ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Statistical Analysis to Predict Clinical Outcomes with Complex Physiologic Data

4 September 2018, 14:10 – 14:30


Submitted by
Monica Puertas
Monica Puertas (Instituto para la Calidad - Pontificia Universidad Católica del Peru), Jose Zayas-Castro (University of South Florida), Peter Fabri (University of South Florida)
The assessment and monitoring of the circulatory system is essential for patients in intensive care units (ICU). One component of this system is the platelet count which is used in assessing blood clotting. However platelet counts represent a dynamic equilibrium of many simultaneous processes. To characterize the value of dynamic changes in platelet counts we applied analytic methods to datasets of critically ill patients in (i) a population of ICU cardiac surgery patients and (ii) a heterogeneous group of ICU patients The objective is to develop a methodology to predict patient outcomes with the first dataset, then redefine the methodology for a more heterogeneous and complex dataset and finally extend it to other clinical parameters. By providing a dynamic patient profile the diagnosis could be more accurate and, as a consequence, physicians could anticipate changes in recovery trajectory and prescribe interventions more effectively, leading to a possible healthcare cost reduction and patient care improvement.
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