The Role of Physiological Models in Critiquing Mechanical Ventilation Treatments
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Transcript of The Role of Physiological Models in Critiquing Mechanical Ventilation Treatments
The Role of Physiological Models in Critiquing Mechanical Ventilation Treatments
ByFleur T. Tehrani, PhD, PE
Professor of Electrical EngineeringCalifornia State University, Fullerton, CA, USA
AndSoraya Abbasi, MD
Research Director, CHOP Newborn Care at Pennsylvania HospitalAssociate Professor of Pediatrics, University of Pennsylvania School of
Medicine, Philadelphia, PA, USA
Pennsylvania Hospital
Pennsylvania Hospital
Pennsylvania Hospital
Rising Preterm Delivery Rate
62,000 VLBW infants < 1500 gram
30,000 ELBW infants < 1000 grams are born annually in US
66 to 88% of ELBW infants survive
Respiratory Distress Syndrome Chronic Lung Disease
Why Decision Support Systems for Mechanical Ventilation?
Assisted ventilation may lead to adverse consequences including lung injury
Therefore clinicians will often select the lowest possible ventilatory support to maintain desired blood gases
The accuracy of their choice remains unknown for minutes to hours until the next blood gases is obtained
The ventilator setting is often readjusted for over or under estimation of the applied ventilatory support
Why Decision Support Systems for Mechanical Ventilation?
• Most ventilation modes are still open loop controlled
• Ventilation parameters need to be set carefully by considering many features of advanced ventilators as well as rapidly changing patient conditions
• Decision Support and Critiquing systems can be used as aides to clinicians to set ventilation parameters and avoid medical errors
What Kind of Critiquing System Was Used in this Study?
• The Critiquing system of this study is based on a mathematical model of neonatal respiratory system*
• The respiratory controller of the model was replaced by a positive pressure mechanical ventilator to simulate the effects of different ventilation parameters on the patient’s blood gases
*Tehrani FT. Mathematical Analysis and Computer Simulation of the Respiratory System in the Newborn Infant. IEEE Transactions on Biomedical Engineering 1993; 40(5): 475-481
The block diagram of the model-based system
The model-based system was used to predict blood gases for an infant on IMV
ventilation in a previous study*
In two simulation experiments, the critiquing system simulated the effects of setting ventilation parameters according to the physician’s recommendations and according to the recommendations of another computerized system called FLEX (which is different from the model-based system proposed in this study)
* Tehrani FT, Abbasi S. Evaluation of a Computerized System for Mechanical
Ventilation of Infants. J of Clinical Monitoring and Computing 2009; 23: 93-104.
Simulation results of the model-based system by using the clinician’s set of ventilatory parameters for infant
#5 in Reference #4
Simulation results of the model-based system by using the ventilation parameters recommended by a computerized
system called FLEX, for infant #5 in Reference #4
The Trends of the results predicted by the model-
based system were confirmed by the
measurements reported in Reference #4
Summary
Model-based critiquing system can analyze the input rapidly and:
Critiques the recommended support level
Predict the resultant blood gases for a selected support level
Prevents the use of potentially lung damaging ventilatory support
Prevents potential tissue damage from out of safe range blood gases and blood pH
CONCLUSION
Model-based critiquing systems have the potential to be used as a helpful computational tools to
determine better ventilatory treatment.
Thank you
BW:528 gmGA: 23 5/7 wks
Therefore, by predicting different treatment outcomes based on patient’s blood gases, the model-based system
could provide greater insight for clinicians and aid in making a more
informed decision about the patient’s ventilation treatment at the bedside.
Summary