The fixed time event-triggered control for high-order nonlinear uncertain systems with time-varying state constraints is investigated in this paper. First, the event-triggered control (ETC) mechanism is introduced to reduce data transmission in the communication channel. In consideration of the physical constraints and engineering requirements, time-varying barrier Lyapunov function (BLF) is deployed to make the system states confined in the given time-varying constraints. Then, the radial basis function neural networks (RBF NNs) is used to approximate the unknown nonlinear terms. Further, the fixed time stability strategy is deployed to make the system achieve semiglobal practical fixed time stability (SPFTS) and the convergence time is independent of the initial conditions. Finally, the proposed control scheme is verified by two simulation examples.