Fig. 5: Case studies demonstrating clinical application of the HM-TARGET framework in patients with ischaemic stroke.

This figure illustrates the application of the HM-TARGET framework in two patients with ischaemic stroke—one who survived and one who died. Both patients were selected from the MIMIC-IV dataset and survived and remained in the ICU for at least 48 h following ICU admission. a Summary of key clinical characteristics for both patients. b Two-dimensional dynamic colour contour maps of cumulative survival probability, depicting the relationship between actual HR and SBP values and model-predicted optimal targets over time. c Individual trajectories of cumulative survival probability during the ICU stay. For panels b and c, the actual HR, SBP, and GCS values, as well as the model-predicted HR and SBP targets, correspond to the six sampled time points (6, 12, 18, 24, 30, and 36 hours post-ICU admission). d, e Time-series plots showing actual versus predicted HR and SBP targets, along with GCS scores, for the deceased and surviving patients, respectively. In panels d and e, the values correspond to hourly measurements, with median values used when multiple data points were recorded within a single hour. The deceased patient’s SBP values consistently fell below the model-predicted target range, while the surviving patient’s SBP remained closely aligned with the predicted targets across the ICU course. These case studies exemplify the potential clinical relevance and feasibility of applying the HM-TARGET framework to guide real-time, personalised haemodynamic management in critical care. Source data are provided as a Source Data file. HM-TARGET Haemodynamic Management by Time-Adaptive, BMI body mass index, CCI Charlson Comorbidity Index, SOFA Sequential Organ Failure Assessment, HR heart rate, SBP systolic blood pressure, ICU intensive care unit, GCS Glasgow Coma Scale.