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. 2011;15(6):R268.
doi: 10.1186/cc10546. Epub 2011 Nov 15.

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

Daren K Heyland  1 , Rupinder Dhaliwal, Xuran Jiang, Andrew G Day
Affiliations

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

Daren K Heyland et al. Crit Care. 2011.

Abstract

Introduction: To develop a scoring method for quantifying nutrition risk in the intensive care unit (ICU).

Methods: 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.

Results: 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).

Conclusions: This scoring algorithm may be helpful in identifying critically ill patients most likely to benefit from aggressive nutrition therapy.

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Figures

Figure 1
Figure 1
Conceptual model for nutrition risk assessment in the critically ill. APACHE, Acute physiology and chronic health evaluation score; BMI, body mass index; CRP, C-reactive protein; IL-6, interleukin 6; PCT, procalcitonin; SOFA, sequential organ failure assessment score.
Figure 2
Figure 2
Relation between NUTRIC score and 28-day mortality. NUTRIC, Nutrition Risk in the Critically Ill Score.
Figure 3
Figure 3
Relation between NUTRIC score and duration of mechanical ventilation among 28-day survivors. NUTRIC, Nutrition Risk in the Critically Ill Score.
Figure 4
Figure 4
Predicted probability of 28-day mortality versus percent of caloric. Prescription received for patients with low (n = 114) and high (n = 97) NUTRIC score. Lines and shading are the predicted probability and 95% confidence intervals based on logistic regression. Circles and plus symbols indicate the observed values for the subgroup of 211 patients evaluable for assessment of nutritional adequacy. NUTRIC, Nutrition Risk in the Critically Ill Score.
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