# Logistic regression and normal distribution of predictors

I have a question and I hope someone can help me with my confusion. I want to run a univariable logistic regression model to see whether my predictor (which is not normally distributed, but also not crazy skewed) is associated with the odds of the outcome (dichotomous). I understand that it is not necessary to have a normally distributed predictor. However, when I run the model with it the odds are not significant, whereas if I just transform it to log(predictor) the odds are significant. How can that be and what is the right way? When I just use a t-test between the two outcomes using log(predictor) the p-value is almost identical with the regression model that uses log(predictor). Is that a coincidence?