Modulation of post-operative insulin resistance by pre-operative carbohydrate loading
- 1 August 2002
- journal article
- review article
- Published by Cambridge University Press (CUP) in Proceedings of the Nutrition Society
- Vol. 61 (3) , 329-336
- https://doi.org/10.1079/pns2002168
Abstract
Insulin resistance develops as a response to virtually all types of surgical stress. There is an increasing body of evidence that suggests that insulin resistance in surgical stress is not beneficial for outcome. A recent large study in intensive-care patients showed that aggressive treatment of insulin resistance using intravenous insulin reduced mortality and morbidity substantially. Similarly, in burn patients, intensive insulin and glucose treatment has been shown to improve N economy and enhance skin-graft healing. In surgical patients insulin resistance has been characterized in some detail, and has been shown to have many similarities with metabolic changes seen in patients with type 2 diabetes. This finding may be important since insulin resistance has been shown to be one independent factor that influences length of stay. When patients about to undergo elective surgery have been treated with glucose intravenously or a carbohydrate-rich drink instead of overnight fasting, insulin resistance was reduced by about half. A small meta-analysis showed that when post-operative insulin resistance was reduced by pre-operative carbohydrates, length of hospital stay was shortened. Overnight intravenous glucose at high doses improved post-operative N economy. This type of treatment has also been shown repeatedly to reduce cardiac complications after open-heart surgery. Furthermore, if the carbohydrates are given as a drink pre-operatively, pre-operative thirst, hunger and anxiety are markedly reduced. In summary, preventing or treating insulin resistance in surgical stress influences outcome. Fasting overnight is not an optimal way to prepare patients for elective surgery. Instead, pre-operative carbohydrates have clinical benefits.Keywords
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