A reanalysis of a randomized trial showing coffee reduces atrial fibrillation recurrence reveals the statistical significance may overstate clinical benefits. The original study reported a statistically significant risk reduction (p <0.01) for caffeinated coffee versus abstinence, but Bayesian modeling found only modest probabilities of clinically meaningful effects—88% chance of hazard ratio below 0.9 and 82% chance of risk difference exceeding 2%. The trial suffered from limited statistical power for realistic effect sizes, making it vulnerable to type-M error where significant results exaggerate true effect magnitude. This represents a crucial methodological advance in interpreting cardiovascular trials. Many studies report statistically significant results that may not translate to clinically meaningful benefits for patients. The coffee-heart rhythm connection remains biologically plausible through adenosine receptor antagonism, but this analysis suggests the protective effect may be smaller than initially reported. As this is a preprint awaiting peer review, these reanalysis methods require validation. However, the approach offers a template for evaluating unexpected trial results across cardiovascular medicine, helping clinicians distinguish between statistical artifacts and genuine therapeutic breakthroughs.