4.6 Article

Definition of malnutrition from routinely-collected data for orthopedic surgery research: the global leadership initiative on malnutrition (GLIM) tool and others

Journal

FRONTIERS IN NUTRITION
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fnut.2023.1200049

Keywords

orthopaedics; surgery; malnutrition; prehabilitation; enhanced recovery after surgery; health status; patient outcomes assessment; blood chemical analyses

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Accurately identifying malnourished patients in surgical research can enhance the prediction of postoperative recovery potential, utilizing literature-based equations built on historical data to classify patients is essential for efficient studies.
The correct identification of malnourished patients in the context of hip, knee, or spine surgery research would enhance the quality of analytical studies investigating the prediction potential of preoperative nutritional disorders on postoperative recovery. However, accurate malnutrition screening and diagnostic assessment rely on parameters that were not routinely collected in routine practice until a few years ago. The authors of this article present substitute literature-based equations that can be built up using historical routinely collected data to classify patients that had been at risk of malnutrition or malnourished. For what concerns the risk screening, several methods are available to identify patients at risk of over- or undernutrition, encompassing the BWd (body weight difference from the ideal weight), GNRI (geriatric nutritional risk index), INA (instant nutritional assessment), LxA (combination of lymphocyte count and albumin), PMA (protein malnutrition with acute inflammation), PMAC (protein malnutrition with acute and chronic inflammation), IDM (iron deficit malnutrition), and VBD (vitamin B deficit malnutrition). Conversely, the GLIM (global leadership initiative on malnutrition) criteria can be used to assess malnutrition and diagnose subclasses of undernutrition. Rational use of these tools can facilitate the conduction of efficient prospective studies in the future, as well as bespoke retrospective cohort studies and database research.

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