A knowledge-based system for assisted ventilation of patients in intensive care units

Abstract

The procedure for weaning a patient with respiratory insufficiency from mechanical ventilation may be complex and requires expertise obtained by long clinical practice. We designed a knowledge-based system for the management of patients receiving respiratory support and implemented a weaning procedure. The system is intended for patients whose spontaneous respiratory activity is assisted by a Hamilton Veolar ventilator delivering a positive pressure plateau during inspiration (Pressure Support Ventilation mode). Our closed-loop real-time system running on a Personal Computer continuously adapts the assistance provided by the ventilator to the patient's evolution, and indicates when the patient can be withdrawn from the ventilator. Three parameters are used to appreciate the 'respiratory comfort' of the patient: breathing frequency, which we consider the most informative index, tidal volume and end-tidal CO2 pressure. A preliminary study of 19 patients was performed to evaluate the ability of our system to adapt the assistance to the patient's needs, with the main objective of facilitating weaning by gradually lowering the level of assistance. In 10 of these patients, considered as good candidates for weaning on the strength of objective criteria, the system maintained the breathing pattern in a zone of comfort for 95% of the period of assisted ventilation and stated that they were 'weanable'. This was consistent with the clinical evolution of all 10 patients. These results show that such a system can provide effective management for mechanically ventilated patients.