Highlights
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Atherosclerosis was present in two-thirds of patients with paroxysmal AF, mostly subclinical.
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Patients with atherosclerosis had an increased risk of AF progression.
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Atherosclerosis remained a determinant of AF progression after adjustment for risk factors.
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Findings suggest vascular disease may contribute directly to atrial remodeling and arrhythmia persistence.
ABSTRACT
Background
Atrial fibrillation (AF) may progress from paroxysmal AF (PAF) to more persistent forms, but the underlaying mechanisms are not well understood. The aim of this study was to assess the association between atherosclerosis and AF progression in patients with PAF.
Methods
In this substudy of RACE V, 612 patients with PAF underwent extensive phenotyping at baseline and continuous rhythm monitoring. The association between atherosclerosis and AF progression was investigated.
Results
The median age was 64 (57–70) years, 257 (42%) were women, and the median CHA 2 DS 2 -VA score was 2 (1-3). At baseline, 395 (65%) patients had atherosclerosis, defined by carotid/coronary imaging and/or history of vascular disease. Patients with atherosclerosis were older, had higher waist circumference, more hypertension, and lower eGFR than patients with no atherosclerosis. During a median of 3.4 (2.8-3.7) years follow-up, 108 (18%) patients had AF progression. The presence of atherosclerosis was associated with increased progression (21% vs. 12%; p =.004). In univariable analyses, atherosclerosis was a determinant of AF progression (OR: 2.04; 95% CI: 1.28-3.37; p =.004), and the association persisted following adjustment for established risk factors (OR: 2.23; 95% CI: 1.10-4.89; p =.034).
Conclusions
In patients with paroxysmal AF, 65% of patients had atherosclerosis. Atherosclerosis was a determinant of AF progression after adjustment for established risk factors and comorbidities, suggesting that vascular disease may contribute directly to atrial remodelling and arrhythmia persistence.
Background
Atrial fibrillation (AF) progression is associated with increased risk of major cardiovascular and cerebrovascular adverse events. , However, predicting which patients progress is difficult, and the mechanisms that drive AF progression are poorly understood.
Several clinical factors have been identified as predictors of AF progression, including older age, male sex, concomitant heart failure (HF), hypertension and obesity. ,, Some of the same factors are also known promoters of atherosclerotic disease. While atherosclerosis is already a well-established risk factor for incident AF, its role in AF progression is less clear and largely unexplored. ,,, However, circulating biomarkers related to inflammation, atherosclerosis, and coagulation have shown associations to atrial remodelling and AF progression.
The Reappraisal of Atrial Fibrillation: Interaction between HyperCoagulability, Electrical Remodeling, and Vascular Destabilisation in the Progression of AF (RACE V) is a prospective observational study designed to explore the mechanisms contributing to AF progression in patients with paroxysmal AF (PAF), using comprehensive baseline phenotyping and continuous rhythm monitoring. In the current analysis, we investigate the association between atherosclerosis presence and AF progression in this cohort of patients with PAF.
Methods
Study design and population
The design of the RACE V study has been described previously. Briefly, RACE V was a Dutch, multicenter, investigator-initiated, prospective observational cohort designed to explore phenotypical differences between patients with and without AF progression. Eligible participants had either >2 documented episodes of self-terminating AF, or 1 documented AF episode plus ≥2 symptomatic episodes suspected to be AF. Exclusion criteria included prior or planned pulmonary vein isolation (PVI), ongoing amiodarone use, and unwillingness to undergo implantable loop recorder (ILR) implantation. All participants received continuous rhythm monitoring via ILRs or pacemakers with an atrial lead and comparable AF detection algorithms, enabling accurate tracking of AF recurrences. Alongside monitoring, patients underwent extensive baseline phenotyping. The study’s primary endpoint was AF progression, defined as (1) development of persistent or permanent AF, or (2) an increase in AF burden >3% during follow-up. Changes in AF burden during follow-up were calculated retrospectively using a previously described weighted algorithm and visually confirmed using time-resolved AF episode plots by three independent experts. Written informed consent was obtained from all participants. The study complied with the Declaration of Helsinki, and the protocol was approved by the Medical Ethics Review Committees of the University Medical Center Groningen and all participating centers.
Vascular assessment
Vascular assessment included the measurement of intima-media thickness (IMT), the presence of carotid plaque, carotid-femoral pulse wave velocity (cfPWV), and coronary calcium (Agatston) scoring. IMT and carotid plaque were evaluated by ultrasound, cfPWV using standard tonometry devices, and coronary calcium scores by non-contrast, ECG-gated cardiac CT.
Atherosclerosis definition
Patients were categorized into 2 groups: atherosclerosis and no atherosclerosis presence at baseline, to explore the association between atherosclerosis and AF progression. Atherosclerosis was defined as the presence of any of the following (1) subclinical measures [mean carotid IMT >0.9 mm, carotid plaque or maximum IMT ≥1.5 mm in any carotid segment, coronary calcium (Agatston) score ≥100, or cfPWV >10 m/s], and/or (2) clinical history of vascular disease [prior coronary artery disease (CAD), transient ischemic attack (TIA), ischemic stroke, peripheral vascular disease (PVD), or systemic embolic event] at baseline. , Further details on subclinical and clinical subgroups are provided in the Supplementary Material.
Statistical analysis
Baseline characteristics are presented as median (interquartile range) for continuous data, and counts (%) for categorical data. Differences between groups were analyzed using independent-samples t-test, Mann-Whitney U test or Chi-square test, as appropriate. Logistic regression analyses were conducted to examine the association between atherosclerosis and AF progression. Two models were constructed: (1) univariable, and (2) sex, age, waist circumference, systolic blood pressure, HF and diabetes presence adjusted. The Hosmer-Lemeshow test was used to evaluate the goodness of fit for the logistic regression models. A two-sided p-value ≤0.05 was considered statistically significant. All analyses were performed using R statistical software (v4.4.1; R Core Team, 2021).
Results
Patient characteristics
Baseline characteristics for the study population are summarized in Table 1 . A total of 612 patients were included in the analysis. The median age was 64 (57–70) years, 257 (42%) were women, and the median CHA 2 DS 2 -VA score was 2 (1-3).
Table 1
Baseline characteristics grouped according to atherosclerosis presence
| Characteristic |
Total population
(n = 612) |
Atherosclerosis
(n = 395) |
No Atherosclerosis
(n = 217) |
p value |
|---|---|---|---|---|
| Age (years) | 64 [57, 70] | 67 [61, 73] | 59 [53, 65] | <.001 |
| Female sex | 257 (42%) | 154 (39%) | 103 (47%) | .051 |
| History of AF (years) | 1.5 [0.4, 3.9] | 1.6 [0.4, 4.1] | 1.38 [0.4, 3.6] | .489 |
| CHA 2 DS 2 -VA score | 2 [1, 3] | 2 [2, 3] | 1 [1, 2] | <.001 |
| Comorbidities | ||||
| Hypertension | 521 (85%) | 355 (90%) | 166 (76%) | <.001 |
| Diabetes mellitus | 50 (8%) | 39 (10%) | 11 (5%) | .054 |
| Chronic renal failure | 37 (6%) | 31 (8%) | 6 (3%) | .019 |
| Heart failure | 180 (29%) | 139 (35%) | 41 (19%) | .003 |
| HFrEF | 14 (2%) | 11 (3%) | 3 (1%) | .469 |
| HFpEF | 163 (27%) | 125 (32%) | 38 (18%) | .011 |
| Hypercholesterolemia | 260 (42%) | 202 (51%) | 58 (27%) | <.001 |
| Examinations | ||||
| BMI (kg/m 2) | 27 [24, 30] | 27 [24, 30] | 27 [24, 30] | .994 |
| Waist circumference (cm) | 100 [93, 108] | 101 [94, 110] | 98 [89, 108] | .003 |
| SBP (mmHg) | 134 [125, 145] | 136 [127, 149] | 130 [123, 140] | <.001 |
| NT-proBNP (pg/mL) | 45 [17, 129] | 45 [17, 112] | 46 [17, 152] | .467 |
| HDL (mmol/L) | 1.4 [1.1, 1.7] | 1.4 [1.1, 1.7] | 1.4 [1.2, 1.8] | .421 |
| LDL (mmol/L) | 2.9 [2.2, 3.6] | 2.7 [2.0, 3.6] | 3.2 [2.6, 3.6] | <.001 |
| eGFR (mL/min/1.73m²) | 82 [70, 90] | 80 [68, 90] | 85 [76, 90] | <.001 |
| PQ interval (ms) | 166 [150, 186] | 170 [152, 192] | 163 [150, 180] | .002 |
| Echocardiographic variables | ||||
| LA volume index (m/m 2) | 32 [26, 40] | 32 [26, 40] | 32 [27, 39] | .430 |
| LA reservoir function (%) | 36 [29, 43] | 35 [29,42] | 37 [30, 45] | .122 |
| LA contractile function (%) | 16 [13, 21] | 16 [12, 21] | 16 [13, 21] | .362 |
| LA conduction function (ms) | 19 [14, 24] | 19 [14, 23] | 20 [15, 25] | .175 |
| LVEF (%) | 58 [55, 61] | 58 [55, 60] | 58 [55, 63] | .561 |
| Medications | ||||
| ACEi/ARB | 225 (37%) | 171 (43%) | 54 (25%) | <.001 |
| Beta blocker | 318 (52%) | 229 (58%) | 89 (41%) | <.001 |
| Verapamil/Diltiazem | 105 (17%) | 56 (14%) | 49 (23%) | .011 |
| Class I AA | 145 (24%) | 83 (21%) | 62 (29%) | .043 |
| Class III AA | 26 (4%) | 18 (5%) | 8 (4%) | .767 |
| MRA | 4 (1%) | 4 (1%) | 0 (0%) | .336 |
| Statin | 195 (32%) | 169 (43%) | 26 (12%) | <.001 |
| Diuretic | 90 (15%) | 65 (16%) | 25 (12%) | .126 |
| Anticoagulation | 416 (68%) | 307 (78%) | 109 (50%) | <.001 |
| VKA | 60 (10%) | 48 (12%) | 12 (6%) | .307 |
| NOAC | 356 (58%) | 259 (66%) | 97 (45%) | .307 |
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