wave voltage
>0.20 mV 10 (1.5%) 9 (1.7%) 1 (0.7%) 0.062
0.10–0.20 mV 351 (51.8%) 286 (53.5%) 65 (46.1%)
<0.10 mV 415 (46.5%) 240 (44.9%) 75 (53.2%)
P‐wave morphology
No interatrial block 428 (63.2%) 360 (67.3%) 68 (48.2%) <0.001
Partial interatrial block 224 (33.1%) 158 (29.5%) 66 (46.8%)
Advanced interatrial block 24 (3.5%) 17 (3.2%) 7 (5.0%)
Significant coronary artery stenoses
Left main 67 (9.9%) 47 (9.0%) 20 (14.3%) 0.081
Left anterior descending 376 (55.5%) 281 (53.6%) 95 (67.9%) 0.003
Left circumflex 281 (41.5%) 201 (39.5%) 74 (52.9%) 0.005
Right coronary 316 (46.7%) 240 (43.9%) 86 (61.4%) <0.001
Posterior descending 46 (6.8%) 27 (5.2%) 19 (13.6%) 0.001
More than one artery 365 (53.9%) 271 (50.6%) 94 (66.7%) 0.001
Echocardiographic variables
LVEF (%) 57.1 ± 12.2 57.6 ± 11.7 55.7 ± 13.6 0.211
Left atrial diameter (mm) 38.6 ± 6.0 38.1 ± 5.8 40.4 ± 6.3 0.011
Left atrial volume index (mL/m2) 31.4 ± 11.3 30.0 ± 9.8 35.7 ± 14.5 0.004
Right atrial volume index (mL/m2) 22.3 ± 9.6 21.6 ± 8.9 24.0 ± 11.2 0.141
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Bold indicates standard at <0.05.

3.2. MVP ECG risk score for atrial fibrillation

The high‐risk and intermediate‐risk groups had an increased risk of AF compared to the low‐risk group (Table 3). The high‐risk group had a significantly shorter mean time to AF (258 weeks; 95% CI 205–310 weeks) compared to the intermediate‐risk group (278 weeks; 95% CI 252–303 weeks) and low‐risk group (322 weeks 95% CI 307–338 weeks); p = 0.005 (Figure 2). Median survival time could not be calculated as the survival curve did not cross 50%.

Table 3.

Multivariate logistic regression analysis for atrial fibrillation by risk score category

Risk score category Atrial fibrillation (n = 141) All (n = 676) Odds ratio 95% confidence interval p‐value
Low (0–2) 68 (15.9%) 428      
Intermediate (3–4) 55 (28.9%) 190 2.1 1.4 – 3.2 <0.001
High (5–6) 18 (31.0%) 58 2.4 1.3 – 4.4 0.006
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Bold indicates standard at <0.05.

Figure 2.

Figure 2

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Kaplan–Meier survival curve for time to incident atrial fibrillation by risk score category

4. DISCUSSION

This study demonstrates that a simple risk score, composed only of easy‐to‐measure electrocardiographic variables, can predict the risk of AF. In practice, such an electrocardiographic risk score may prove extremely valuable in stratifying patients for closer monitoring. In recent years, wearable cardiac monitoring devices have emerged on the market. There is currently no clear consensus for which patients to recommend these devices (Halcox et al., 2017). On one hand, these monitors provide a clear benefit of earlier identification and increased awareness of AF; on the other hand, recommending these devices to all patients may create unnecessary anxiety and increased health costs. The MVP ECG risk score may help clinicians to decide which patients warrant further monitoring through these devices to detect incident AF. The MVP ECG risk score also has the advantage of being calculated entirely from the surface electrocardiogram, the most common, widespread and least costly cardiac rhythm diagnostic tool. With the increasing sophistication of computer models, it will likely be possible to automatically calculate the MVP ECG risk score directly through ECG software in the near future.

The components of the MVP ECG risk score have a wealth of evidence regarding their predictive value for new‐onset AF (Alexander, MacHaalany, et al., 2017; Alexander et al., 2016; O’Neal, Zhang, et al., 2016; Tse et al., 2017). The P wave represents atrial depolarization and as such is an electrocardiographic marker of atrial conduction. A recent meta‐analysis of 18,204 patients across 16 studies by Tse et al. (2017) demonstrated that patients with IAB had a 2.4‐fold increase in the risk of incident AF. Interatrial block is thought to represent fibrosis of the interatrial conduction system and thus is an indirect marker of atrial cardiomyopathy. More specifically, IAB represents fibrosis of the Bachmann region, impeding normal interatrial conduction, forcing the stimulus to travel from the right to the left atrium using lower connections at the coronary sinus and fossa ovalis (Tse, Tsz, Lai, Yeo, & Yan, 2016). P‐wave voltage in lead I is a relatively new concept; however, it is thought to represent a similar phenomenon of atrial fibrosis as IAB. Lower voltage of P wave in lead I correlates well with advanced fibrosis in the atrium (Alexander, Haseeb, et al., 2017). Based on the component variables, of the score, the summation of the three variables is able to identify those patients who already have a process of atrial remodeling and atrial cardiomyopathy underway and as such have the anatomical–electrical substrate present to develop AF.

An interesting aspect of this score is that it may increase monitoring of asymptomatic patients and detect instances of subclinical AF. Subclinical AF refers to asymptomatic AF in patients without a known history of arrhythmia that is detected only incidentally by monitoring techniques. (Gold, 2018) There is currently no consensus regarding if patients with subclinical AF should be treated the same as those with symptomatic AF (Andrade et al., 2018; Gold, 2018) Several large clinical trials have demonstrated that subclinical AF carries an increased risk of stroke (Glotzer et al., 2009; Healey et al., 2012). However, there appears to be no temporal relationship between AF and stroke and the risk of stroke appears to be lower than for symptomatic cases (Martin et al., 2015).

Prior risk scores have attempted to predict AF using clinical variables or the P‐R interval in addition to clinical variables (Alonso et al., 2013; Chamberlain et al., 2011; Kokubo et al., 2017; Schnabel et al., 2009). However, these scores were constructed prior to publication of much of the evidence regarding P‐wave markers. There are several other valid P‐wave indices that have not been included in the score for different reasons, including P‐terminal force in lead V1 (PtfV1), P‐wave dispersion, and P‐wave axis. P‐terminal force in lead V1 is a biphasic P wave with a distal component >40 ms in lead V1. P‐terminal force in lead V1 is strongly correlated with left atrial enlargement (Batra, Khan, Farooq, Masood, & Karim, 2018). Since PtfV1 is not ideally suited for distinguishing altered conduction in the setting of a normal or mildly dilated left atria, it has been excluded from the MVP ECG Risk Score in favor of other parameters that are independent of left atrial enlargement. P‐wave dispersion has likewise been previously associated with AF. However, P‐wave dispersion is highly affected by electrode placement and has a high interobserver variability, so it was also excluded from the score (Pérez‐Riera et al., 2016). A recent article has been published on improving the discrimination of the CHA₂DS₂‐VASc score to predict stroke through addition of altered P‐wave axis to the traditional CHA₂DS₂‐VASc (Maheshwari et al., 2019). There is currently not a large body of literature of the ability of the P‐wave axis to predict AF independent of stroke, and it was therefore not included in this score. Advanced IAB has been shown to be predictive of stroke in several populations (Lindow & Baranchuk, 2018; O’Neal, Kamel, et al., 2016). However, as only twelve patients experienced a stroke during the follow‐up period in our study, we did not evaluate the ability of MVP ECG score to predict stroke. Further studies will be needed to assess the ability of this score to predict AF and stroke in different populations.

4.1. Limitations

This study was performed at a single center. The retrospective nature of the study implies a potential for inherent bias. While patients with prior documented episodes of AF were excluded from the study, it is possible that patients with prior undocumented episodes were included. In addition, as AF was captured only from follow‐up appointments (ECG and Holter) it is possible that silent AF episodes may have gone unreported. The length of follow‐up was variable for this sample, with many patients being followed for only a few years prior to being censored.

5. CONCLUSIONS

The MVP ECG risk score can predict new‐onset AF using simple, noninvasive, and easily obtainable electrocardiographic markers. Further studies are needed to validate these findings in other populations.

CONFLICT OF INTEREST

None.

Alexander B, Milden J, Hazim B, et al. New electrocardiographic score for the prediction of atrial fibrillation: The MVP ECG risk score (morphology‐voltage‐P‐wave duration). Ann Noninvasive Electrocardiol. 2019;24:e12669 10.1111/anec.12669

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