Multi-domain Dialogue State Tracking (DST) requires discourse coherence that transcends independent slot-filling. Most existing approaches rely on statistical regularities within static schemas, failing to capture the semantic coordination governing simultaneous slot updates. In this paper, we propose Event-DST, which models latent events as cognitive organizing units to dynamically coordinate slot interactions. By projecting dialogue context into a continuous semantic space, our model induces a dynamic structural bias to enforce pragmatic consistency. This structural guidance is integrated via a dual-stream fusion strategy that balances top-down structural constraints with bottom-up textual precision. Experimental results on two benchmarks demonstrate the superiority of our framework, providing an interpretable and parameter-efficient path toward robust dialogue understanding.