Bootstrap confidence intervals depend on three elements: (a) the cumulative distribution of the bootstrap replications, (b) the bias-correction, and (c) the acceleration number that measures the rate of change in the standard deviation of the estimate as the data changes. The first two of these depend only on the bootstrap distribution, and not how it is generated: parametrically or non-parametrically. Therefore, the only difference in a parametric bca analysis would lie in the nonparametric estimation of the acceleration, often a negligible error.