Bioengineering is the application of modern technology to the biological and medical disciplines. An important subset of the discipline that has had a large impact on anesthesiology in particular is bioinformatics, which combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret biological data. The field has improved anesthesia care by helping anesthesiologists to monitor and treat patients more efficiently. The three principal areas where bioinformatics contributes to anesthesia are: information gathering, information processing, and information abstraction [1].
In terms of information abstraction, two conceptual approaches from bioengineering have been applied to the administration of anesthesia, closed-loop control and the use of mathematical models. The basic principle of closed-loop systems is that there are particular goals set, and when deviations from these goals are sensed by the system, it triggers a response to counter that deviation [1]. The very first application of this bioengineering principle for use in anesthesia was implemented after it was observed that activity of the electroencephalogram (EEG) of a patient was a valid indicator of “depth of anesthesia.” Thus, this metric was used in a closed-loop system to regulate the amount of anesthetics the patient was given through surgery [2]. In open heart surgeries, a closed-loop system can be created by using a continuous cardiac output measurement to control the concentration of inhaled anesthetic [1], and, in post-surgery care, a computer can monitor a patient’s variables and administer drugs intravenously when needed.
Another form of information abstraction, mathematical models, have helped anesthesia by increasing understanding of the science behind it [1]. These models, created by bioengineers and bioinformaticians, have led physicians to discover important facts like how the speed of drug uptake in different compartments depends on factors like body perfusion and solubility of the anesthetic agent [1], and, recently, a bioinformatics analysis of gene profiles discovered the pathway involved in isoflurane-induced anesthesia [3]. Computer simulations of mathematical models are being used to teach anesthesia today [1] and are very useful in collecting and processing data to discover patterns that could lead to important breakthroughs and improve future anesthesia care.
Another way that that bioengineering has helped is in information gathering. They have engineered transducers that allow physicians to take more accurate measurements from patients, and to also take measurements of factors that were previously unable to be measured. For example, before the invention of ultrasonic devices, blood flow could only be measured by dangerously exposing an artery but is now safe and simple for physicians to measure [1]. Machines like the EEG were also invented by bioengineers and are used in anesthesia to gather information about the patient’s consciousness level [1]. Without accurate and effective transducers, the closed-loop systems used in anesthesia would not be possible.
In the information processing stage of the closed-loop systems, computer science is most prominently utilized in order to increase the speed of care. The principle behind this is that any rule that physicians may use to administer care can be stated logically and encoded into a computer so that it can then execute that rule, independent of human input [1]. For example, when an anesthesiologist sees the heart rate of a patient increase during surgery, they typically increase the amount of anesthesia being given to decrease it to a steady rate. Encoding this logic into a computer so that when it senses the increase, it administers more drugs, is quicker and far more efficient than what a human can do.
In summary, bioengineering and bioinformatics have had profound effects on how anesthesia is administered by enabling closed-looped systems through information gathering, processing, and abstraction.
References
1. Murphy, T. W. and Mazzia, V. D. Bioengineering and anesthesia. 1969 Mar; 45(3): 301–307
2. Faulconer, A. and Bickford, R. G. Electroencephalography in Anesthesiology. Springfield, Ill., Thomas, 1960.
3. Wang, H., Jin, Y. &
Dai, J. Biological processes and pathway changes in isoflurane-induced
anesthesia revealed by bioinformatics analysis of gene expression profiles. J
Anesth 29, 912–919 (2015) doi:10.1007/s00540-015-2049-1
