title: Three-Dimensional Segmented Poincaré Plot Analyses SPPA3 Investigates Cardiovascular and Cardiorespiratory Couplings in Hypertensive Pregnancy Disorders.
abstract: Hypertensive pregnancy disorders affect 6-8% of gestations representing the most common complication of pregnancy for both mother and fetus. The aim of this study was to introduce a new three-dimensional coupling analysis methods - the three-dimensional segmented Poincaré plot analyses (SPPA3) - to establish an effective approach for the detection of hypertensive pregnancy disorders and especially pre-eclampsia (PE). A cubic box model representing the three-dimensional phase space is subdivided into 12 × 12 × 12 equal predefined cubelets according to the range of the SD of each investigated signal. Additionally, we investigated the influence of rotating the cloud of points and the size of the cubelets (adapted or predefined). All single probabilities of occurring points in a specific cubelet related to the total number of points are calculated. In this study, 10 healthy non-pregnant women, 66 healthy pregnant women, and 56 hypertensive pregnant women (chronic hypertension, pregnancy-induced hypertension, and PE) were investigated. From all subjects, 30 min of beat-to-beat intervals (BBI), respiration (RESP), non-invasive systolic (SBP), and diastolic blood pressure (DBP) were continuously recorded and analyzed. Non-rotated adapted SPPA3 discriminated best between hypertensive pregnancy disorders and PE concerning coupling analysis of two or three different systems (BBI, DBP, RESP and BBI, SBP, DBP) reaching an accuracy of up to 82.9%. This could be increased to an accuracy of up to 91.2% applying multivariate analysis differentiating between all pregnant women and PE. In conclusion, SPPA3 could be a useful method for enhanced risk stratification in pregnant women.
authors.affiliation: Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena , Jena , Germany.
authors.forename: Claudia
authors.initials: C
authors.lastname: Fischer
authors.affiliation: Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena , Jena , Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Voss
keywords: Poincaré plot analysis; blood pressure variability; heart rate variability; hypertensive pregnancy disorders; multivariate analysis; non-linear dynamics; respiration; risk stratification