title: [Acute hypotensive episodes prediction based on non-linear chaotic analysis].
abstract: In intensive care units (ICU) , the occurrence of acute hypotensive episodes (AHE) is the key problem for the clinical research and it is meaningful for clinical care if we can use appropriate computational technologies to predict the AHE. In this study, based on the records of patients in ICU from the MIMIC II clinical data, the chaos signal analysis method was applied to the time series of mean artery pressure, and then the patient's Lyapunov exponent curve was drawn ultimately. The research showed that a curve mutation appeared before AHE symptoms took place. This is powerful and clear basis for AHE determination. It is also expected that this study may offer a reference to research of AHE theory and clinical application.
authors.forename: Dazhi
authors.initials: D
authors.lastname: Jiang
authors.forename: Liyu
authors.initials: L
authors.lastname: Li
authors.forename: Chenfeng
authors.initials: C
authors.lastname: Peng
mesh_terms: D006801:Humans; D007022:Hypotension / Q000175:diagnosis*; D007362:Intensive Care Units; D017711:Nonlinear Dynamics; D012984:Software