Computing in Anesthesia and Intensive Care edited by Omar Prakash.

There is a tendency of an increasing number of signals and derived variables to be incorporated in the monitoring of patients during anesthesia and in intensive care units. The addition of new signals hardly ever leads to thedeletion of other signals. This is probably based on a feeling of insecurit...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Prakash, Omar (Editor)
Format: eBook
Language:English
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 1983.
Edition:1st ed. 1983.
Series:Developments in Critical Care Medicine and Anaesthesiology, 5
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

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505 0 |a Computer operating systems for patient monitoring -- On the use of computers in the practice of anaesthesia -- Computerized data acquisition and display in anesthesia -- Microcomputer based automatic capture of signals from non-invasive instruments -- Physiologic monitoring of critically ill patients: computerized data acquisition, outcome prediction, organisation of therapy and prospective clinical trials -- Set up and results ICU database -- An interactive information system for anaesthesia -- Automated analysis of the esophageal accelerogram as a minimally invasive monitor of manifest contractile state -- Information transfer from operating room to ICU 10 -- Energy metabolism -- Gas distribution and ventilation-perfusion relationships during anaesthesia and in acute respiratory failure -- Continuous monitoring of intrathoracic fluid -- The potential of computer modelling techniques in intensive care medicine -- An interactive program for intravenous drug infusion management -- Computer assisted learning in anaesthesiology -- Teaching with “ATTENDING”: Tutorial use of an expert system -- Introductory courses in computing for anaesthetists -- The use of computer-generated numbers in interpreting the EEG -- Automatic EEG monitoring during anesthesia -- Computerized EMG and EEG correlates of consciousness -- Computer control of anesthesia delivery -- Computer controlled anaesthesia -- Computer regulated sodium nitroprusside infusion for blood pressure control -- Computer controlled infusion of drugs during anesthesia: methods of muscle relaxant and narcotic administration -- Oxygen requirements during anesthesia -- Real time oximetry -- Graphic presentation of blood gas data -- Teaching the interpretation of acid-base and blood gas parameters by computer application -- Visual evoked potentials during cardiac surgery, basic considerations -- Phosphorus nuclear magnetic resonance (31 P NMR): a computer based instrument for studying brain hypoxia -- Measuring pulmonary blood flow with an 8085 -- A microcomputer-based charting system for documentation of heamodynamic, respiratory parameters and drug administration during cardiac anaesthesia -- Computer control of Intravenous anesthesia. 
520 |a There is a tendency of an increasing number of signals and derived variables to be incorporated in the monitoring of patients during anesthesia and in intensive care units. The addition of new signals hardly ever leads to thedeletion of other signals. This is probably based on a feeling of insecurity. We must realize that each new signal that is being monitored brings along its cost, in terms of risk to the patient, investment and time. It is therefore essential to assess the relative contribution of this new signal to the quality of the monitoring process; i. e. given the set of signals already in use, what is the improvement when a new signal is added? Beyond a certain point the addition of new information leads to new uncertainty and degrades the result (Ream, 1981) In the diagnostic process, it is possible to evaluate "result" in an objective, qualitative way. The changes in the sensitivity and specificity of the diagnosis as a result of the addition or deletion of a certain variable can be calculated on the basis of false negative, false positive, correct negative and false negative scores. Different methods for multiple regression analysis have been implemented on computers (Gelsema, 1981) which can support such decision processes. In monitoring, the situation is much more complex. Many definitions of monitoring have been given; the common denominator is that monitoring is a continuous diagnostic process based upon a (semi)continuous flow of information. This makes simple assessment methods useless. 
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