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A model to predict patient temperature during cardiac surgery
A core temperature drop after cardiac surgery slows down the patient's recuperation process. In order to minimize the amount of the so-called afterdrop, more knowledge is needed about the impaired thermoregulatory system during anesthesia and the effect of different protocols on temperature dis...
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Published in: | Physics in medicine & biology 2007-09, Vol.52 (17), p.5131-5145 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A core temperature drop after cardiac surgery slows down the patient's recuperation process. In order to minimize the amount of the so-called afterdrop, more knowledge is needed about the impaired thermoregulatory system during anesthesia and the effect of different protocols on temperature distribution. Therefore, a computer model has been developed that describes heat transfer during cardiac surgery. The model consists of three parts: (1) a passive part, which gives a simplified description of the human geometry and the passive heat transfer processes, (2) an active part that takes into account the thermoregulatory system as a function of the amount of anesthesia and (3) submodels, through which it is possible to adjust the boundary conditions. The validity of the new model was tested by comparing the model results to the measurement results of three surgical procedures. A good resemblance was found between simulation results and the experiments. Next, a model application was shown. A parameter study was performed to study the effect of different temperature protocols on afterdrop. It was shown that the effectiveness of forced-air heating is larger than the benefits resulting from increased environmental temperature or usage of a circulating water mattress. Ultimately, the model could be used to develop a monitoring decision system that advises clinicians what temperature protocol will be best for the patient. |
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ISSN: | 0031-9155 1361-6560 |
DOI: | 10.1088/0031-9155/52/17/002 |