Risk of atrial fibrillation in athletes: a systematic review and meta-analysis

In the paper

“Two prior meta-analyses investigating the possible increased risk of AF in athletes have demonstrated equivocal findings, with ORs of 1.64 14 and 5.29.15”

What the sources say

• Supported

  The Results of the analyses report an odds ratio of 5.29 (95% CI 3.57–7.85) for atrial fibrillation in athletes versus controls. In the citing sentence, this paper is cited for the 5.29 estimate; the 1.64 estimate is assigned to a different citation. (LLM, conf=0.93)

  cites [14] source
• Supported

  The Results report this meta-analysis’s pooled odds ratio of 1.64 for atrial fibrillation in athletes versus the general population. The Discussion also identifies the earlier meta-analysis reporting 5.29 and notes that its effect size was much larger, supporting the comparison of differing estimates. (LLM, conf=0.92)

  cites [15] Ayinde, 2018, Age modifies the risk of atrial fibrillation among athletes: a systematic literature review and meta-analysis, Int J Cardiol Heart Vasc source

In the paper

“It has been reported that male endurance athletes performing high-intensity and high-volume exercise training are at an increased risk, 9”

What the sources say

• Partly supported

  The Abstract reports a higher risk of symptomatic lone atrial fibrillation in male marathon runners than in sedentary men. The Discussion (Figure 2 section; page unavailable) indicates substantial lifetime sport practice among the runners, but the paper does not establish that high training intensity specifically increases risk; its finding is also narrower than atrial fibrillation generally. (LLM, conf=0.83)

  cites [9] sourceExperimental — accuracy not yet measured

In the paper

“with studies suggesting a U-shaped curve, with lack of physical activity and long-term vigourous exercise both increasing the risk of developing AF. 10 11”

What the sources say

• Supported

  The discussion and Figure 2 caption (p. 3624) describe a U-shaped relationship: AF risk falls with regular mild-to-moderate activity, then rises with more sustained vigorous exercise. The paper presents this as a suggested pattern drawn from studies, matching the claim's qualification. (LLM, conf=0.92)

  cites [10] source
• Partly supported

  The Introduction reports reduced AF risk with moderate activity and increased risk with high-intensity or endurance exercise in younger athletes and middle-aged men, supporting the suggested curve for those groups. The Results (Physical activity and AF) found that activity above 1,000 MET-minutes/week was not associated with higher risk than inactivity, so this paper does not establish increased risk at both extremes in the general population. Page numbers were not supplied in our copy. (LLM, conf=0.86)

  cites [11] sourceExperimental — accuracy not yet measured

In the paper

“Interestingly, Ayinde et al 15 identified age as a significant determinant of AF risk, with younger athletes (below 40 years old) at greater relative risk than athletes >54 years of age.”

What the sources say

• Partly supported

  The Results (Stratified analysis > Age) identify age as an effect modifier: athletes under 54 had significantly higher odds of AF than similarly aged controls, while the increase was not significant among athletes 54 or older. The paper uses a cutoff of 54, not 40, and compares each athlete age group with controls rather than directly comparing younger and older athletes. (LLM, conf=0.90)

  cites [15] Ayinde, 2018, Age modifies the risk of atrial fibrillation among athletes: a systematic literature review and meta-analysis, Int J Cardiol Heart Vasc sourceExperimental — accuracy not yet measured

In the paper

“Investigating the mechanistic underpinning of this age-dependant risk, Hoogsteen et al 24 discuss AF being triggered by adrenergic surges occurring during exercise in younger athletes, 25 whereas older athletes typically experience vagally induced AF after exercise, normally from secondary autonomic dysfunction.26”

What the sources say

• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [24] Hoogsteen, 2004, Recommendations and cardiological evaluation of athletes with arrhythmias: Part 1, Neth Heart JExperimental — accuracy not yet measured
• Partly supported

  Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.

  cites [25] sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [26] source

In the paper

“Mechanistically, Wilhelm 13 indicates biatrial remodelling, dilation and fibrosis as crucial substrates to developing this pathology.”

What the sources say

• Partly supported

  In “The substrate: atrial remodelling in athletes” (page unavailable), Wilhelm reports enlargement of both atria in endurance athletes and says enlargement accompanied by fibrosis in aging athletes may create a substrate for atrial fibrillation. Calling remodelling, dilation and fibrosis unqualified “crucial substrates” overstates that tentative, age-dependent account; the section also notes that enlarged atria in young athletes did not necessarily increase AF risk. (LLM, conf=0.86)

  cites [13] sourceExperimental — accuracy not yet measured

In the paper

“This analysis may also be limited by the possibility of sparse data bias in the pooled OR estimates, as indicated by the unconventional ORs and wide confidence limits produced by some studies.This is problematic as such bias can inflate the estimate of effect measures, which should be taken into account when interpreting the findings of the present analysis.37”

What the sources say

• Supported

  The paper’s Abstract explains that sparse data bias can inflate estimated effect ratios, including odds ratios. Its “Preliminary checks for sparse data bias” passage illustrates unusually large odds ratios with wide confidence intervals. The citing authors frame its possible relevance to their pooled analysis as their own interpretation. (LLM, conf=0.90)

  cites [37] Greenland S , Mansournia MA , Altman DG . Sparse data bias: a problem hiding in plain sight. BMJ;2016:i1981. doi:10.1136/bmj.i1981 source

In the paper

“Only two studies provided data on volume or average duration of exercise and both defined this by lifetime exercise hours and could therefore not be used to quantify weekly exposure.”

In the paper

“Of the endurance sports, cycling conferred the highest risk of AF and Nordic skiing conferred the lowest risk (see online supplemental figure S3 for the lowest to highest risk of AF in endurance sports).”

In the paper

“Crucially, our research identifies a significant relationship between mode of exercise and risk of developing AF, with mixed sport conferring a greater risk than endurance sport.”

In the paper

“Five studies included athletes with the CVD risk factors diabetes and/or hypertension.”

In the paper

“The meta-analysis included 13 studies (7 cohort and 6 case-control) with a pooled sample size of 70 478 participants, which included 63 662 controls and 6816 athletes (online supplemental file).”

In the paper

“However, it was not possible to appropriately analyse the association of exercise intensity and AF risk due to insufficient data.”

In the paper

“The post hoc Egger's test (1997) was statistically significant (p<0.001),suggesting publication bias.”

In the paper

“Of the studies included in the analysis, three involved Nordic skiing, with these studies representing 36% of the total weighting in the overall effect size.”

In the paper

“Study data was extracted and a risk of bias analysis performed, which were systematically screened by a second reviewer.When disputes were detected in coding or quality analyses, the reviewers met to discuss any conflicts, which were then resolved and evaluated further.”

In the paper

“This systematic review and meta-analysis was fully compliant with and performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 16 including use of the described PICOS method for the systematic review process.”

What the sources say

• ?Not checked — no full text of the sourcecites [16] source

In the paper

“Qualitative risk of bias assessment was carried out utilising the tool from CLARITY at McMaster University (Evidence Partners, 2019) to ascertain the risk of bias in the cohort and case-control studies independently.”

In the paper

“Additionally, the inclusion of studies involving athlete cohorts with common health conditions offers a more 'real world' estimation.”

In the paper

“Indeed, the observation that endurance sports correlate with AF is generally accepted.21”

What the sources say

• ?Not checked — no full text of the sourcecites [21] source

In the paper

“However, the OR in older athletes was still 1.76 and much higher compared with non-athletes and thus must not be ignored.”

In the paper

“With this, it cannot be excluded that the remaining endurance sports included were comparatively underestimated in the analysis with Nordic skiing over-represented due to a greater quantity of published studies.”

In the paper

“Prior research suggests there is a threshold beyond which exposure to increasing levels of exercise is associated with an increased risk of cardiovascular disease, including arrhythmias (U-shaped relationship).”

In the paper

“First, our OR, considering all primary studies, of 2.46 is much closer to the 'true' value as we included studies examining athletes, physically active individuals and sedentary populations, unlike other analyses.”

In the paper

“Indeed, 84% is well above an expected I 2 value for a meta-analysis, probably owing to the differences in methodological parameters in the included studies.20”

What the sources say

• ?Not checked — no full text of the sourcecites [20] source

In the paper

“With this, the lower association of AF in older athletes compared with younger athletes has been previously linked to the higher rates of AF in older individuals, independent from physical activity levels.27”

What the sources say

• ?Not checked — no full text of the sourcecites [27] source

In the paper

“Additionally, Furlanello et al 23 examined the relationship between AF risk and sport participation in elite and Olympic athletes, finding a significant prevalence among young (average age 24 years old), male athletes.”

What the sources say

• Not checked yetcites [23] Furlanello, 1998, Atrial fibrillation in elite athletes, J Cardiovasc Electrophysiol

In the paper

“As detailed in Greenland and O'Rourke, 32 the present analysis would have benefited from adjustment using external estimates in those studies which do not apply sufficient adjustment.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [32] Greenland S , O’Rourke K . Meta-analysis. In: Rothman KJ , Greenland S , Lash T , eds. Modern epidemiology. 3rd edn. Philadelphia, PA: Lippincott Williams & Wilkins, 2008.

In the paper

“Indeed, it is possible that studies with a null hypotheses of a significant relationship between AF and athletes were not published, alongside bias in study methodologies.”

In the paper

“Finally, due to the lack of available data, we were unable to provide information regarding training volume and the risk of AF.”