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Dynamic assessment of prealbumin for nutrition support effectiveness in critically ill patients.
Pardo, Emmanuel; Jabaudon, Matthieu; Godet, Thomas; Pereira, Bruno; Morand, Dominique; Futier, Emmanuel; Arpajou, Gauthier; Le Cam, Elena; Bonnet, Marie-Pierre; Constantin, Jean-Michel.
Affiliation
  • Pardo E; Sorbonne Université, GRC 29, AP-HP, DMU DREAM, Département d'Anesthésie-Réanimation, Hôpital Saint-Antoine, Assistance Publique-hôpitaux de Paris, 75012, Paris, France. Electronic address: emmanuel.pardo@aphp.fr.
  • Jabaudon M; Department of Perioperative Medicine, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France; iGReD, CNRS, INSERM, Université Clermont Auvergne, Clermont-Ferrand, France.
  • Godet T; Department of Perioperative Medicine, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France; Université Clermont Auvergne, Department of Healthcare Simulation, Clermont-Ferrand, F-63000, France; Université Clermont Auvergne, Inserm, Neuro-Dol, Clermont-Ferrand, F-63000, France.
  • Pereira B; Biostatistics and Data Management Unit, Department of Clinical Research and Innovation, CHU Clermont-Ferrand, Clermont-Ferrand, France.
  • Morand D; Direction de la Recherche Clinique (DRCI), CHU de Clermont-Ferrand, Clermont-Ferrand, F-63003, France.
  • Futier E; Department of Perioperative Medicine, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France; iGReD, CNRS, INSERM, Université Clermont Auvergne, Clermont-Ferrand, France.
  • Arpajou G; Department of Perioperative Medicine, CHU Clermont-Ferrand, 58 Rue Montalembert, 63000, Clermont-Ferrand, France.
  • Le Cam E; Sorbonne Université, GRC 29, AP-HP, DMU DREAM, Département d'Anesthésie-Réanimation, Hôpital Saint-Antoine, Assistance Publique-hôpitaux de Paris, 75012, Paris, France.
  • Bonnet MP; Sorbonne Université, Département Anesthésie-Réanimation, Hôpital Armand Trousseau, DMU DREAM, GRC 29, AP-HP, Paris, France; Université Paris Cité, INSERM, INRA, Centre for Epidemiology and Statistics Sorbonne Paris Cité (CRESS), Obstetrical Perinatal and Pediatric Epidemiology Research Team, EPOPé,
  • Constantin JM; Sorbonne Université, GRC 29, AP-HP, DMU DREAM, Département d'Anesthésie-Réanimation, Hôpital Pitié-Salpêtrière, Assistance Publique-hôpitaux de Paris, 75013, Paris, France.
Clin Nutr ; 43(6): 1343-1352, 2024 Jun.
Article de En | MEDLINE | ID: mdl-38677045
ABSTRACT
BACKGROUND &

AIMS:

Serum prealbumin is considered to be a sensitive predictor of clinical outcomes and a quality marker for nutrition support. However, its susceptibility to inflammation restricts its usage in critically ill patients according to current guidelines. We assessed the performance of the initial value of prealbumin and dynamic changes for predicting the ICU mortality and the effectiveness of nutrition support in critically ill patients.

METHODS:

This monocentric study included patients admitted to the ICU between 2009 and 2016, having at least one initial prealbumin value available. Prospectively recorded data were extracted from the electronic ICU charts. We used both univariable and multivariable logistic regressions to estimate the performance of prealbumin for the prediction of ICU mortality. Additionally, the association between prealbumin dynamic changes and nutrition support was assessed via a multivariable linear mixed-effects model and multivariable linear regression. Performing subgroup analysis assisted in identifying patients for whom prealbumin dynamic assessment holds specific relevance.

RESULTS:

We included 3136 patients with a total of 4942 prealbumin levels available. Both prealbumin measured at ICU admission (adjusted odds-ratio (aOR) 0.04, confidence interval (CI) 95% 0.01-0.23) and its change over the first week (aOR 0.02, CI 95 0.00-0.19) were negatively associated with ICU mortality. Throughout the entire ICU stay, prealbumin dynamic changes were associated with both cumulative energy (estimate 33.2, standard error (SE) 0.001, p < 0.01) and protein intakes (1.39, SE 0.001, p < 0.01). During the first week of stay, prealbumin change was independently associated with mean energy (6.03e-04, SE 2.32e-04, p < 0.01) and protein intakes (1.97e-02, SE 5.91e-03, p < 0.01). Notably, the association between prealbumin and energy intake was strongest among older or malnourished patients, those suffering from increased inflammation and those with high disease severity. Finally, prealbumin changes were associated with a positive mean nitrogen balance at day 7 only in patients with SOFA <4 (p = 0.047).

CONCLUSION:

Prealbumin measured at ICU admission and its change during the first-week serve as an accurate predictor of ICU mortality. Prealbumin dynamic assessment may be a reliable tool to estimate the effectiveness of nutrition support in the ICU, especially among high-risk patients.
Sujet(s)
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Préalbumine / Marqueurs biologiques / Maladie grave / Soutien nutritionnel / Unités de soins intensifs Limites: Aged / Female / Humans / Male / Middle aged Langue: En Journal: Clin Nutr Année: 2024 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Préalbumine / Marqueurs biologiques / Maladie grave / Soutien nutritionnel / Unités de soins intensifs Limites: Aged / Female / Humans / Male / Middle aged Langue: En Journal: Clin Nutr Année: 2024 Type de document: Article
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