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Identifying critically ill patients who benefit the most from nutrition therapy: the development and initial validation of a novel risk assessment tool

TLDR
This scoring algorithm may be helpful in identifying critically ill patients most likely to benefit from aggressive nutrition therapy in the intensive care unit (ICU), and based on the statistical significance in the multivariable model, the final score used all candidate variables except BMI.
Abstract
To develop a scoring method for quantifying nutrition risk in the intensive care unit (ICU). A prospective, observational study of patients expected to stay > 24 hours. We collected data for key variables considered for inclusion in the score which included: age, baseline APACHE II, baseline SOFA score, number of comorbidities, days from hospital admission to ICU admission, Body Mass Index (BMI) < 20, estimated % oral intake in the week prior, weight loss in the last 3 months and serum interleukin-6 (IL-6), procalcitonin (PCT), and C-reactive protein (CRP) levels. Approximate quintiles of each variable were assigned points based on the strength of their association with 28 day mortality. A total of 597 patients were enrolled in this study. Based on the statistical significance in the multivariable model, the final score used all candidate variables except BMI, CRP, PCT, estimated percentage oral intake and weight loss. As the score increased, so did mortality rate and duration of mechanical ventilation. Logistic regression demonstrated that nutritional adequacy modifies the association between the score and 28 day mortality (p = 0.01). This scoring algorithm may be helpful in identifying critically ill patients most likely to benefit from aggressive nutrition therapy.

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Journal ArticleDOI

Identifying Critically Ill Veterans Who Require Nutrition Intervention: A Quality Improvement Study Comparing Nutrition Risk Tools.

TL;DR: Trialing several tools to identify their efficacy and reliability individual setting may help determine the most appropriate tool to utilize for your patient population and specific goals.
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Nutrition support for acute kidney injury 2020-consensus of the Taiwan AKI task force

TL;DR: In this article , the authors used evidence-based medicine to suggest guidelines of nutritional support for Taiwanese patients with acute kidney injury (AKI), and reached a consensus on answering clinical questions related to the effects of the nutritional status, energy/protein intake recommendations, timing of enteral, and parenteral nutrition supplementation.
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Faut-il nourrir les sujets obèses en réanimation ?

TL;DR: L’etat nutritionnel peut s’apprecier par l’imagerie de the masse musculaire Les apports nutritionnels se font preferentiellement par voie enterale.
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Nutritional risk factors for all-cause mortality of critically ill patients: a retrospective cohort study

TL;DR: Wang et al. as mentioned in this paper explored the predictive value of single and multiple risk factors for the clinical outcomes of critically ill patients receiving enteral nutrition and established an effective evaluation model, which had a good predictive value for 28-day mortality.
Journal ArticleDOI

Nutritionnal Status Assessment in the Elderly Person in Intensive Care Unit

TL;DR: Subjective global assessment, Nutrition Risk In Critically Ill Score (NUTRIC score), and CT Scan in the 3rd lumbar vertebra (L3) could be the objective tools for assessment of the nutritional status of aged adults in the ICU.
References
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Applied Logistic Regression

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Journal ArticleDOI

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A note on a general definition of the coefficient of determination

TL;DR: In this article, a generalization of the coefficient of determination R2 to general regression models is discussed, and a modification of an earlier definition to allow for discrete models is proposed.
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