The design and implementation of a ventilator-management advisor
Artificial Intelligence in Medicine
The intelligent ventilator project: application of physiological models in decision support
AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
Computer Methods and Programs in Biomedicine
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Selecting appropriate ventilator settings decreases the risk of ventilator-induced lung injury. A decision support system (DSS) has been developed based on physiological models, which can advise on setting of tidal volume (Vt), respiratory frequency (f) and fraction of inspired oxygen (FiO"2). The aim of this study is to assess the feasibility of the DSS by comparing its advice with the values used in clinical practice. Data from 20 patients following uncomplicated coronary artery bypass grafting (CABG) with cardiopulmonary bypass was used to test the DSS. Ventilator settings suggested by the DSS were compared to the settings selected by the clinician. When compared to the clinician the DSS suggested: lowering FiO"2 (by median 7%, range 2-17%) at high SpO"2 and increasing FiO"2 (by median 2%, range 1-5%) at low SpO"2; lowering ventilation volume (by median 0.57lmin^-^1, range 0.2-1.1lmin^-^1) at high pHa and increasing ventilation volume (by median 0.4lmin^-^1, range 0.1-0.9lmin^-^1) at low pHa. Suggested changes in ventilation volume were such that simulated values of PIP were @?22.9cmH"2O and respiratory frequency @?18breathsmin^-^1. In all cases, computer suggested values of FiO"2, Vt or f were consistent with maintaining sufficient oxygenation, normalising pH and obtaining low values of PIP.