Literature DB >> 26936031

Can Nutritional Assessment Tools Predict Response to Nutritional Therapy?

Chirag Patel1, Endashaw Omer1, Sarah J Diamond2, Stephen A McClave3.   

Abstract

Traditional tools and scoring systems for nutritional assessment have focused solely on parameters of poor nutritional status in the past, in an effort to define the elusive concept of malnutrition. Such tools fail to account for the contribution of disease severity to overall nutritional risk. High nutritional risk, caused by either deterioration of nutritional status or greater disease severity (or a combination of both factors), puts the patient in a metabolic stress state characterized by adverse outcome and increased complications. Newer scoring systems for determining nutritional risk, such as the Nutric Score and the Nutritional Risk Score-2002 have created a paradigm shift connecting assessment and treatment with quality outcome measures of success. Clinicians now have the opportunity to identify high risk patients through their initial assessment, provide adequate or sufficient nutrition therapy, and expect improved patient outcomes as a result. These concepts are supported by observational and prospective interventional trials. Greater clinical experience and refinement in these scoring systems are needed in the future to optimize patient response to nutrition therapy.

Entities:  

Keywords:  Malnutrition; Nutritional assessment; Nutritional risk

Mesh:

Year:  2016        PMID: 26936031     DOI: 10.1007/s11894-016-0488-y

Source DB:  PubMed          Journal:  Curr Gastroenterol Rep        ISSN: 1522-8037


  16 in total

1.  Impact of preoperative nutritional support on clinical outcome in abdominal surgical patients at nutritional risk.

Authors:  Bin Jie; Zhu-Ming Jiang; Marie T Nolan; Shai-Nan Zhu; Kang Yu; Jens Kondrup
Journal:  Nutrition       Date:  2012-06-05       Impact factor: 4.008

2.  Short-term individual nutritional care as part of routine clinical setting improves outcome and quality of life in malnourished medical patients.

Authors:  Juliane Starke; Heinz Schneider; Birgit Alteheld; Peter Stehle; Rémy Meier
Journal:  Clin Nutr       Date:  2011-04       Impact factor: 7.324

3.  Use of the nutritional risk score by surgeons and nutritionists.

Authors:  Michael Benoit; Fabian Grass; Nicolas Demartines; Pauline Coti-Bertrand; Markus Schäfer; Martin Hübner
Journal:  Clin Nutr       Date:  2015-01-28       Impact factor: 7.324

4.  Identifying critically-ill patients who will benefit most from nutritional therapy: Further validation of the "modified NUTRIC" nutritional risk assessment tool.

Authors:  Adam Rahman; Rana M Hasan; Ravi Agarwala; Claudio Martin; Andrew G Day; Daren K Heyland
Journal:  Clin Nutr       Date:  2015-01-28       Impact factor: 7.324

5.  Use of Subjective Global Assessment, Patient-Generated Subjective Global Assessment and Nutritional Risk Screening 2002 to evaluate the nutritional status of non-critically ill patients on parenteral nutrition.

Authors:  M B Badia-Tahull; S Cobo-Sacristán; E Leiva-Badosa; M E Miquel-Zurita; N Méndez-Cabalerio; R Jódar-Masanés; J Llop-Talaverón
Journal:  Nutr Hosp       Date:  2014-02-01       Impact factor: 1.057

6.  Utilizing multiple methods to classify malnutrition among elderly patients admitted to the medical and surgical intensive care units (ICU).

Authors:  Patricia M Sheean; Sarah J Peterson; Yimin Chen; Dishan Liu; Omar Lateef; Carol A Braunschweig
Journal:  Clin Nutr       Date:  2013-01-05       Impact factor: 7.324

Review 7.  Nutritional-risk scoring systems in the intensive care unit.

Authors:  Jens Kondrup
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2014-03       Impact factor: 4.294

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

Authors:  Daren K Heyland; Rupinder Dhaliwal; Xuran Jiang; Andrew G Day
Journal:  Crit Care       Date:  2011-11-15       Impact factor: 9.097

9.  Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients.

Authors:  Lesley L Moisey; Marina Mourtzakis; Bryan A Cotton; Tahira Premji; Daren K Heyland; Charles E Wade; Eileen Bulger; Rosemary A Kozar
Journal:  Crit Care       Date:  2013-09-19       Impact factor: 9.097

Review 10.  Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review.

Authors:  Lilian Minne; Ameen Abu-Hanna; Evert de Jonge
Journal:  Crit Care       Date:  2008-12-17       Impact factor: 9.097

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  4 in total

Review 1.  Measuring and monitoring lean body mass in critical illness.

Authors:  Wilhelmus G P M Looijaard; Jeroen Molinger; Peter J M Weijs
Journal:  Curr Opin Crit Care       Date:  2018-08       Impact factor: 3.687

2.  High nutritional risk is associated with unfavorable outcomes in patients admitted to an intensive care unit.

Authors:  Julia Marchetti; Audrey Machado Dos Reis; Amanda Forte Dos Santos; Oellen Stuani Franzosi; Vivian Cristine Luft; Thais Steemburgo
Journal:  Rev Bras Ter Intensiva       Date:  2019-10-14

3.  Nutritional risk screening score as an independent predictor of nonventilator hospital-acquired pneumonia: a cohort study of 67,280 patients.

Authors:  Zhihui Chen; Hongmei Wu; Jiehong Jiang; Kun Xu; Shengchun Gao; Le Chen; Haihong Wang; Xiuyang Li
Journal:  BMC Infect Dis       Date:  2021-04-01       Impact factor: 3.090

4.  Association of nutrition risk screening 2002 and Malnutrition Universal Screening Tool with COVID-19 severity in hospitalized patients in Iran.

Authors:  Ghazaleh Eslamian; Sohrab Sali; Mansour Babaei; Karim Parastouei; Dorsa Arman Moghadam
Journal:  Acute Crit Care       Date:  2022-07-05
  4 in total

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