In this paper the distribution of a concomitant statistic in a Gaussian sequential setting is characterized. It is shown that the distribution of such a statistic, conditional on the value of the stopping time, can be represented as a convolution of a normal random variable with a stochastic integral of the monitoring process of the trial. For continuous sequential designs the characteristic function of this stochastic integral is shown to satisfy an integral equation. The tools developed here are relevant for secondary inference problems in sequential clinical trials.