Abstract
Objectives:
The aim of this study was to evaluate the shape of the dose-response relationship between body mass index (BMI) and atrial fibrillation (AF) recurrence in patients who have undergone radiofrequency ablation.
Methods:
Studies investigating BMI and AF recurrence in patients with AF after ablation were identified through electronic searches in the PubMed, EMBASE, and Cochrane Library databases. The potential non-linear relationship was fitted using robust error meta-regression. Our study was registered with PROSPERO (CRD42019121373).
Results:
Twenty-six cohort studies with 7,878 cases/26,450 individuals were included, and a linear dose-response relationship between BMI and AF recurrence (Pnon–linearity = 0.12) was found. The risk of AF recurrence in patients with a BMI over 28 was significantly increased. Specifically, for each 5 kg/m2 increase in BMI, the risk of AF recurrence increased by 15% (95% CI: 1.08–1.22) with moderate heterogeneity (I2 = 53%). Subgroup analyses showed that the pooled risk ratio was not significantly changed in subgroup analysis adjustment for the following important potential intermediate factors: left atrial diameter and obstructive sleep apnea.
Conclusion:
This study showed that there is a borderline positive linear association between BMI and AF recurrence post ablation. Overweight and obesity are significantly associated with AF recurrence.
Systematic review registration:
https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42019128770.
Introduction
Obesity is a rapidly growing global public health concern (1). For example, in the United States, nearly 65% of the population is overweight, and 31% is obese (2). The direct association between obesity and the incidence of atrial fibrillation (AF) has been well-established in large, long-term general population-based cohorts (3, 4). According to a report, obesity increased the risk of developing AF by 49% in the general population, and the risk increased in parallel with increasing body mass index (BMI) (5). AF is the most common cardiac rhythm dysfunction worldwide and leads to significant morbidity and mortality. Over the past decade, radiofrequency ablation, an alternative treatment for AF, has shown advantages over pharmacological methods of rhythm control and has evolved into an important therapy for AF. However, reports of long-term outcomes of ablation demonstrate reduced success over time. The actuarial recurrence at 2 years post ablation was 20% and increased to 40–45% at 5 years.
Body mass index, an important predictor of the incidence of AF in the general population, has also been linked to increased AF recurrence after ablation (6, 7). However, the results regarding the impact of BMI in patients undergoing ablation therapy have been controversial, with several studies demonstrating no clear association (7–11). Five meta-analyses have been conducted to show an increased risk of AF recurrence in patients with elevated BMI (12–16). These studies have provided valuable information; however, there are certain limitations to be addressed. First, a categorical model they applied has the risk of losing power and precision by dividing the exposure into several groups (17). Second, previous meta-analyses have not taken into account confounding factors between obesity and AF recurrence, and it remains unclear whether obesity independently increases the risk of AF recurrence. Second, previous meta-analyses have not taken into account confounding factors between obesity and AF recurrence, and it remains unclear whether obesity independently increases the risk of AF recurrence. Routine risk factors such as hypertension, diabetes, obstructive sleep apnea (OSA) and left atrial diameter (LAD) have been reported to be more prevalent in obese individuals and those undergoing ablation therapy. Also the 2020 ESC guidelines review OSA as one of the potential confounders between obesity and AF recurrence (18). Third, only one meta-analysis has examined dose-response analysis of BMI and AF recurrence after catheter ablation, but it included a limited number of articles and had high publication bias and heterogeneity. In addition, this study did not demonstrate a statistically significant effect of linear dose-response analysis on AF recurrence, and the effect estimate at the obesity threshold was not significant. Whether there are any threshold effects between BMI and the risk of AF recurrence after ablation is unclear, and clarifying the dose-response association is necessary and would be of major importance for facilitating better outcomes for patients with obesity and AF undergoing ablation. Thus, we conducted a meta-analysis to clarify the dose-response relationship between BMI and the risk of AF recurrence after ablation.
Methods
The protocol of this study was registered with PROSPERO (International prospective register of systematic reviews) (https://www.crd.york.ac.uk/PROSPERO/: registration number-CRD 42019128770).
We performed this meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Supplementary Table 1).
Literature search
Two authors (FL and XL) independently systematically searched the Cochrane Library, PubMed, and Embase databases for eligible studies until October 5, 2021. Three groups of keywords (linked to BMI, AF, radiofrequency ablation, respectively) were combined using the Boolean operator “and.” In addition, we searched the reference lists of three previous published meta-analyses (12, 13, 16) or other relevant publications to identify further studies. All discrepancies were resolved through discussion with each other. No language restrictions were applied in the whole literature search. The detail search strategy was provided in Supplementary Table 2.
Study selection
According to the PICOS (population, intervention, comparison, outcome, and study design), the selection criteria were as follows: (i) population: patients with AF undergoing radiofrequency ablation; (ii) and exposure and comparison: high vs. low BMI level; (iii) outcomes: reported the association between of BMI on AF recurrence. No blank period was pre-defined: (iv) study design: cohort, nested case-control, or clinical trials. For multiple publications/reports created from the same data, the studies with the longest follow-up period or the largest number of AF cases were included. We only included studies with multivariate analysis. Case-control and univariate analysis studies were excluded considering their larger bias. Certain publication types (e.g., reviews, editorials, and animal studies), or studies with insufficient data were excluded from this study. The details reasons of excluded studies were listed in Supplementary Table 3.
Data extraction and quality assessment
Basic information of each study, including the authors, publication year, region, study design, participants (sex, age), follow-up time, adjustments for confounders, categories of BMI and adjusted risk ratios (RRs) with its 95% confidence intervals (CIs) for each BMI category were extracted. If multi-adjusted RRs were reported in one study, we extracted the most completely adjusted one.
The quality of all included observational studies were assessed by using Newcastle-Ottawa quality assessment scale (NOS) (19). The validated NOS items with a total of 9 stars involved three aspects including the selection of studies, the comparability of cohorts, and the assessment of the outcome. A NOS score of ≥7 stars was considered as acceptable quality, otherwise, as low-quality studies (20).
Statistical analyses
Summary RRs and 95% CIs for a 5-unit increment in BMI were using a random effects model. Study-specific slopes (linear trends) and 95% CIs from the natural logs of the reported RRs and CIs across categories of BMI were calculated by using the method of Greenland and Longnecker (21). Non-linear dose-response analysis were performed by using the robust error meta-regression method described by Xu and Sar (22). This method is based on a “one-stage approach” which treating each study as a cluster of the whole sample and considering the within study correlations by clustered robust error. It requires known levels of BMI and RRs with variance estimates for at least two quantitative exposure categories. For studies that did not set the lowest BMI group as a reference, data were transformed using a method described by Hamling et al. (23) which requires the number of cases and participants in each category. If these data could not be obtained from an article, the evidence was not pooled. If the median or mean BMI was not provided and reported in ranges, we estimated the midpoint of each category by averaging the lower and upper boundaries of that category (20). If the highest or lowest category was open-ended, we assumed that the open-ended interval length was the same as the adjacent interval. To assess the heterogeneity of RRs across studies, the I2 (95% CI) statistic was calculated with the following interpretation: low heterogeneity, defined as I2 < 50%; moderate heterogeneity, defined as I2 50–75%; and high heterogeneity, defined as I2 > 75% (24, 25). Publication bias was explored by Egger’s test, Begg’s test, and funnel plot. Sensitivity analysis was performed by excluding a bank period < 3 months and leave one-out methods to confirm the robustness of primary analysis. P-value < 0.05 was considered statistically significant.
Results
Study selection
As shown in Figure 1, we identified 1,723 articles through an initial database search (Cochrane Library = 30, PubMed = 332, and EMBASE = 1,361) (Figure 1). After removing duplicate articles (n = 801), 922 studies remained. We further excluded 863 records by quickly screening the titles and abstracts, and 59 articles were reviewed in the detailed evaluation. Of the 59 records, 33 were excluded after the full-text review for the following reasons: (1) Reviews or meta-analyses (n = 2); (2) without target populations (n = 1); (3) without target exposure (n = 11); without target outcome (n = 3); (4) publications with insufficient data (n = 2); (5) studies based on duplicate population (n = 3); (6) case-control studies (n = 2); (7) univariate analysis (n = 9). Supplementary Table 3 provides the detailed reasons for exclusion following the full-text review. Finally, 26 (6–11, 26–45) studies were included in present study.
FIGURE 1
Flow diagram of study selection for the dose-response meta-analysis of body mass index and atrial fibrillation recurrence in patients undergoing radiofrequency ablation.
Study characteristics and quality
Table 1 shows the baseline characteristics of the patients included in the study. Overall, the publication years ranged from 2008 to 2021, with ten conducted in North America (the USA and Canada), eight in Asia, and eight in Europe. The age range of patients in the included studies was 52–65 years, sample size range was 72–3,333, and follow-up time range was 3–42 months. Among the 26 articles, 14 and 12 was prospective and retrospective cohort studies, respectively. AF recurrence in the included studies was detected by using 12-lead ECG or 24 h Holter monitoring.
TABLE 1
| References, country | Source of participants | AF cases, sample size | Mean age (years), male | Follow-up (month), blank period | Study design, AF detection | AF type | BMI data reported (kg/m2) | Adjustment for confounders | Ablation strategy | |
| Par | Non-Par | |||||||||
| Jongnarangsin et al. (26), USA | University of Michigan | 127/324 | 57, 76% | 12, 8 weeks | PC, ECG | 72% | 28% | <25 25–29 ≥30 Continuous | Age, gender, type and duration of AF, left atrial size, and LVEF | CPVI |
| Chang et al. (8), China | National Yang-Ming University School of Medicine | 84/282 | 52, 76% | 12, 2 months | PC, ECG | 76.6% | 23.4% | Continuous | HTN, diabetes, fasting glucose, triglycerides, high-density lipoprotein cholesterol, Mets score | CPVI |
| Letsas et al. (27), Germany | NA | 28/72 | 55, 81% | 13, 1 month | PC, ECG | 64% | 36% | Continuous | Use of statins, ACEIs/ARBs, spironolactone, WBC count, C-reactive protein | CPVI |
| Tang et al. (28), China | Beijing An Zhen Hospital | 242/654 | 57, 71% | 16, 3 months | RC, ECG | 79.8% | 20.2% | <25 ≥25 Continuous | AF duration, AF type, LAD, left ventricular end-diastolic diameter and ablative strategy | CVPI |
| Chilukuri et al. (10), USA | Johns Hopkins Hospital | 34/109 | 60, 78% | 11, 3 months | PC, ECG | 67% | 33% | <25.0 25.0–29.9 ≥30.0 Continuous | Age, persistent AF, OSA, female, left atrial size, LVEF | SPVI |
| Patel et al. (6), USA | Medical Center, Cleveland | 781/3265 | 56, 84% | 12, 8 weeks | RC, ECG | 53.3% | 46.7% | <30 ≥30 | Age, type of AF, echo parameters, type II DM, HTN, CAD | PVAI |
| Kang et al. (7), Korea | Korea University Anam Hospital | 32/94 | 59, 81% | 9, 3 months | PC, ECG | NA | NA | Continuous | AF duration, DM, and required cardioversion during ablation | CPVI |
| Cai et al. (29), China | Hospital of Chongqing Medical University | 47/186 | 55, 66% | 24, 3 months | PC, ECG | 85.6% | 13.4% | <25 ≥25 | MetS, AF type, duration of AF history, LAD, DM, ablation strategies, procedural failure, and ERAF. | SPVI or CPVA |
| He et al. (30), China | Beijing Anzhen Hospital | 106/330 | 59, 68% | 12, 3 months | RC, ECG | 100% | 0% | Continuous | Gender, HTN, Hs-CRP, serum triglyceride, LAD, and eGFR | CPVI |
| Sotomi et al. (31), Japan | Sakurabashi-Watanabe Hospital | 40/392 | 62, 76% | 32, 3 months | RC, ECG | 71.2% | 28.8% | <25 ≥25 | HTN, persistent AF, high CRP | CVPI |
| Baek et al. (32), Japan | Yonsei AF ablation cohort in Japan | 523/1,825 | 58, 74% | 42, 3 months | PC, ECG | NA | NA | <25 ≥25 | Age, sex, persistent AF, dyslipidemia, and HTN | CPVI |
| Bunch et al. (33), USA | LDS Hospital or Intermountain Medical Center | 1,067/1,558 | 65, 61% | 36, 3-month | RC, ECG | 56.9% | 43.1% | 21–25 26–30 >30 | Age, sex, HTN, hyperlipidemia, DM, HF, renal failure, OSA, prior cardioversion, CHADS2 | PVI |
| Winkle et al. (9), USA | Sequoia Hospital | 678/2,715 | 64, 70% | 12, 3-month | PC, ECG | 32.7% | 54.9% | <35 ≥35 | Age, LAD, sex, AF type, previous cardioversion, number of AADs failed, OSA, previous CVA/TIA, diabetes, CAD, AF duration | CPVI |
| Sivasambu et al. (35), USA | Johns Hopkins Hospital | 354/701 | 59, 72% | 12, 3-month | RC, ECG | 59.1% | 40.9% | 18.5–25 25–30 30–40 >40 | HTN, OSA, CHA2DS2-VASC score, and persistent AF | PVI |
| Glover et al. (36), Canada | Cardiology of Queen’s University | 636/3,333 | 58, 68% | 20, 3 month | PC, ECG | 67.2% | 27.8% | <25 25–30 >30 Continuous | AAD after procedure, achievement of exit and entrance block, first or redo procedure, HTN, CHA2D2S-VAS, OSA, type of AF | CPVI or SPVI |
| Providencia et al. (37), multi-country in Europe | 7 European centers | 916/2497 | 61, 72% | 12, 3-month | PC, ECG | 57.6% | 32.8% | Continuous | Age, female, AF duration, AF type, mean of procedures time, CHA2DAS2-VASC, CHF, HTN, DM, stroke, TIA, vascular disease, OSA, eGFR, LAD, LVEF, procedure duration, additional LA line, AAD, fluoroscopy duration, cavotricuspid isthmus ablation | PVI |
| Trines et al. (38), Sweden | ESC-EHRA-AFA LT registry | 1008/3069 | 59, 68% | 12, 3 months | PC, mixed | 68.3% | 27% | Continuous | HTN | CPVI |
| Baek et al. (39), Korea | Inha University College of Medicine and Inha University Hospital | 416/2221 | 55, 79% | 54, 3 months | RC, ECG | 59% | NA | <25 ≥25 | Age, sex, non-paroxysmal AF, HF, HTN, DM, LAD, AF duration, and MR LGE ≥ 25% | CPVI |
| Bose et al. (40), USA | NA | 19/103 | 60, 29% | 12, NA | RC, ECG | 100% | 0 | <25 25–30 30–35 35–40 >40 | Age, sex, CAD, CHD, HTN, DM, dyslipidemia, valvular heart diseases, beta blocker, CCB, AAD | CPVI |
| Deng et al. (11), China | Guangdong General Hospital | 365/1,410 | 57, 68% | 21, 3 months | PC, ECG | NA | NA | 18.5–25 ≥30 Continuous | Age, gender, bundle branch block, AF duration, COPD, alcohol consumption, smoking, HTN, DM, stroke/TIA, CAD, LVEF, vascular disease, early recurrence, LAD, and AF type | CPVI |
| De Maat et al. (34), Netherlands | University Medical Center Groningen | 146/414 | 56, 76% | 46, 3-month | RC, ECG | 75% | 25% | Continuous | Age, sex, OSA, AAD, LAD, AF duration, AF type, CHD, total cholesterol, number of PVI procedures HTN, DM, vascular disease, and stroke | CPVI |
| Donnellan et al. (42), USA | Cleveland Clinic | 87/267 | 65, 69% | 12, 3 months | RC, ECG | NA | NA | <31.7 ≥31.7 | OSA, AF type, and LA size, OSA, HF | CPVI |
| Kong et al. (43), USA | University of Chicago | 217 | 64, 68.2% | 12, NA | RC, ECG | Na | Na | <30 ≥30 | Age, gender, smoking, HTN, DM, HF, eGFR, and type of AF | PVI |
| Calero Nunez et al. (41), Spain | Albacete University Hospital | 34/114 | 54, 70% | 12, NA | RC, ECG | 70.2% | 29.8% | Continuous | Type of AF, OSA, LA size, ejection fraction, and HTN | CPVI |
| Abou El Khair (44), Sweden | Region Värmland and Örebro | 19/90 | 63, 73% | 12, 3 months | RC, ECG | NA | NA | Continuous | Age, sex, CHA2DS2-VASc score, DM, HF, HTN, LVEDd, and right atrial area. | CPVI |
| Mugnai et al. (45), Belgium | Electrophysiology centre of Brussels | 89/208 | 59, 66% | 62, 3 months | RC, ECG | 100% | 0 | Continuous | Duration of symptoms, LAD | Index PV isolation |
Basic characteristics of the included studies in the dose-response meta-analysis of BMI and AF recurrence in patients post ablation.
RC, retrospective cohort; PC, prospective cohort; ECG, electrocardiograph; NA, not available; PVI, pulmonary vein isolation; CPVI, circumferential pulmonary vein isolation; SPVI, segmental pulmonary vein isolation; CPVA, circumferential pulmonary vein ablation; LAD, left atrial diameter; MetS, metabolic syndrome; ERAF, early recurrence of AF after ablation; OSA, obstructive sleep apnea; WBC, white blood cell; CRP, C-reactive protein; CAD, coronary artery disease; AAD, antiarrhythmic drugs; CHRD, centre for heart rhythm disorders; LVEF, left ventricular ejection fraction; eGFR, estimated glomerular filtration rate; ACEIs/ARBs, ACE inhibitors/ARB inhibitors; SHD, structural heart disease; CHF, congestive HF; CVA, cerebrovascular accident; TIA, transient ischemic attack; AF, atrial fibrillation; BMI, body mass index; Par, paroxysmal; HTN, hypertension; COPD, chronic obstructive pulmonary disease; USA, United States of America; MR LGE, late gadolinium enhancement on cardiac magnetic resonance.
The quality of the articles was acceptable, with a majority (n = 23) of studies scores Newcastle-Ottawa Scale ≥ 7 points (Supplementary Table 4).
Dose-response analysis of the association of BMI with the risk of post ablation AF recurrence
Twenty-six (6–11, 26–45) studies including 7,878 cases/26,450 individuals were included in the dose-response analysis. The summary RR for a 5-unit increase in BMI was 1.15 (95% CI: 1.08–1.22, I2 = 53%), with moderate heterogeneity (Figure 2). There was little evidence of heterogeneity (I2 = 34%) after excluding studies from Cai et al. (29) and Kang et al. (7), but a positive association remained (RR = 1.12, 95% CI: 1.07–1.18). In the non-linear analysis, we found a borderline positive linear association between BMI and AF recurrence after ablation (Pnon–linearity = 0.12) (Figure 3). Supplementary Table 5 displays the RR estimates and 95% CIs from the specific BMI values derived from the dose-response figures.
FIGURE 2
Body mass index and atrial fibrillation recurrence in patients undergoing radiofrequency ablation based on a dose-response analysis, per 5 units.
FIGURE 3
Body mass index and atrial fibrillation recurrence in patients undergoing radiofrequency ablation based on a non-linear dose-response analysis. The solid and dashed lines represent the estimated relative risk and the 95% confidence interval, respectively.
Subgroup analysis, sensitivity analysis, and publication bias
There may be a stronger association between BMI and AF recurrence among groups with larger AF recurrence cases (Pheterogeneity = 0.006). The positive association between BMI and AF recurrence persisted in almost all subgroups stratified by age, time of follow-up, region, and sample size after adjusting for confoundings (e.g., OSA), and there was little evidence of heterogeneity across these subgroups (Table 2).
TABLE 2
| Items | Number of studies | RR | 95% CI | I2 | P | ||
| Within subgroup | Between subgroup | ||||||
| Result of primary analysis | 21 | 1.15 | 1.08, 1.22 | 54% | 0.002 | NA | |
| Age* | ≤60 | 13 | 1.10 | 1.03, 1.17 | 38% | 0.005 | 0.19 |
| >60 | 7 | 1.20 | 1.08, 1.33 | 60% | 0.003 | ||
| Study design | Retrospective cohort | 10 | 1.11 | 1.02, 1.21 | 39 | 0.001 | 0.12 |
| Prospective cohort | 11 | 1.25 | 1.11, 1.39 | 68 | 0.001 | ||
| Region | Northern America | 8 | 1.08 | 1.03, 1.12 | 0% | 0.0003 | 0.06 |
| Europe | 6 | 1.18 | 1.06, 1.33 | 46% | 0.004 | ||
| Asia | 7 | 1.30 | 1.08, 1.56 | 65% | 0.006 | ||
| NOS scores | <7 scores | 2 | 1.16 | 1.00, 1.36 | 26% | 0.06 | 0.76 |
| 7 or high scores | 19 | 1.13 | 1.07, 1.20 | 51% | <0.001 | ||
| Publication years | 2008–2013 | 9 | 1.13 | 1.07, 1.19 | 43% | <0.001 | 0.28 |
| 2014–2021 | 12 | 1.28 | 1.03, 1.60 | 65% | 0.03 | ||
| Sample size | ≤1,000 | 14 | 1.24 | 1.08, 1.43 | 57% | 0.003 | 0.11 |
| >1,000 | 7 | 1.10 | 1.05, 1.15 | 22% | 0.0001 | ||
| Cases | ≤100 | 9 | 1.70 | 1.26, 2.31 | 54% | 0.006 | 0.006 |
| >100 | 12 | 1.10 | 1.05, 1.14 | 26% | 0.001 | ||
| Adjusted factors | Age (+) | 11 | 1.21 | 1.04, 1.21 | 57% | 0.003 | 0.26 |
| Age (−) | 10 | 1.23 | 1.07, 1.42 | 60% | 0.004 | ||
| Sex (+) | 13 | 1.19 | 1.09, 1.31 | 59% | <0.001 | 0.90 | |
| Sex (−) | 8 | 1.21 | 1.05, 1.40 | 63% | 0.01 | ||
| DM (+) | 11 | 1.29 | 1.14, 1.47 | 76% | <0.001 | 0.02 | |
| DM (−) | 10 | 1.09 | 1.02, 1.17 | 11% | 0.001 | ||
| left atrial size (+) | 9 | 1.16 | 1.04, 1.30 | 64% | 0.004 | 0.86 | |
| left atrial size (−) | 12 | 1.15 | 1.06, 1.23 | 45% | 0.04 | ||
| Hypertension (+) | 15 | 1.14 | 1.08, 1.20 | 30% | <0.001 | 0.37 | |
| Hypertension (−) | 6 | 1.26 | 1.02, 1.57 | 73% | 0.03 | ||
| AF categories (+) | 10 | 1.11 | 1.04, 1.18 | 42% | 0.08 | 0.07 | |
| AF categories (−) | 11 | 1.29 | 1.11, 1.51 | 62% | 0.001 | ||
| Obstructive sleep apnea (+) | 7 | 1.11 | 1.05, 1.17 | 36% | <0.001 | 0.23 | |
| Obstructive sleep apnea (−) | 14 | 1.20 | 1.07, 1.36 | 60% | 0.003 | ||
Subgroup analysis of BMI and AF recurrence in patients after catheter ablation, dose-response analysis, per 5 unit increase.
AF, atrial fibrillation; BMI, body mass index; DM, diabetes mellitus. *The mean age of Khair et al. was not available. Bolded values are meant to be the total results of all studies before subgroup analysis.
In the sensitivity analysis, the pooled results were stable when omitting one study at a time, with an RR range from 1.13 (95% CI: 1.07–1.20, I2 = 47%) to 1.16 (95% CI: 1.09–1.25, I2 = 53%). The result was also stable by excluding studies with a blank period < 3 months (RR: 1.15, 95% CI: 1.08–1.23) (Supplementary Figure 1). Publication bias was assessed using Egger’s test (p = 0.004), Begg’s test (p = 0.019), or funnel plots (Supplementary Figure 2). However, metatrim analysis showed that the addition of six missing studies did not significantly change the results, with a decreased magnitude of the pooled effect size (RR: 1.11; 95% CI: 1.03–1.18) (Supplementary Figure 3).
Discussion
Main findings
Based on available cohort studies, we showed a borderline positive linear dose-response relationship between baseline BMI and AF recurrence in patients after ablation. We found a 15% increase in AF recurrence per 5-unit increase in BMI. These results were confirmed in all subgroups stratified by age, sex, study design, region, follow-up duration, sample size, and adjustment. Overall, our results showed that overweigh (BMI > 28 kg/m2) or obesity was independently positively associated with AF recurrence after ablation.
Several well-known risk factors, including age, hypertension, diabetes, and enlarged LAD, have been linked to the recurrence of AF after ablation. Moreover, these comorbidities were common in patients with obesity. Therefore, whether the role of obesity is independent of these comorbidities is still unclear. For example, Jongnarangsin et al. showed that obesity was not associated AF recurrence post AF ablation after adjustments (26), suggesting obesity may simply be a phenotypic marker of profibrillatory comorbidities and not the key predictor of ablation failure. Moreover, although several previous meta-analyses (12, 13, 16) showed that obesity was associated with an increased risk of AF, none of them conducted a stratified analysis according to these confounding factors; therefore, this relationship is still under debate. We showed that the positive association of BMI and AF recurrence after ablation was still positive in all subgroups after adjustments, including those for hypertension, diabetes, age, OSA, and LAD (Table 2), which suggested that obesity was a factor contributing to AF recurrence, independent of conventional risk factors.
Although we found a linear association between BMI and AF (p for non-linearity = 0.12), we should explain these results with caution. As shown in Figure 3, we should figure out that the dose-response curve is much steeper at the BMI > 35. Specifically, a change in BMI of 25–30 kg/m2 increases the RR from 1.08 to 1.38, while RR increased sharply (1.95–2.78) between the 35 and 40 kg/m2 BMI group, somewhat reflecting a non-linear trend at higher BMI values. This observation reinforces the previous findings, showing severe obesity was a strong risk factor for cardiovascular diseases, including incident AF. A previous meta-analysis (14) also examined the dose-response analysis of BMI and risk of AF recurrence, but it failed to demonstrate the existence of a linear dose-response relationship. Although we demonstrated a borderline linear relationship between BMI and AF recurrence, the study demonstrated a dramatic increase in the risk of AF recurrence when BMI was greater than 35 kg/m2, so we would carefully interpret the borderline linear association. We should include more relevant studies. The non-linear p value might be significant if more population with high BMI were include. Overall, we should point out that grade II obesity substantially increased the risk of AF relapse after ablation. Weight loss intervention might be encouraged for these patients with severe obesity to reduce rate of AF relapse. 2020 European Society of Cardiology guidelines did not set a BMI threshold value for weight loss in obese patients who plan to receive AF ablation, while our results provide a valuable information for this.
Comparison with other studies
In the context of AF ablation, obesity was not a new topic. Several reviews have shown that obesity increases the risk of AF relapse after ablation. Three showed that the obese group had a significantly increased risk of AF recurrence (13, 15, 16). In another excellent review by Wong et al., for every 5-unit increase in BMI, there was a 13% greater excess risk of post AF ablation (12). A recent meta-analysis included 12 studies reported a positive non-linear dose-response relationship between BMI and AF ablation (14). Interestingly, with the inclusion of more studies (N = 26), our results were opposite to theirs, showing a borderline positive linear dose-response relationship (P = 0.16), revealing a threshold effect between BMI and the risk of AF recurrence after ablation. In addition, the five published meta-analyses did not take into account confounding factors such as age, hypertension, AF category, diabetes, OSA, and LAD and did not demonstrate whether obesity could independently increase the risk of AF recurrence. We showed that the positive association of BMI and AF recurrence after ablation was still positive in all subgroups after adjustments, which suggested that obesity was a factor contributing to AF recurrence, independent of conventional risk factors.
Underlying mechanism
Several potential mechanisms could explain this association. First, obesity could result in many changes involving various domains, such as hemodynamics, neurohumoral factors, inflammatory factors, metabolic factors, adipokines, and autonomics. For example, obesity leads to a high cardiac output state and the presence of left ventricular hypertrophy (eccentric or concentric) in association with left ventricular diastolic dysfunction (46). The hemodynamic changes associated with the elevation in left atrial and systolic blood pressure and left ventricular diastolic dysfunction contribute to atrial stretch and “trigger” AF (47). Furthermore, obesity is considered a state of chronic low-grade inflammation (48, 49). Studies have shown that patients with a higher BMI exhibit increased levels of several inflammatory and oxidative stress markers, including high-sensitivity C-reactive protein, serum creatinine, fibrinogen, and uric acid (50). Numerous studies have also demonstrated the implication of inflammation and oxidative stress in the pathophysiology of AF (51, 52). Therefore, it is reasonable to assume that obesity-associated inflammation may contribute to AF recurrence after ablation. Finally, it must be noted that the pathophysiological mechanisms linking obesity and AF are highly complex and remain incompletely understood. It is likely that a combination of multiple factors previously mentioned contributes to the recurrence of AF after ablation.
Future research
Some authors proposed that obesity was a phenotypic marker of OSA that is associated with AF recurrence. Obesity is an important risk factor for the incidence of OSA (53), and the association between OSA and AF has been explored extensively (28). A meta-analysis reported that patients with OSA had a 25% greater risk of AF recurrence after ablation than those without OSA (53). The present study showed that the positive association was significant regardless of adjustment for OSA, which suggested that obesity increased the risk of AF recurrence independently of OSA. Therefore, we hypothesized that OSA may not be a mechanism by which obesity results in AF recurrence. Furthermore, a large retrospective cohort study also showed that obesity remains a powerful predictor of incident AF in patients without OSA based on the gold standard diagnostic test (54). This finding was consistent with our results, which suggested that obesity contributes to AF recurrence after ablation independent of OSA. However, considering the limited studies in the subgroup (N = 7), further prospective studies are needed to confirm our results.
The association between underweight and AF relapse is still inconclusive. Based on a retrospective cohort study in China, Deng et al. showed that underweight (BMI < 18.5 kg/m2) significantly increased the risk of AF recurrence (HR 1.85, P = 0.02) (11). In contrast, by using a different definition of underweight (BMI < 20 kg/m2), Bunch et al. did not find an elevated risk of AF recurrence of underweight in the US (33). However, the scarcity of studies precludes us from performing a dose-response analysis, which may be attributed to the high prevalence of obesity in Western countries. However, evidence from several population-based studies has shown that underweight is a risk factor for AF. Therefore, although the results regarding underweight and AF relapse were inconclusive, we supposed there may be a positive association between underweight and the risk of AF recurrence in patients undergoing ablation. More studies are warranted to address this issue.
In addition, although BMI is widely adopted because it is convenient to apply and inexpensive, BMI is not perfect as a measure of obesity. Because BMI is an indirect measure of obesity, it cannot distinguish between fat and lean tissue and can produce a certain amount of error (55). The problem may lead to misclassification of the experimental population in terms of body fat and may introduce bias. The impact of other parameters of body fat and body composition (e.g., waist circumference and waist-hip ratio) on outcomes among patients undergoing ablation should be further assessed by future studies.
Policy implications
As shown in our results, the likelihood of AF recurrence after ablation increasing with BMI. In patients with grade II obesity (BMI > 35 kg/m2), the risk of AF recurrence increased by 95%. Our findings provide valuable insight for the clinical prevention of AF recurrence after ablation. For patients with severe obesity (BMI > 35 kg/m2), cardiologists should consider that their likelihood of AF relapse is much higher than that of individuals with a normal BMI. Therefore, for those patients strongly considering AF ablation, the risks and benefits should be carefully evaluated.
Weight loss is associated with improvements in risk factors (e.g., hypertension, OSA, and glycemic control), decreased morbidity and mortality, and a decreased risk of AF. Evidence from observational studies, such as the Long-Term Effect of Goal-Directed Weight Management in an Atrial Fibrillation (LEGACY) study, showed that long-term weight loss (bariatric surgery or weight management) could reduce AF risk and burden in people with AF (56). Moreover, the benefit of weight loss from the prevention of AF was dose-dependent. A 10% weight loss with accompanied risk factor modification reduced the risk among arrhythmia-free patients by 45% compared with that associated with 3% weight loss (56). Therefore, current guidelines set the weight loss target at > 10% weight reduction with lifestyle modifications for BMI < 27 kg/m2 (18) to improve AF ablation. However, weight loss, either through lifestyle or bariatric surgery, is typically a long process. It is well-described that increasing the duration of AF has negative effects on ablation success rates. The time required for weight loss would have resulted in a delay of ablation of at least 6 months, which would have led to AF progression with worsening of success rates. Therefore, it is not recommended for all patients with overweight or obesity to lose weight; the benefits and risks should be carefully considered.
Strengths and limitations
The strengths and limitations of this study merit careful consideration. This is the first dose-response meta-analysis that demonstrated a positive linear association between BMI and AF recurrence after ablation with a large sample size and robustness of the findings based on multiple subgroups (e.g., age, sex, duration of follow-up and adjustment for confounding and potential intermediate factors). However, it was limited by the inclusion of observational studies, which cannot definitively prove causation. Although most studies were adjusted for other comorbidities, it is impossible to fully take into account all confounding factors. For example, the dose of antiarrhythmic medication may differ between studies, and studies have shown that LA volume is more accurate than diameter. Second, several studies have shown that underweight and AF patients have worse outcomes (11). However, due to data restrictions, the impact of underweight (BMI < 18.5) on AF recurrence after ablation was not analyzed and needs to be further investigated. Third, BMI may not accurately indicate the degree of body adiposity, and the impact of other parameters of body fat and body composition (e.g., waist circumference and waist-hip ratio) on outcomes among patients undergoing ablation should be further assessed by future studies. Fourth, ablation techniques across studies may also influence our results. Overall, further well-designed, larger clinical trials are needed to confirm our results.
Conclusion
This study demonstrated a positive independent association between BMI and AF recurrence among patients undergoing ablation, and overweight and obesity were found to be significantly associated with AF recurrence. Further well-designed, prospective studies are required to determine the effect of weight loss on AF recurrence post ablation.
Statements
Data availability statement
The original contributions presented in this study are included in this article/Supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
JL was responsible for the entire project and revised the draft. FL, TS, and XL performed the systematic literature review and drafted the first version of the manuscript. All authors participated in the interpretation of the results and prepared the final version of the manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (Nos. 81760050, 81760048, 82100347, and 8210020907), the Jiangxi Provincial Natural Science Foundation for Youth Scientific Research (No. 20192ACBL21037), and China Postdoctoral Science Foundation (No. 2021M703724).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2022.999845/full#supplementary-material
Abbreviations
AF, atrial fibrillation; RR, relative risk; BMI, body mass index; ablation, radiofrequency ablation; LAD, left atrial diameter.
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Summary
Keywords
body mass index, obesity, atrial fibrillation, exposure-effect, meta-analysis, radiofrequency ablation
Citation
Liu F, Song T, Hu Q, Zhu X, Zhao H, Tan Z, Yu P, Ma J, Luo J and Liu X (2023) Body mass index and atrial fibrillation recurrence post ablation: A systematic review and dose-response meta-analysis. Front. Cardiovasc. Med. 9:999845. doi: 10.3389/fcvm.2022.999845
Received
21 July 2022
Accepted
29 December 2022
Published
02 February 2023
Volume
9 - 2022
Edited by
Sergio Conti, ARNAS Ospedali Civico Di Cristina Benfratelli, Italy
Reviewed by
Deyong Long, Capital Medical University, China; Giovanni Perego, Italian Auxological Institute (IRCCS), Italy
Updates
Copyright
© 2023 Liu, Song, Hu, Zhu, Zhao, Tan, Yu, Ma, Luo and Liu.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jun Luo, luojun1966@163.com
†These authors have contributed equally to this work and share first authorship
‡Senior author
This article was submitted to Cardiac Rhythmology, a section of the journal Frontiers in Cardiovascular Medicine
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.