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European Heart Journal Advance Access originally published online on September 4, 2006
European Heart Journal 2006 27(21):2499-2510; doi:10.1093/eurheartj/ehl218
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© The European Society of Cardiology 2006. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Risk factors for primary ventricular fibrillation during acute myocardial infarction: a systematic review and meta-analysis

Peter J. Gheeraert1,*, Marc L. De Buyzere1, Yves M. Taeymans1, Thierry C. Gillebert1, Jose P.S. Henriques2, Guy De Backer3 and Dirk De Bacquer3

1 Department of Cardiology, University Hospital, De Pintelaan 185, 9000 Ghent, Belgium
2 Department of Cardiology, Academic Medical Centre, Amsterdam, The Netherlands
3 Department of Public Health, Ghent University, Ghent, Belgium

Received 15 May 2006; revised 11 July 2006; accepted 17 August 2006; online publish-ahead-of-print 4 September 2006.

* Corresponding author. Tel: +32 9 240 44 05; fax: +32 9 240 49 99. E-mail address: peter.gheeraert{at}uzgent.be


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 References
 
Aims To evaluate potential risk factors for primary ventricular fibrillation (PVF) during acute myocardial infarction (AMI) by a systematic review and meta-analyses.

Methods and results We searched PubMed for English articles on ‘humans’ published between 1964 and January 2006 using a validated combination of MESH terms. Twenty-one cohort studies describing 57 158 patients with AMI were analysed. Patients with validated PVF (n=2316) were characterized by an earlier admission (weighted mean difference –2.62 h), male gender [odds ratio (OR 1.27)], smoking (OR 1.26), absence of history of angina (OR for history of angina 0.84), lower heart rate at admission (weighted mean difference –4.02 b.p.m.), ST-segment elevation on admission ECG (OR 3.35), AV conduction block before PVF (OR 2.02), and lower serum potassium at admission (weighted mean difference –0.27 meq/L). Patients with validated PVF developed a larger enzymatic infarct size (standardized mean difference 0.74, P<0.00001). PVF was not associated with a history of myocardial infarction or hypertension.

Conclusion Patients who developed a validated PVF presented with characteristics of both abrupt coronary occlusion and early hospital admission. This review provides no evidence for risk factors for PVF other than ST-elevation and time from onset of symptoms. To find new risk factors, studies should compare validated PVF patients with non-PVF patients who have no signs of heart failure and comparable time delay between onset of symptoms and medical attendance.

Key Words: Acute myocardial infarction • Meta-analysis • Primary ventricular fibrillation • Risk factors


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 References
 
Primary ventricular fibrillation (PVF) during acute myocardial infarction (AMI) is conventionally defined as ventricular fibrillation that is not preceded by signs or symptoms of heart failure or cardiogenic shock. It occurs in more than 10% of patients during the first hours of chest pain related to AMI.1–8 PVF is the most frequent cause of death related to AMI because it often occurs before monitoring. The risk factors for this complication are still unknown. Factors that were inconsistently associated with PVF include younger age,9–12 male gender,11,13 smoking,11,12 absence of history of diabetes,12,14 lower serum potassium concentration,11,15–18 and inferior infarct location.10,11,19,20 Other previously studied factors could have been not significant due to lack of statistical power. Such factors include history of angina, history of myocardial infarction, history of hypertension, heart rate and blood pressure before PVF, AV-block, and QTc-interval. Reliable risk factors for PVF can optimize the pre-monitoring management of AMI, including the recommendations on the management of acute chest pain given to the general public and patients. Identification of low vs. high-risk patients could also have impact on the modes of inter-hospital transports for primary angioplasty. New prospective studies on risk factors for PVF during coronary occlusion are limited by early reperfusion strategies. A systematic review and meta-analysis can provide an overview of the potential risk factors studied in humans, uncover associations that were not found in underpowered studies, quantify the strength of associations, and can also help to understand the differences across studies. We aimed to consolidate all published reports in English literature that reported risk factors for PVF and to fulfil the most recent methodological recommendations for meta-analysis of observational studies.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 References
 
Search strategy
During the last 7 years, we gradually constructed a library of articles related to ventricular fibrillation during ischaemia or AMI by searching manually and contacts with authors in this field. For the aim of the study, we constructed a systematic search strategy in PubMed by gradually including MESH terms and combined sets that were sensitive enough to retrieve at least all references of our personal library. We searched PubMed for English articles on ‘humans’ and published between 1964 and January 2006 using six MESH terms and combined sets: ‘myocardial ischaemia’, ‘ventricular fibrillation’, ‘tachycardia, ventricular’, ‘death, sudden, cardiac’, ‘heart arrest’, and ‘autopsy’. One author (P.G.), who has more than 10 years of clinical experience with PVF patients, read the titles and abstracts of all 5288 references and selected manuscripts that possibly described patients with AMI and ventricular arrhythmias. A total of 325 full papers were studied in detail to select those that specified patients with a validated PVF within 48 h of onset of AMI. PVF was considered validated if it occurred in patients without signs of overt heart failure or shock during an AMI defined by WHO criteria. Studies were included if PVF patients were compared with non-PVF patients in a cohort or case–control study design. We excluded studies with composite outcomes such as ‘ventricular fibrillation’ (n=73) without differentiating between primary and secondary ventricular fibrillation, ‘cardiac arrest’ (n=16), or ‘ventricular tachyarrhythmias’ (n=35) not allowing data abstraction for patients with PVF. We identified 21 original cohort studies (Table 1) and six original case–control studies (Table 2) that compared PVF patients with non-PVF patients. We checked the 167 full articles that were included in the references of these studies. No additional complying study was found. This systematic review and meta-analysis were therefore restricted to these 27 original studies. The only outcome variable was PVF within 48 h of onset of AMI.


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  		Table 1 Overview of cohort studies and their characteristics

 

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  		Table 2 Overview of case–control studies and their characteristics

 
Data abstractions and classification of studies
We abstracted dichotomous and continuous variables that represented patient or infarction characteristics compatible with the definitions summarized in Table 3. Infarction site was the only categorical variable. We abstracted infarction site data in three mutually exclusive categories: anterior (including antero-lateral), inferior (including infero-posterior), and not-localized. The category ‘anterior’ was described in all studies and the category ‘inferior’ in all studies except one,13 which was excluded from this analysis. The category ‘not-localized’ was used when the infarction was not located specifically as anterior or inferior. In most studies, this category was described as ‘non-ST-elevation infarction’, ‘non-Q-wave’, ‘subendocardial’, ‘not-localized’, or ‘uncertain’. Two studies had also few patients in a category described as ‘combined’,12,21 which we also abstracted in the category ‘not localized’. Missing data on infarction location were also abstracted in the category ‘not localized’. The continuous variables were abstracted only if mean values were available in both PVF patients and non-PVF patients.


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  		Table 3 Definitions of study variables

 
The cohort studies (Table 1) were classified according to seven well-defined objective criteria for subgroup or sensitivity analysis to assess heterogeneity. These subgroups were defined as (i) exclusion of patients with heart failure (Killip class>1) in the non-PVF patients, (ii) mean admission delay after onset of symptoms more/less than 4 h, (iii) use of fibrinolytics in more/less than 50% of patients, (iv) mean age of study population more/less than 60 years, (v) analysis of risk indicators for PVF being/not being an aim of the observational study, (vi) single/multicentre study, and (vii) published before/after 1987 (which was median of publication years).

One author (P.G.) classified the studies and abstracted the data. We decided not to duplicate study classification and data abstraction by another independent person, as it was done according to easily defined criteria independent of subjective judgement.

Statistical methods
We extracted data to construct two-by-two contingency tables for every dichotomous variable reported in the retained studies. Abstracted data were entered into the Cochrane Review Manager (version 4.2.7) software. We pooled data using the odds ratio (OR) with two sided 95% confidence intervals (95% CI), expressing the strength of the association in a random effect model. The significance of discrepancies in the estimates of association from the different reports was assessed by means of Cochrane's test for heterogeneity. The two-sided significance for heterogeneity was conventionally set at P-value<0.10. In order to combine continuous measures, weighted mean differences were calculated according to the inverse-variance method in a random effect model. To compare enzymatic infarction size, the standardized mean differences were calculated according to the inverse-variance method in a random effect model. To study possible publication bias, we evaluated funnel plots generated by the Cochrane Review Manager (version 4.2.7) software.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 References
 
Twenty-one cohort studies (Table 1) and six case–control studies (Table 2) described 18 potential risk factors (Table 3) for PVF in patients hospitalized with AMI. Owing to the fundamental differences in study design, meta-analysis was restricted to cohort studies, except for the variables ‘AV block’ and ‘QTc’, as these were only reported in case–control studies (Table 4). One variable (diastolic blood pressure) was not analysed by meta-analysis, as it was reported in only one cohort and one case–control study. All studies used validated criteria for diagnosis of AMI and PVF. More specific inclusion criteria are presented in Tables 1 and 2.


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  		Table 4 Summary of data extractions

 
The observational studies differed in some potentially important characteristics or qualities and were therefore categorized according to seven well-defined criteria (Tables 1 and 2). Each category included a sufficient number of studies for subgroup analysis in case of heterogeneity of results across all studies. Almost half of the cohort studies used no reperfusion therapy, six studies excluded patients with heart failure, and in 10 studies, the aim was to find risk indicators for PVF. The results of the meta-analyses are summarized in Table 5.


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  		Table 5 Summary of meta-analyses

 
Variables significantly associated with PVF with homogeneity across all studies
Patients who developed PVF were characterized by male gender (OR 1.27), absence of history of angina (OR for history of angina 0.84), lower heart rate at admission (weighted mean difference –4.02 b.p.m.), presence of ST-segment elevation on admission ECG (OR 3.35), development or presence of AV conduction block before PVF (OR 2.02), and lower serum potassium at admission (weighted mean difference –0.27 meq/L). Patients with PVF developed a significantly larger enzymatic infarction size (standardized mean difference 0.74, P<0.00001).

Variables significantly associated with PVF with heterogeneity across studies
PVF is associated with earlier hospital admission (weighted mean difference –2.62 h) and smoking (OR 1.26). The heterogeneities were caused by differences in strength of associations and not by differences of direction of associations which can be visually appreciated in Figure 1. One study17 was excluded from this analysis because smoking was completely absent in the PVF group, which was regarded as an exceptional finding that the authors could not explain.


Figure 2181
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  		Figure 1 Meta-analysis of the associations between PVF and time (h) from onset of symptoms to hospital admission (A) and smoking (B). WMD, weighted mean difference in random effect model.

 
Variables not associated with PVF with homogeneity across the studies
History of AMI and history of hypertension were not associated with PVF. Five cohort studies11,13,14,22,23 reported on the relation between history of hypertension and PVF (8243 with and 14 124 without history of hypertension). No individual study described a significant association. Pooled data of these five studies indicated homogeneity (test of heterogeneity: {chi}2=5.62; four degrees of freedom, P=0.23) and had an overall OR of 0.98 (95% CI 0.82–1.17, P=0.81). Seven cohort studies13,14,17,20,22,24,25 reported on the relation between history of AMI and PVF (4061 with and 11 767 without history of AMI). The individual ORs varied between 0.77 and 1.34. No study described a significant association between history of AMI and PVF. Pooled data of these seven studies indicated no heterogeneity ({chi}2=3.88; six degrees of freedom, P=0.69) and had an OR of 1.06 (95% CI 0.88–1.28, P=0.51).

Variables not associated with PVF but with heterogeneity across studies
For this category of variables, there was no overall effect in the pooled analysis, but the effects across the studies were heterogeneous, indicating that associations might depend on other study or population characteristics. Therefore, seven dichotomous study variables were used to explore the heterogeneities across studies (Tables 1 and 2). The variables ‘systolic blood pressure’ and ‘QTc’ were studied in only three studies. None of them allowed meaningful study subgroup analysis. Subgroup analysis for the variables age, diabetes, and infarction site are presented in Figure 2. None of the study characteristics could divide the cohort studies in homogeneous groups (Figure 2), except for the association with DM. Studies with mean admission delay<4 h and studies that used fibrinolytic therapy in the majority of patients showed homogeneously that non-diabetic patients had a higher risk of PVF compared with diabetic patients (Figure 2). The borderline significant (P=0.07) and inverse association between PVF and age became significant in studies that included heart failure in the control group and in studies with older patients (mean age>60 years).


Figure 2182
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  		Figure 2 Exploration of heterogeneities across studies by grouping studies according to seven dichotomous characteristics. The number of studies in the subgroups is indicated; bars represent the OR or WMD with 95% CI; open square is proportional to the number of patients; filled square indicates homogeneous results across studies (test for heterogeneity: P≥0.10).

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
References
 
We performed a systematic review and meta-analysis of published English literature on risk factors for PVF. Twenty-one cohort and six case–control studies covered 57 968 patients with confirmed AMI, including 2580 patients with validated PVF. We found that PVF is significantly associated with earlier hospital admission (weighted mean difference –2.62 h), male gender (OR 1.27), smoking (OR 1.26), absence of history of angina (OR for history of angina 0.84), lower heart rate at admission (weighted mean difference –4.02 b.p.m.), ST-segment elevation on admission ECG (OR 3.35), AV conduction block before PVF (OR 2.02), and lower serum potassium at admission (weighted mean difference –0.27 meq/L). PVF was not associated with anterior myocardial infarction, history of hypertension, or history of myocardial infarction. Patients with PVF developed a significantly larger enzymatic infarction size.

These data suggest that the substrate for developing PVF includes a first AMI, no prior angina, and ST-segment elevations—findings in the aggregate that would support those with an abrupt, or acute, coronary artery occlusion without time for pre-conditioning or collaterals to form. This hypothesis can also explain the larger enzymatic infarction size independent of anterior or inferior location.

Large myocardial infarction registries in the USA and Europe have shown that patients who were admitted within 2 h of onset of symptoms are also characterized by male gender,26–28 smoking,26,27 absence of history of angina,26–28 more frequent ST-segment elevation,26 lower heart rate,27 and more frequent AV-block.26 Patients with early admission for AMI also present with lower potassium concentrations compared with patients admitted later.29 To appreciate this resemblance with PVF more quantitatively, we pooled the data of three infarction registries26 that compared patients admitted within 2 h of onset of symptoms with patients admitted later. We then compared the profiles of patients with PVF with the profiles of patients with hospital admission within 2 h of symptom onset (Figure 3).27,28 Patients who develop PVF during hospitalization for AMI presented with characteristics comparable with those of patients who were admitted early to hospital for AMI and who did not develop PVF. ST-elevation was stronger associated with PVF than with early admission. Therefore, the previously reported clinical and infarction characteristics other than ‘ST-elevation’ are probably no risk factors for PVF but are associates confounded by early admission. Previous studies on patients with validated PVF and AMI inevitably selected PVF patients with early medical attendance because more than half of all PVF events occur within 2 h of onset of symptoms. In future analysis, validated PVF patients have to be compared with non-PVF patients with comparable admission delay to find associates that are independent of admission delay. To our knowledge, no previous cohort study had performed a multivariate analysis that included admission delay into the model, and only one small case–control study30 matched for admission delay.


Figure 2183
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  		Figure 3 Associates of PVF (open rhombi) compared with associates of hospital admission within 2 h (filled squares, pooled data from infarction registries26–28); bars represent OR and 95% CI.

 
It is expected that patients with ST-elevation have a higher risk for PVF compared with patients with no ST-elevation infarction. A recent large study of patients with acute coronary syndromes confirmed that patients with no ST-segment elevation had a lower cumulative incidence of VF (1.3%)31 compared with the cumulative incidence of PVF in patients with confirmed AMI ranging from 2.118 to 9.8%.8

The finding of lower serum potassium before PVF was very consistent. Although this association can also be related to early admission,29 it deserves more discussion. Five cohort studies independently showed that patients with PVF had a lower level of potassium before the event compared with patients without PVF. Pooled analysis demonstrated that the weighted mean difference was small (–0.27 meq/L, 95% CI –0.35 to –0.19). Other clinical and experimental data indicated a causal and concentration-dependent risk between hypokalaemia and ventricular arrhythmias during AMI independently of diuretic usage.15,32–36 We additionally analyse systematically all studies on PVF that reported on diuretic usage at admission. Diuretic usage at admission was specified in two cohort17,24 and one case–control37 studies and there were no associations with PVF, suggesting that the relation between low potassium and PVF cannot, or only partially, be explained by diuretic usage. Other leading reviews on potassium during AMI35,38 also conclude that the associations with ventricular arrhythmias during AMI were independent of diuretic usage. The association between low potassium and ventricular arrhythmias was also confirmed in other clinical settings35 and in individual studies of patients resuscitated from out-of-hospital VF during AMI.39 However, potassium levels were also inversely correlated with catecholamine concentrations during AMI. The catecholamine surge during AMI shifts potassium intracellularly especially through muscular beta2-receptor stimulation of the sodium–potassium–ATPase.40 It cannot be excluded that the relatively small decrease of potassium before PVF would only be a marker of catecholamine surge. The association of lower level of potassium and PVF does not imply that immediate corrections of these small dips would lower the risk of ventricular fibrillation.

The association between PVF and lower heart rate is puzzling especially if one of the mechanisms cited to explain low potassium is a catecholamine surge. These seemingly paradoxical observations deserve some further comments. We believe that abrupt coronary occlusion (without time for pre-conditioning or collaterals to form) is indeed the aggregate of most of the described risk factors including the higher catecholamine surge and the resulting lower potassium concentration. However, abrupt coronary occlusion is also associated with more pronounced local cardiac autonomic reflexes41 independent of peripheral catecholamine levels. The resulting heart rate then largely depends on the site of infarction. Patients with abrupt inferior infarction have a more pronounced vagal reflex compared with those with anterior infarction.42,43 We therefore believe that abrupt coronary occlusion resulting in PVF will be associated with lower heart rate in patients with inferior AMI and with higher heart rates in patients with anterior AMI, both independent of the systemic plasma catecholamine level. The two studies that evaluated heart rate had in their PVF group predominantly patients with inferior infarction resulting in lower mean heart rate. The question then remains why in some studies PVF was associated with inferior MI and in others associated with anterior MI. We could document this heterogeneity of associations with infarction site (Table 5) but could not explain it even after subgroup analysis (Figure 2).

Limitations
This meta-analysis does not allow multivariate analysis because it includes only group-data of observational studies. Individual data could not be obtained because we aimed to cover 40 years of research. In this first approach, we aimed to review all current data available, including older studies up to the early periods of monitoring patients with AMI in the early 1960s. These older observational cohort studies present unique data of relatively long observations of cohorts without reperfusion therapy. By including these older studies (that have only group data available) in meta-analysis, it was possible to evaluate if the observed associations were independent of reperfusion therapy and, in case of heterogeneity, to perform additional analysis according to whether or not reperfusion therapy was applied (Figure 2). The meta-analysis was probably not influenced by publication bias, as more than half of the reports had another aim than finding risk indicators (Table 1) and did not show different trends compared with those with the aim of finding risk factors. This was also confirmed by funnel plots, which did not show trends towards publication bias. One common flaw uncovered in most studies is that history of angina, hypertension, diabetes, and smoking were not well defined. For instance, history of angina can theoretically include pre-infarction angina (within 72 h before the AMI) as well as chronic angina. The effect of pre-infarction angina, which is more equivalent to experimental preconditioning, could therefore have been underestimated by all cohort studies. Accordingly, smoking and DM were not uniformly defined, which could have created heterogeneities between studies.

We did not provide a quality score for the individual studies because our inclusion criteria ensured a minimum standard of quality, and studies were subsequently categorized according to seven well-defined study characteristics. We did not include warning ventricular arrhythmias because of extremely varying definitions in too few studies on PVF.14,37,44–49 Only one cohort study25 and one case–control study50 compared left ventricular ejection fraction (EF) in patients with confirmed PVF with patients without PVF and without signs or symptoms of heart failure. In both studies, the EF was measured more than 1 week after onset of AMI, and results were conflicting, showing, respectively, no significant difference and lower EF in PVF patients. One study25 evaluated the extent of coronary artery disease (CAD) in survivors of PVF and concluded that PVF patients had more extensive CAD when measured with the Gensini coronary arteriographic score and by number of diseased vessels. Treatment before admission was not clearly separated from treatment on admission or treatment before PVF.13,17,24,25,37 The effects of early treatment with thrombolytics, beta-blockers, lidocaine, and other antiarrhythmics should preferentially be studied in specific meta-analyses of randomized control trials, which is beyond the scope of this study.

Clinical implications
This meta-analysis shows that both ST-segment elevation and the first hours of symptoms dramatically elevate the risk of PVF. Clinicians should not rely on the traditional risk factors for atherosclerosis (such as gender and age), infarction-related characteristics (such as anterior vs. inferior site), or on the medical history to estimate the risk of the event. ‘Time is muscle’ is important to reduce the final infarct size, ‘time is life’ would better incorporate the strong and important association between PVF and time.

Implications for future research
This systematic review confirmed that after 40 years of research, a significant portion of the risk of PVF remains unexplained and may be unrelated to traditional risk factors for atherosclerosis and myocardial infarction. PVF must be related to unrecognized temporarily acquired functional and structural changes and to genetic and environmental interactions that more directly influence arrhythmic susceptibility. Additional cohort and case–control studies directed at discovering these risk factors and their interactions would appear to have considerable potential for reducing cardiovascular mortality. This meta-analysis provides a framework to design prospectively or retrospectively well-matched case–control or cohort studies. These future studies should compare validated PVF patients with non-PVF patients who have no signs of heart failure and have comparable time delay between onset of symptoms and medical attendance. These studies could include cardiac autonomic function (e.g. heart rate variability and baroreflex sensitivity), early abnormalities in cardiovascular function (e.g. left ventricular size, EF, early remodelling, diastolic function), electrocardiographic variables (e.g. late potentials, T-wave alternans, QRS duration, dispersion of repolarization), metabolic factors (e.g. circulating non-esterified fatty acids), and genetic factors (e.g. mutations of ion channel-encoding genes, polymorphisms of coagulation factors or beta-adrenergic receptors).

Conflict of interest: none declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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