Modifiable Risk Burden, ECG-Documented Atrial Fibrillation/Flutter, and Systemic Inflammation in a German Prevention Survey

C. Schach (Regensburg)1, L. Krämer (Regensburg)1, J. Micek (Regensburg)1, J. Pangratz (Regensburg)2, R. Lutzke (Regensburg)2, J. Konzok (Regensburg)3, J. Pec (Regensburg)1, I. Haiberger (Regensburg)1, I. Abou Tabikh (Regensburg)1, M. Wester (Regensburg)1, C. Brummer (Regensburg)4, A. Herrmann (Regensburg)5, A. Mühlberger (Regensburg)3, L. S. Maier (Regensburg)1, E. Ücer (Regensburg)1
1Universitätsklinikum Regensburg Klinik und Poliklinik für Innere Med. II, Kardiologie Regensburg, Deutschland; 2Regensburg, Deutschland; 3Institut für Psychologie Regensburg, Deutschland; 4Klinik und Poliklinik für Innere Medizin 3 Hämatologie/Onkologie Regensburg, Deutschland; 5Fakultät für Medizin Institut für Epidemiologie und Präventivmedizin Regensburg, Deutschland

Background: Atrial fibrillation/flutter (AF/AFl) is closely linked to modifiable cardiovascular risk factors, but prevention-oriented phenotypes integrating lifestyle, psychosocial, and inflammatory domains are incompletely characterized.

Hypothesis: A patient-reported modifiable risk-burden score is associated with contemporaneous ECG-documented AF/AFl and with systemic inflammation.

Methods: In a cross-sectional German prevention survey, six binary AF-relevant risk domains were derived: obesity, unfavorable smoking status, higher alcohol consumption, low physical activity, poor sleep, and higher mental stress. Domains were summed to a 0–6 risk-burden score, requiring ≥5 available domains. Among participants with ECG data, AF/AFl versus sinus rhythm was analyzed using logistic regression with robust standard errors. The primary model adjusted for age, sex, and education. A secondary model additionally included self-reported cardiovascular disease, which contained self-reported AF and was therefore considered potentially overlapping with the outcome. In a biomarker subset, an inflammation score was derived from log-transformed CRP values <50 mg/L, platelet count, and neutrophil-to-lymphocyte ratio; components were z-standardized, summed, and rescaled from 0 to 1 using capped 1st–99th percentile scaling.

Results: Of 1,228 participants, 519 had ECG data; AF/AFl was documented in 113 participants (21.8%). Compared with participants without ECG data, the ECG subgroup was older, more often male, had higher BMI, more frequent self-reported cardiovascular disease, and higher risk burden. Higher risk burden was associated with ECG-documented AF/AFl after adjustment for age, sex, and education (OR 1.30 per burden point, 95% CI 1.04–1.63; p=0.024). Results were similar after additional adjustment for self-reported cardiovascular disease (OR 1.29, 95% CI 1.02–1.64; p=0.034). A sensitivity score excluding mental stress showed a stronger association with AF/AFl (OR 1.51, 95% CI 1.13–2.02; p=0.006). In the biomarker subset, risk burden correlated with inflammation (Spearman ρ=0.176; p=0.0003) and remained associated after adjustment for age, sex, and self-reported cardiovascular disease (β=0.031 per burden point, 95% CI 0.015–0.047; p<0.001). Inflammation itself was not independently associated with AF/AFl in multivariable analysis.

Conclusions: In this prevention-focused survey, a simple patient-reported modifiable risk-burden score identified participants with higher probability of ECG-documented AF/AFl and was mirrored by higher systemic inflammation. These findings support integrated prevention phenotyping that combines lifestyle, psychosocial, and inflammatory risk signals. Because ECG acquisition was enriched for higher-risk participants and the design was cross-sectional, the results should be interpreted as hypothesis-generating.