Thursday December 4, 2008
Artificial intelligence in ICU !!
A very interesting study - "An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study" - is just published at ccforum.com
An alternative way of personalizing medicine in the ICU on a realtime basis by using information derived from the application of artificial intelligence on a high resolution database, is proposed. Calculation of maintenance fluid requirement at the height of systemic inflammatory response was selected to investigate the feasibility of this approach.
The Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) is a database of patients admitted to the Beth Israel Deaconess Medical Center ICU.
METHOD: Patients who were on vasopressors for more than 6 hours during the first 24 hours of admission were identified from the database. Demographic and physiologic variables that might affect fluid requirement or reflect the intravascular volume during the first 24 hours in the ICU were extracted from the database. The outcome to be predicted is the total amount of fluid given during the second 24 hours in the ICU, including all the fluid boluses administered.
Investigators represented the variables by learning a Bayesian network from the underlying data. Using ten-fold cross-validation repeated 100 times, the accuracy of the model in predicting the outcome is 77.8%. The network generated has a threshold Bayes factor of 7 representing the posterior probability of the model given the observed data. This Bayes factor translates into p < .05 assuming Gaussian distribution of the variables.
Conclusions: Based on the model, the probability that a patient will require a certain range of fluid on day 2 can be predicted. In the presence of a larger database, analysis may be limited to patients with identical clinical presentation, demographic factors, co-morbidities, current physiologic data, and those who did not develop complications as a result of fluid administration. By better predicting maintenance fluid requirements based on the previous day's physiologic variables, one might be able to prevent hypotensive episodes requiring fluid boluses during the course of the following day.
Reference: click to get article
An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study - Critical Care 2008, 12:R151 - pdf file
