I have a simple model with only one independent variable, and it is binary/categorical (as is the dependent variable). The log-odds estimate is 4.6821 with a standard error of 0.4978. The point estimate for the odds ratio is 108, with a confidence interval of 40.708 , 286.527.

I ran the same model, simply changing the reference and the log-odds estimate is -4.6821, same standard error, but the point estimate for the odds ratio is 0.009 with a confidence interval of 0.003 , 0.025. This seems reasonable.

Is an odds ratio of 108 valid? Since both my dependent and independent variables are binary/categorical, it isn't an issue of outliers. I only have 2 missing values. Sample sizes are sufficient (275 negative, 102 positive, 73 Y, and 304 N). For Y and negative there are only 5. Could that account for such an inflated odds ratio?