Intervention-Aware Clinical World Model for Post-Op Outcome Forecasting in Cardiology

• URL: http://arxiv.org/abs/2608.13518v1
• Date: Thu, 13 Aug 2026 17:38:13 GMT
• Title: Intervention-Aware Clinical World Model for Post-Op Outcome Forecasting in Cardiology
• Abstract summary: Many clinical prediction models treat post-intervention outcomes as a one-step mapping from baseline measurements to a future endpoint.<n>We propose an intervention-aware clinical world model that represents each patient with a structured latent state and evolves it through time-ordered post-intervention events.
• Score: 8.701738697134955
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Many clinical prediction models treat post-intervention outcomes as a one-step mapping from baseline measurements to a future endpoint. However, recovery after a procedure often unfolds as an irregular trajectory: clinical observations, medication changes, repeat interventions, and physiological measurements are recorded asynchronously and can change risk assessment over time. We propose an intervention-aware clinical world model that represents each patient with a structured latent state and evolves it through time-ordered post-intervention events. The model first encodes baseline imaging into a 3D spatial latent state. It then updates this state using procedural context, static covariates, elapsed time, and peri-event physiological embeddings. Follow-up imaging provides training-only supervision through a latent forecasting objective. We apply the framework to atrial fibrillation ablation. During the 90-day recovery window, irregular post-procedure records provide clinically meaningful evidence for long-term recurrence risk. In repeated internal cross-validation on DECAAF-II, our model achieves AUROC 0.756 and AUPRC 0.777 for recurrence prediction. It also achieves a scar-extent MAE of 2.971 percentage points without requiring follow-up MRI intensities at inference. The learned state supports recurrence-risk queries at different horizons and retrospective input editing of blanking-period records.

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