Background: Parameters determining carbon monoxide (CO) concentrations produced by anesthetic breakdown have not been adequately studied in clinical situations. The authors hypothesized that these data will identify modifiable risk factors.
Methods: Carbon monoxide concentrations were measured when partially desiccated barium hydroxide lime was reacted with isoflurane (1.5%) and desflurane (7.5%) in a Draeger Narkomed 2 anesthesia machine with a latex breathing bag substituting for a patient. Additional experiments determined the effects of carbon dioxide (0 or 350 ml/min), fresh gas flow rates (1 or 4 l/min), minute ventilation (6 or 18 l/min), or absorbent quantity (1 or 2 canisters). End-tidal anesthetic concentrations were adjusted according to a monochromatic infrared monitor.
Results: Desflurane produced approximately 20 times more CO than isoflurane when completely dried absorbents were used. Peak CO concentrations approached 100,000 ppm with desflurane. Traces of water remaining after a 66-h drying time (one weekend) markedly reduced the generation of CO compared with 2 weeks of drying. Reducing the quantity of desiccated absorbent by 50% reduced the total CO production by 40% in the first hour. Increasing the fresh gas flow rate from 1 to 4 l/min increased CO production by 67% in the first hour but simultaneously decreased average inspiratory concentrations by 53%. Carbon dioxide decreased CO production by 12% in completely desiccated absorbents.
Conclusion: Anesthetic identity, fresh gas flow rates, absorbent quantity, and water content are the most important factors determining patient exposures. Minute ventilation and carbon dioxide production by the patient are relatively unimportant.
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http://dx.doi.org/10.1097/00000542-200103000-00015 | DOI Listing |
Acc Chem Res
January 2025
The Department of Chemistry, State University of New York at Binghamton, Binghamton, New York 13902, United States.
ConspectusIn the search for efficient and selective electrocatalysts capable of converting greenhouse gases to value-added products, enzymes found in naturally existing bacteria provide the basis for most approaches toward electrocatalyst design. Ni,Fe-carbon monoxide dehydrogenase (Ni,Fe-CODH) is one such enzyme, with a nickel-iron-sulfur cluster named the C-cluster, where CO binds and is converted to CO at high rates near the thermodynamic potential. In this Account, we divide the enzyme's catalytic contributions into three categories based on location and function.
View Article and Find Full Text PDFBackground: Several modifiable risk factors for dementia and related neurodegenerative diseases have been identified including education level, socio-economic status, and environmental exposures - however, how these population-level risks relate to individual risk remains elusive. To address this, we assess over 450 potential risk factors in one deeply clinically and demographically phenotyped cohort using random forest classifiers to determine predictive markers of poor cognitive function. This study aims to understand early risk factors for dementia by identifying predictors of poor cognitive performance amongst a comprehensive battery of imaging, blood, atmospheric pollutant and socio-economic measures.
View Article and Find Full Text PDFBackground: Household air pollution is a major contributor to cardiovascular disease burden in women in Sub-Saharan Africa. However, little is known about exposures during pregnancy or the effect of clean cooking interventions on postpartum blood pressure trajectories.
Methods: The Ghana Randomized Air Pollution and Health Study (GRAPHS) randomized 1414 non-smoking women in the first and second trimesters to liquefied petroleum gas (LPG) or improved biomass stoves - vs control (traditional three-stone open fire).
ACS Omega
January 2025
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China.
It is of great significance to realize the accurate prediction of the key output response of the chemical synthetic ammonia process for optimizing system performance and operation monitoring. Because many key intermediate variables of complex systems are difficult to measure comprehensively, there are great difficulties and errors in mechanism analysis and identification modeling techniques. Based on random forest (RF) variable selection, a deep neural network combining temporal convolutional network (TCN) and transformer is proposed to predict the output variables of the synthetic ammonia process.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Mechanical Engineering, Addis Ababa Science and Technology University, Addis Ababa, 16417, Ethiopia.
Many approaches have been implemented in order to reduce the emissions of particular pollutants without compromising engine performance. Cotton and castor mixed seed oil was chosen for the current study due to their distinct fatty acid composition and potential as a feedstock for bio-additives. Three fuel samples-99 % diesel and 1 % blended fuel (cottonseed oil + castor seed oil), 99.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!