Predicting Adverse Events: Detecting Myocardial Damage in Intensive Care Unit (ICU) Patients

Derek Sleeman, Laura Elizabeth Moss, Malcolm Sim, John Kinsella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Myocardial damage is known to occur relatively frequently, and
although it is not often fatal it results in the patient staying in the
ICU for significantly longer. Thus it is important for clinicians to
detect these events. Confirmation of myocardial damage is by a
biomarker (troponin), but these tests are only done at fixed timepoints.
Consequently it is desirable for doctors, and support systems,
to detect myocardial damage from the standard parameters
collected for ICU patients. We have undertaken a study with several
ICU consultants to determine the conditions which generally
precede a myocardial-damaging event. In fact, these knowledge
acquisition sessions produced a complex model which we have
realized as 2 interacting modules. Subsequently, we compared
this model’s predictions against the original datasets; the model
when run against the test dataset resulted in a relatively high True
Positive (TP) rate (75.8%). The implications of these analyses are
discussed, as are a number of planned follow-up studies.
Original languageEnglish
Title of host publicationKCAP 2011 Conference Proceedings
Place of PublicationNew York
PublisherACM Press
Pages73-79
Number of pages7
ISBN (Electronic)978-1-4503-0396-5
Publication statusPublished - 2011

Keywords

  • Knowledge Acquisition
  • Modelling of Expertize
  • Event Prediction
  • Intensive Care Unit
  • Myocardial Damage.

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