Predicting hypotension in perioperative and intensive care medicineSaugel, B., Kouz, K., Hoppe, P., Maheshwari, K. & Scheeren, T. W. L., Jun-2019, In : Best practice & research. Clinical anaesthesiology. 33, 2, p. 189-197 9 p.
Research output: Contribution to journal › Review article › Academic › peer-review
Blood pressure is the main determinant of organ perfusion. Hypotension is common in patients having surgery and in critically ill patients. The severity and duration of hypotension are associated with hypoperfusion and organ dysfunction. Hypotension is mostly treated reactively after low blood pressure values have already occurred. However, prediction of hypotension before it becomes clinically apparent would allow the clinician to treat hypotension pre-emptively, thereby reducing the severity and duration of hypotension. Hypotension cannowbepredictedminutes before it actually occurs from the blood pressure waveform using machine-learning algorithms that can be trained to detect subtle changes in cardiovascular dynamics preceding clinically apparent hypotension. However, analyzing the complex cardiovascular system is a challenge because cardiovascular physiology is highly interdependent, works within complicated networks, and is influenced by compensatory mechanisms. Improved hemodynamic data collection and integration will be a key to improve current models and develop new hypotension prediction models. (C) 2019 Elsevier Ltd. All rights reserved.
|Number of pages||9|
|Journal||Best practice & research. Clinical anaesthesiology|
|Publication status||Published - Jun-2019|
- artificial intelligence, machine learning, blood pressure, cardiovascular dynamics, hemodynamic monitoring, hypotension prediction index, MEAN ARTERIAL-PRESSURE, ACUTE KIDNEY INJURY, INTRAOPERATIVE HYPOTENSION, NONCARDIAC SURGERY, BAROREFLEX SENSITIVITY, MYOCARDIAL INJURY, INSTABILITY, DEFINITION, MORTALITY, ASSOCIATION