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Advances on energy expenditure predictive equations for oncology patients |
1Ruan Huijuan,1Feng Yi,2Liang Xiaoxiao,2Chen Dawei,2Huang Jiaoyan,2Huang Youyang,2Shi Hanping |
1Department of Clinical Nutrition Xinhua Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200092
China
2Department of Nutrition Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences Shanghai
202150 China |
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Abstract The prevalence of malnutrition in oncology patients is around 40%-80% and its occurrence is associated with higher
mortality and more medical expenditures. The nutritional status of oncology patients is an important factor affecting treatment outcome
and prognosis. Accurate prediction of human energy requirements is a prerequisite for nutritional health counseling and clinical nutrition
support. The indirect calorimetry IC method is often considered the gold standard for assessing resting energy expenditure REE .
Due to substantial geographical differences differences in the level of medical development the IC method requires not only specialized
equipment but also specialized personnel to perform it and therefore it is still not possible to perform IC measurements for all patients
in accordance with the guidelines. It has been found that different cancer types stages and treatments have different effects on energy
expenditure and conflicting findings exist. The estimation of energy expenditure and demand of cancer patients still remains to be
studied. Therefore it is important to evaluate and select predictive equations for energy expenditure suitable for patients with different
types of cancers. This study reviews the characteristics of energy metabolism of cancer patients common energy expenditure prediction
formulas and focuses on sorting out the relevant research progress of energy expenditure and prediction formulas for patients with
various tumor diseases. Finally this study also proposes the direction and outlook of future research.
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Received: 01 April 2023
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