Sign-Constrained Intervention Effects for Domain-Generalizable ICU World Models

Predicting how a patient's vital signs will respond to an intervention is a central question in intensive care. World models can do so by learning dynamics as a function of prior actions, so that a trajectory can be unrolled under any chosen treatment course. However, such models tend to be brittle for dosing practices outside of those seen in training data. Clinicians choose drug dosages based on the patient's state, so the association a model learns between dose and outcome runs opposite to the drug's effect, which does not generalize well to out-of-distribution (OOD) dosing practices. However, pharmacological information already provides the effects on vital signs of different drugs, which is invariant to dosing practice distribution shifts. To resolve the OOD sensitivity issues of current ICU world models, we introduce **PhysioWorld**, a world model that isolates an intervention's effect by evaluating a forward pass twice: once under the recorded doses, and once with those doses set to zero. The difference is then projected onto the set of pharmacologically admissible *effect directions* stated by a corpus of 70 (drug, channel, sign) rules over 28 drugs, leaving the magnitude, which no source states, to be learned from data. Across five distribution-shift parameters over cohorts from three intensive-care databases, and against forecasters, counterfactual treatment-effect models, invariance objectives and two weaker placements of the same knowledge, PhysioWorld attains the lowest OOD RMSE in every setting, improving on the strongest baseline by 8–12%, while maintaining the in-distribution error of an unconstrained backbone's. Reversing the pharmacologic effect directions degrades accuracy below the unconstrained backbone, and directions estimated from the training records recover almost no performance gain, indicating that the improvement derives from the content of the pharmacologic knowledge rather than from the presence of a constraint. Nothing in the construction is specific to intensive care: it applies wherever the sign of an effect is known in advance and its magnitude is confounded by how the treatment was assigned.