Évaluation de l’état nutritionnel péri-opératoire

Thibault, Ronan; Francon, Daniel; Eloumou, Servais Albert Fiacre Bagnaka; Piquet, Marie-Astrid

doi:10.1016/j.nupar.2010.10.005

Cited by 12 publications

(2 citation statements)

References 84 publications

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“…The nutritional assessment is most often based on body mass, including weight loss and the calculation of body mass index (BMI), the albuminemia [5, 13, 14, 15, 16, 17]. Here we show that, although many assessment tools exist, none is entirely satisfactory in terms of sensitivity and/or specificity.…”

Section: Potential Biomarkers To Detect Malnutrition and To Monitor Tmentioning

confidence: 89%

“…A weight loss greater than 10% of the usual weight or during the six last months is a predictive factor of postoperative complications in major surgery [13]. Even if it a widely used marker, one can say that severe malnutrition is sometimes present in the absence of weight loss, such as with ascites because of liver disease.…”

Section: Potential Biomarkers To Detect Malnutrition and To Monitor Tmentioning

confidence: 99%

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Biomarkers in immunonutrition programme, is there still a need for new ones? A brief review

Forget

Echeverria

Giglioli

et al. 2015

ecancer

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Background and aimsPre-existing malnutrition is one the most important factors affecting postsurgical complications, especially in cancer patients. The consequences of this on the immune function as well as on outcome could be reversed by immunonutrition. To help the clinician as a researcher, a routinely available biomarker (derived from clinical or biological data) would be of great importance.MethodsWe reviewed the potential markers that may routinely be used in perioperative immunonutrition programmes. A comprehensive approach was used to identify and discuss the potential markers, focusing on body mass and serum biomarkers.ResultsBody mass (including weight loss and body mass index) are predictive of complications, but not specifically to malnutrition. Serum markers, such as albumin, transthyretin, white blood cells counts, and C-reactive protein are not more specific. Composite scores, including the Nutritional Risk Index (NRI), the Prognostic Inflammatory and Nutritional Index (PINI), the modified Glasgow Prognostic Score (mGPS), the neutrophil-to-lymphocyte ratio (NLR), CD4 and CD8 lymphocytes counts, the platelet-to-lymphocyte ratio (PLR), the Prognostic Index (PI), and the Prognostic Nutritional Index (PNI) are prognostic factors of outcome, but are not always correlated to immunonutrition effect.ConclusionsIn conclusion, there remains a lack of efficient and widely available monitoring of the effects of immunonutrition. To predict and monitor the effect of immunonutrition on immunity, efforts should be directed to the validation of routinely available tools to aid the implementation of advanced immune monitoring (like lymphocytes subpopulations counts) in clinical practices.

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