Analysis of 16 cardiovascular polygenic risk scores in 4,137 participants revealed that while these genetic tests perform similarly at the population level, they produce wildly inconsistent results for individual patients. For a typical person, risk estimates varied by ±18 percentile points across different scoring systems, with 75.6% of participants classified into different risk categories depending on which test was used. Most concerning, 54.6% of individuals were simultaneously classified as both low and high cardiovascular risk by different scores. The variability primarily stemmed from methodological differences in how scores are calculated rather than genuinely distinct genetic insights. When integrated into clinical risk calculators like SCORE2-OP, this inconsistency far exceeded the measurement error from standard clinical variables like blood pressure. These findings expose a critical weakness in the clinical application of genetic testing for heart disease prevention. While polygenic scores hold promise for personalized medicine, this preprint—awaiting peer review—suggests current implementations may create more confusion than clarity for individual patients. The research underscores the urgent need for standardized methodologies and rigorous clinical trials before widespread adoption of cardiovascular genetic risk assessment.