Statistical and prognostic analysis of dynamic changes of platelet count in ICU patients

Laboratory tests are a primary resource to diagnose patient's diseases. However, physicians often make decisions based on the available information, which commonly includes the last test results as a static picture and have limited perspective of the role of trends in commonly measured parameters in enhancing the diagnostic process. 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. Intensive care unit (ICU) patients need continuous monitoring, which commonly includes the assessment of several blood components. One of these components is the platelet count which is used in assessing blood clotting. However, platelet counts represent a dynamic equilibrium of many simultaneous processes including altered capillary permeability, inflammatory cascades, as well as the coagulation process. To characterize the value of dynamic changes in platelet counts we applied analytic methods to datasets of critically ill patients in (i) a homogeneous population of ICU cardiac surgery patients, where an observation appears to be predictive of patient's complications and mortality and (ii) a heterogeneous group of ICU patients to confirm the previous observation.