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