While P-values in clinical studies are an easy method to denote statistical significance, the interpretation of significant findings can be somewhat skewed. The Fragility Index is a newly developed metric that complements p-values and confidence intervals. It is calculated by adding consecutive events to a significant dichotomous finding until the result is no longer significant. The number of events needed to be added thus represents the fragility of the finding. Analysis of 399 trials published within high-impact journals found a median Fragility Index of 9, with 25% of studies at a Fragility Index of 3 or lower. Linear regression indicated that findings were less fragile when the reported P-values were lower (ie. P<0.001), the number of events reported was high, or when a large number of participants were included in the study. Application of the Fragility Index should hopefully aid readers in their determination of the impact of significant findings within the literature.