In this paper we consider how the use of Kaleidomaps can facilitate our understanding and interpretation of large complex multivariate medical datasets relating to cardiovascular function in critical care medicine. Kaleidomaps are a new technique for the visualization of multivariate time-series data. They build upon the classic cascade plot and use the curvature of a line to enhance the detection of periodic patterns within multivariate dualperiodicity datasets. Kaleidomaps keep user interaction to a minimum, facilitating the rapid identification of periodic patterns not only within their own variants but also across many different sets of the variants. By linking this technique with traditional line graphs and signal processing techniques, we are able to provide medical experts with a set of visualization tools that permit the combination of medical datasets in their raw form and also with the results of mathematical analysis.