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This study describes a decision support system designed to automatically determine the ventilator settings in consideration of the ventilation data obtained from two different hospitals.
Data sources include an electronic patient information system (Quantitative Sentinel; GE-Marquette Medical Systems Inc, MilWIUSAe, WI, USA) that is interfaced to all bedside monitoring and ventilator devices that capture physiological and ventilation data.
The explicit computerized platform collects the data from the patient (SpO2, ETPCO2, ventilation data...) and processes the data to determine new ventilator settings in open- or closed-loop (output data).
Results are shown in Table 9. Duration of mechanical ventilation data showed divergent results among studies.
Data collection in the PDMS is mostly automated (e.g., blood pressure, ventilation data) by a direct link to the equipment.
Local guidelines, applicable during the survey and collection of ABG and ventilation data, instructed for lowest acceptable FiO2 levels.
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Although monitoring technologies can provide vast amounts of information before, during, and after liberation from mechanical ventilation, little data exists on how to maximally harness even routinely monitored, basic physiologic parameters.
Based on the ventilation scan data, the predicted FEV1.0 after right EPP combined was only 0.96 L/mm2, indicating that the patient could not tolerate right EPP combined with left upper lobe resection.
E, early tracheostomy; ICU, intensive care unit; L, late tracheostomy; LOS, length of stay; MV, mechanical ventilation; NA, data not available.
Although Sri Lanka being a tropical country is expected to have good indoor ventilation, limited data suggest that indoor air is more polluted than outdoor air [ 19, 20].
Since subjects became ambulatory upon recovering from surgery with the associated changes in PBPK parameters (eg. muscle blood flow, ventilation) only data out to 15 hours was used.
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