Tracking progression of patient state of health in critical care using inferred shared dynamics in physiological time series
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Author(s)
Lehman, Li-wei H.
Adams, Ryan P.
Moody, George B.
Malhotra, Atul
Mark, Roger Greenwood
Nemati, Shamim, 1980-
Date Issued
July 2013
Journal
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Lehman, Li-wei H., Shamim Nemati, Ryan P. Adams, George Moody, Atul Malhotra, and Roger G. Mark. “Tracking Progression of Patient State of Health in Critical Care Using Inferred Shared Dynamics in Physiological Time Series.” 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (July 2013), Osaka, Japan, 3-7 July, 2013.
Version
Author's final manuscript
Abstract
Physiologic systems generate complex dynamics in their output signals that reflect the changing state of the underlying control systems. In this work, we used a switching vector autoregressive (switching VAR) framework to systematically learn and identify a collection of vital sign dynamics, which can possibly be recurrent within the same patient and shared across the entire cohort. We show that these dynamical behaviors can be used to characterize and elucidate the progression of patients' states of health over time. Using the mean arterial blood pressure time series of 337 ICU patients during the first 24 hours of their ICU stays, we demonstrated that the learned dynamics from as early as the first 8 hours of patients' ICU stays can achieve similar hospital mortality prediction performance as the well-known SAPS-I acuity scores, suggesting that the discovered latent dynamics structure may yield more timely insights into the progression of a patient's state of health than the traditional snapshot-based acuity scores.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. School of Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/EMBC.2013.6611187
