干预粒度至关重要：临床世界模型反事实模拟中的连贯治疗捆绑
Intervention Granularity Matters: Coherent Treatment Bundles in Counterfactual Simulation with Clinical World Models
- Duke University（杜克大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究通过临床世界模型反事实模拟，发现干预粒度影响模型响应：完整治疗捆绑比单组件编辑更显著改变预测状态，为反事实治疗模拟提供更可靠基础。
AI中文摘要：
使用临床世界模型进行反事实模拟，意味着固定患者病史、改变治疗方式，并读取预测的响应。这样做需要确定什么算作一次干预。在临床环境中，干预被记录为捆绑：对MIMIC-IV中945,707个患者小时的共现审计显示，组件组（如透析回路的每个参数）从不分开出现，因此单独更改一个组件的编辑描述的是数据中从未出现过的一个小时。我们假设干预编辑的粒度会改变世界模型的响应方式，并使用Clin-JEPA（一种以每小时治疗文本为条件的患者轨迹潜在世界模型）对此进行测试。在1,019次有记录的侵入性通气开始时，我们保持患者病史和其他治疗不变，比较编辑一个通气设置与编辑为最近轨迹最相似的真实患者记录的完整配置。完整的捆绑将预测的下一状态移动得比任何单一设置都远，在所有五个设置中一致如此，并且在考虑每次编辑对模型输入改变的程度后，这种差异仍然存在。因此，干预粒度实质性地影响临床世界模型的响应：单组件编辑可能低估治疗敏感性，而捆绑感知编辑可能为反事实治疗模拟提供更有依据的基础。
英文摘要：
Counterfactual simulation with a clinical world model means fixing a patient's history, changing the treatment, and reading off the predicted response. Doing so requires deciding what counts as one intervention. In clinical settings, interventions are documented as bundles: a co-occurrence audit of 945,707 patient-hours from MIMIC-IV shows groups of components, such as every parameter of a dialysis circuit, that never appear apart, so an edit that changes one component on its own describes an hour that never occurs in the data. We hypothesize that the granularity at which an intervention is edited changes how a world model responds, and test this with Clin-JEPA, a latent world model of patient trajectories conditioned on hourly treatment text. At 1,019 documented onsets of invasive ventilation, we keep the patient's history and other treatments fixed and compare editing one ventilator setting with editing the complete configuration recorded for a real patient with the most similar recent trajectory. The complete bundle moves the predicted next state further than any single setting, consistently across all five settings, and the difference remains after accounting for how much each edit changes the model's input. Intervention granularity therefore materially affects the response of a clinical world model: single-component edits may understate treatment sensitivity, and bundle-aware editing may offer a better-supported basis for counterfactual treatment simulation.
