Using physiological models and decision theory for selecting appropriate ventilator settings.
OBJECTIVE
To present a decision support system for optimising mechanical ventilation in patients residing in the intensive care unit.


METHODS
Mathematical models of oxygen transport, carbon dioxide transport and lung mechanics are combined with penalty functions describing clinical preference toward the goals and side-effects of mechanical ventilation in a decision theoretic approach. Penalties are quantified for risk of lung barotrauma, acidosis or alkalosis, oxygen toxicity or absorption atelectasis, and hypoxaemia.


RESULTS
The system is presented with an example of its use in a post-surgical patient. The mathematical models describe the patient's data, and the system suggests an optimal ventilator strategy in line with clinical practice.


CONCLUSIONS
The system illustrates how mathematical models combined with decision theory can aid in the difficult compromises necessary when deciding on ventilator settings.
Rees
S E
SE
Center for Model-Based Medical Decision Support Systems, Aalborg University, Niels Jernes vej 14, 4-313, DK-9220, Aalborg East, Denmark. sr@hst.aau.dk
Allerød
C
C
Murley
D
D
Zhao
Y
Y
Smith
B W
BW
Kjaergaard
S
S
Thorgaard
P
P
Andreassen
S
S
D002245:Carbon Dioxide / Q000502:physiology; D003199:Computer Systems; D003662:Decision Theory; D006801:Humans; D008433:Mathematics; D008954:Models, Biological; D008991:Monitoring, Physiologic; D010100:Oxygen / Q000502:physiology; D012121:Respiration, Artificial / Q000379:methods* / Q000706:statistics & numerical data; D015656:Respiratory Mechanics
D002245:Carbon Dioxide; D010100:Oxygen