Stratifying mortality risk in hypotension using outcome-oriented clustering of vital sign trajectories

The prognostic significance of early vital sign trajectories in critically ill patients with hypotension remains unclear. This study applied an outcome-oriented two-step clustering model to characterize vital sign trajectories within 12 h of symptom onset, with the optimal window determined by weight learning, to improve mortality risk stratification. Patients (mean arterial pressure ≤65 mmHg or on vasopressors) were from the MIMIC-IV (development), eICU, and Xiangya multi-ICU (validation) databases. Three clusters with progressively increasing mortality were identified. Cluster 3 vs. 1 had the highest adjusted hazard ratio (2.30, 95%CI [2.04, 2.58]). The respiratory rate trajectory within the initial 2 h was the primary mortality discriminator. External validation demonstrated the model's generalizability, with hazard ratios (eICU, 2.96, 95% CI: 2.70, 3.23) and (Xiangya, 2.28, 95% CI: 1.93, 2.71) for cluster 3 vs. 1, respectively. This study demonstrated that hypotension can be risk-stratified by respiratory rate trajectories, with elevated breaths linked to higher mortality.