| الوصف: |
Intraoperative hypotension is associated with myocardial injury, acute kidney injury, and death. In routine practice, specific causes of intraoperative hypotension are often unclear. A more detailed understanding of underlying haemodynamic alterations of intraoperative hypotension may identify specific treatments. We thus aimed to use machine learning - specifically, hierarchical clustering - to identify underlying haemodynamic alterations causing intraoperative hypotension in major abdominal surgery patients. Specifically, we tested the hypothesis that there are distinct endotypes of intraoperative hypotension, which may help refine therapeutic interventions.We conducted a secondary analysis of intraoperative haemodynamic measurements from a prospective observational study in 100 patients who had major abdominal surgery under general anaesthesia. We used stroke volume index, heart rate, cardiac index, systemic vascular resistance index, and pulse pressure variation measurements. Intraoperative hypotension was defined as any mean arterial pressure ≤65 mm Hg or a mean arterial pressure between 66 and 75 mm Hg requiring a norepinephrine infusion rate exceeding 0.1 μg kgA total of 615 episodes of intraoperative hypotension occurred in 82 patients (46 [56%] female; median age: 64 [57, 73] yr) who had surgery of a median duration of 270 (195, 335) min. Hierarchical clustering revealed six distinct intraoperative hypotension endotypes. Based on their clinical characteristics, we labelled these endotypes as (1) myocardial depression, (2) bradycardia, (3) vasodilation with cardiac index increase, (4) vasodilation without cardiac index increase, (5) hypovolaemia, and (6) mixed type.Hierarchical clustering identified six endotypes of intraoperative hypotension. If validated, considering these intraoperative hypotension endotypes may enable causal treatment of intraoperative hypotension. |