Nutrition Screening Tools Analysis Research Paper

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There are various methods to identify if a patient is at risk for malnutrition. In older people, malnutrition is a frequently occurring problem, and early and proper nutrition intervention can improve life quality as well as health outcomes. Early detection and sufficient nutrition support may help to reverse or arrest the malnutrition progression and the negative consequences that come with it. To assist in discovering those who are at risk of malnutrition, a nutrition screening method is proposed. Identification of people who are at risk of suffering from malnutrition has to be a simple process. The screening does not need nutrition knowledge and may be carried out by any member of staff. Malnutrition may not be diagnosed or treated if nutrition screening is not performed. As a result, it should be performed by someone who has received specialized training. MUST, MST, and MNA-SF display sufficient concurrent validity when contrasted with validated nutritional assessment instruments and can be used to triage nutritional services in the long-term care setting.

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Many nutrition screening methods have been published; however, many of them have flaws in their statistical creation as well as their validity and reliability testing. Although some nutrition screening approaches have received more research, others are more difficult, including anthropometric measurements and computations. Others were validated and widely utilized in acute settings but not for implementation with long-term care patients (Isenring et al, 2012). This article was chosen due to it researching various methods and, most importantly, due to it comparing their results with the previously validated methods. The goal of the study was to compare the concurrent validity of the routinely used nutrition screening instruments.

The MST is made up of two questions on recent unintended weight reduction and eating poorly due to a diminished appetite. The MST yields a score between 0 and 5, with a score of 2 indicating that the patient is in danger of malnutrition. The MST has been tested in acute hospital and ambulatory care settings but not in the long-term care. It was found that the consumption question needs to be widened as a consequence. As a result, the MST instrument utilized in research determined whether or not a person was eating badly for any reason. Reduced appetite, quick satiety, swallowing, and chewing difficulty are among them.

MUST is a global screening test that includes a BMI category (BMI 20 is considered high risk), a weight reduction category (unintentional weight reduction in the previous three to six months), and a severe disease rating. A score of one indicates a medium risk of malnutrition, whereas a value of two or higher indicates severe risk of malnutrition. ESPEN recommends MUST for community-based adult screening. The previous Mini Nutritional Assessment (MNA) was transformed into the six-item MNA-SF for use as a nutritional screening method for the elderly (Isenring, 2012). Recent poor intake, the recent loss of weight, body mass index (BMI), physical activity, recent psychological stress or acute illness, and cognitive issues are among the characteristics used. The MNA-SF instrument is presently recommended for screening the elderly (Isenring, 2012). Anthropometric evaluation, general assessment, dietary assessment, and self-assessment are all covered by the entire MNA, which comprises 18 questions, with possible scores varying from 0 to 30 (Isenring, 2012). Older individuals with a score of 24 are considered well-fed, those with a score of 17 to 23.5 are considered at malnutrition risk, and those with a score of 17 are considered malnourished (Isenring, 2012). MNA is suggested as the first-choice instrument in care facilities, has been extensively researched in older persons, and is advised to be used in the baseline data set for older adults.

The MNA-SF, in all of its incarnations, has a useful predictive capacity versus the MNA. The method has the benefit of requiring fewer resources as well as less time in general practice, yet the specific characteristics of the local population must always be considered when making a decision relying on the MNA-SF scales (Lozoya et al, 2017). The MST accurately identifies malnutrition for more than 80% of patients in the study, and it has strong reliability and validity when it comes to nutritional evaluation, not just in inpatients and cancer outpatients, where it has been validated (Castro-Vega & Bañuls, 2018). The MST was proven to be valid in ambulatory, institutionalized, and hospitalized patients in population. Another research shows that MUST may be safely used to diagnose malnutrition in acutely ill general medical, aged people (Murphy et al, 2018). Significant recent weight reduction seemed to have relevance, nearly on par with MUST, in predicting the likelihood of malnutrition in this research.

In conclusion, MST, MUST, and MNA-SF are efficient in identifying malnutrition, which is demonstrated in various studies. Usage of these methods will improve practice due to their efficiency, which is defined by fewer resources required to use these nutrition screening tools, relatively simple and quick training, and preciseness. Having such evidence provides the assurance for healthcare organizations to use these screening tools, as they are proven to be valid. The primary weaknesses of the evidence are related to small sample sizes, as well as the susceptibility of these methods to specifics of local population in terms of their results. They allow diagnosing nutrition issues early both for ambulatory and hospitalized patients that permits to reduce risks of later severe outcomes. When compared to the MNA and SGA nutrition assessments, the nutrition screening methods MST, MUST, and MNA-SF demonstrated adequate sensitivity and specificity.

References

Castro-Vega, I., & Bañuls, C. (2018). Validation of nutritional screening Malnutrition Screening Tool compared to other screening tools and the nutritional assessment in different social and health areas. Nutricion Hospitalaria, 35(2), 351-358. Web.

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Isenring, E., Banks, M., Ferguson, M., & Bauer, J. (2012). . Journal of the Academy of Nutrition and Dietetics, 112(3), 376-381. Web.

Lozoya, R. M., Martínez-Alzamora, N., Marín, G. C., Guirao-Goris, S. J., & Ferrer-Diego, R. M. (2017). PeerJ, 5, e3345. Web.

Murphy, J., Mayor, A., & Forde, E. (2018). British Journal of General Practice, 68(672), 344-345. Web.

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IvyPanda. 2023. "Nutrition Screening Tools Analysis." April 20, 2023. https://ivypanda.com/essays/nutrition-screening-tools-analysis/.

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