A Digital Twin for Individualized Treatment Effects of Non-Invasive Respiratory Support Strategies (DINIRS)
Objective: Choosing between noninvasive respiratory support (NIRS) and invasive mechanical ventilation (IMV) for acute respiratory failure is a time-sensitive decision. Although guidelines provide population-level guidance, it remains unclear who benefits more from NIRS than IMV. The standard outcome, ventilator-free days at 28 days (VFD-28), scores death and prolonged ventilation equally, and current estimators do not distinguish between them. We developed and validated a censoring-aware Digital Twin framework for Individualized Treatment Effects of Non-Invasive Respiratory Support (DINIRS) to estimate individualized treatment effects (ITEs) that capture both mortality and ventilation duration. Materials and Methods: We emulated a target trial in 5,336 MIMIC-IV patients and trained DINIRS on 23 baseline clinical variables measured during the first 24 ICU hours. A transformer encoder with a survival attention gate decomposed VFD-28 into survival probability and conditional ventilation duration. A cross-fitted, doubly robust learner estimated ITEs. We externally validated DINIRS in 2,540 patients from the multi-site eICU-CRD dataset without retraining. Results: The DINIRS policy achieved a mean benefit of 2.07 ventilator-free days per patient (207 per 100 patients) compared with observed practice. Predicted NIRS benefit was higher among patients with less organ dysfunction (88.4% versus 49.0%) and persisted across hypoxemia severity. External validation reproduced this pattern. Discussion: The NIRS benefit stemmed from shorter ventilation among survivors rather than from reduced mortality, indicating that avoiding intubation-associated complications was the primary mechanism. Conclusion: Prospective validation is needed before these estimates inform treatment decisions. The decomposition framework can be extended beyond respiratory support to any zero-inflated composite outcome.