Feasibility, safety, and economic consequences of using minimal flow anaesthesia by Maquet FLOW-i equipped with automated gas control.
Yusuf Ziya ColakHüseyin I ToprakPublished in: Scientific reports (2021)
Low fresh gas flow rates are recommended because of their benefits, however, its use is limited due to associated risks. The main purpose of this study was to investigate whether 300 mL of fresh gas flow that practised with automated gas control mode is applicable and safe. The second aim is to show that automated mode can provide economic benefits. Sixty hepatectomy cases who suitable criterias were included to cohort study in three groups as prospective, sequential, observational. An operating room were allocated only for this study. 300 mL fresh gas flow with automated mode (groupA3), 600 mL fresh gas flow with automated mode (groupA6) and, 600 mL fresh gas flow with manually (groupM6) was applied. Patients' respiratory, hemodynamic parameters (safety), number of setting changes, O2 concentration in the flowmeter that maintained FiO2:0.4 during the low flow anaesthesia (feasibility) and comsumption data of anaesthetic agent and CO2 absorber (economical) were collected and compared. p < 0.05 was accepted as statistical significance level. No significant differences were detected between the groups in terms of demographic data and duration of operation. Safety datas (hemodynamic, respiratory, and tissue perfusion parameters) were within normal limits in all patients. O2 concentration in the flowmeter that maintained FiO2:0.4 was statistically higher in groupA3 (92%) than other groups (p < 0.001) but it was still within applicable limits (below the 100%). Number of setting changes was statistically higher in groupM6 than other groups (p < 0.001). The anaesthetic agent consumption was statistically less in groupA3 (p = 0.018). We performed fresh gas flow of 300 mL by automated mode without deviating from the safety limits and reduced the consumption of anaesthetic agent. We were able to maintain FiO2:0.4 in hepatectomies without much setting changes, and we think that the automated mode is better in terms of ease of practise.
Keyphrases
- deep learning
- high throughput
- machine learning
- room temperature
- end stage renal disease
- chronic kidney disease
- ejection fraction
- carbon dioxide
- newly diagnosed
- computed tomography
- cross sectional
- magnetic resonance imaging
- prognostic factors
- data analysis
- big data
- single cell
- climate change
- patient reported outcomes