Malnutrition is a growing public health problem leading to increased morbidity and mortality worldwide. Up to 50% of elderly patients are hospitalized due to this condition. In this review, we focused on analyzing the current diagnostic criteria for malnutrition among the elderly population and proposing promising solutions. Currently used diagnostic methods such as BMI or serum albumin levels are not sufficient to indicate malnutrition, which is affected by many factors, including the number of chronic diseases, multiple medications taken, or physical condition. Moreover, current recommendations are inadequate because they fail to account for various factors such as chronic illnesses, multiple medications, and bodily changes that are crucial in diagnostic evaluations. There is a noticeable gap between these recommendations and actual clinical practice. Nevertheless, developing more precise, non-invasive biomarkers and personalized nutrition strategies has to be explored. One of these strategies we discuss in our review is multidisciplinary approaches that combine nutrition, physical activity, and psychosocial support. Addressing malnutrition among the elderly should rely on standardized protocols and personalized interventions to enhance their nutritional health and overall well-being.

OBJECTIVE: Correctly characterizing malnutrition is a challenge. Transthyretin (TTR) rapidly responds to adequate protein intake/infusion, which could be used as a marker to identify malnutrition. Nutritional therapy is used to prevent malnutrition. Parenteral nutrition (PN) requires daily monitoring to determine whether what is being offered is adequate. This article aims to investigate whether the practice of measuring TTR is justified.
METHODS: Data from patients admitted to the ward or intensive care unit (ICU) were collected at three different times: within the first 72 h (T1) of PN use, on the 7th day (T2), and the 14th day (T3) after the initial assessment.
RESULTS: 302 patients were included; the average age was 48.3 years old; the prevalence of death was 22.2%, and 61.6% of the sample were male. TTR values and the effectiveness of nutritional support in these patients were not associated with the outcome; however, meeting caloric needs was related to the outcome (p = 0.047). No association was found when TTR values were compared to the nutritional status. Thus, TTR was not a good indicator of nutritional risk or nutritional status in hospitalized patients.
CONCLUSIONS: Undoubtedly, the TTR measurement was inversely proportional to CRP measurements. It was possible to conclude in this follow-up cohort of hospitalized patients that TTR values were not useful for determining whether the patient was malnourished, predicting death or effectiveness of nutritional support, yet based upon our analyses, a decrease in TTR greater than 0.024 units for every 1 unit increase in CRP might be due to ineffective nutritional supply.

UNASSIGNED: Nutrition is a fundamental aspect of nursing care, however older people cared for in hospital, in a care home or in their own home do not always receive adequate support with their nutritional needs, which can leave them at risk of malnutrition. Using a holistic, biopsychosocial framework to support a comprehensive nutritional assessment that includes malnutrition screening can support the nurse to identify the older person\'s nutritional status and nutrition needs. Nurses undertaking this procedure must ensure they have the knowledge and skills to do so and work within the limits of their competence. • Malnutrition in older people can lead to a decline in functional ability, reduced muscle strength, fatigue, impaired immunity, suboptimal wound healing, increased risk of infection and increased risk of falls. • Screening for, and assessing the risk of, malnutrition is an important part of nursing assessments in any healthcare setting. • A holistic nutritional assessment should incorporate physiological, psychological, emotional, spiritual, social and cultural elements. REFLECTIVE ACTIVITY: \' How to\' articles can help to update your practice and ensure it remains evidence based. Apply this article to your practice. Reflect on and write a short account of: • How this article might improve your practice when undertaking a holistic nutritional assessment with an older person. • How you could use this information to educate nursing students or your colleagues on the appropriate techniques and evidence base for undertaking a holistic nutritional assessment with an older person.

BACKGROUND: Dysphagia and malnutrition are major contributors to mortality in patients with acute stroke. An early assessment of nutritional status upon hospital admission is crucial to enhance clinical outcomes by reducing the associated high-risk complications. However, the fragmented nature of the existing literature makes it difficult to optimize clinical practices.
OBJECTIVE: This study aims to identify the best clinical practices that nurses and other healthcare professionals can employ for the immediate assessment of nutritional risk in patients diagnosed with acute stroke.
METHODS: Systematic review of clinical practice guidelines and systematic reviews.
METHODS: Comprehensive bibliographic searches were conducted up to May 2024 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines across the databases Cochrane Library, PubMed, Embase, CINAHL, and Scopus, and three recognized guideline repositories.
METHODS: The quality of clinical practice guidelines was ascertained using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument, and the quality of systematic reviews was assessed through A MeaSurement Tool to Assess Systematic Reviews (AMSTAR 2). The evidence quality was appraised based on the classifications by the European Society of Cardiology.
RESULTS: Out of 2534 identified records, 15 were incorporated into this review. Predominantly, the selected clinical practice guidelines and systematic reviews exhibited high methodological quality. Notably, the Gugging Swallowing Screen and the Malnutrition Universal Screening Tool were pinpointed as primary tools for initial screenings. Most studies recommended that these assessments, ideally conducted within the first 24 h of patient admission, should be carried out by specially trained professionals, highlighting the pivotal role of nurses. Deviations in screening outcomes necessitate complementary specialist evaluations.
CONCLUSIONS: This systematic review offers a consolidation of current insights, proposing an innovative and integrated approach to assess nutritional needs of high-risk patients. It underscores the importance of nurses in the screening process, emphasizing their pivotal role in the nutritional management of patients with acute stroke, and advocates for further research endeavors to standardize intervention protocols to elevate patient clinical outcomes.
UNASSIGNED: PROSPERO CRD42023425140.

UNASSIGNED: To evaluate the hypothesis that anthropometric dimensions derived from a person\'s manifold-regression predicted three-dimensional (3D) humanoid avatar are accurate when compared to their actual circumference, volume, and surface area measurements acquired with a ground-truth 3D optical imaging method. Avatars predicted using this approach, if accurate with respect to anthropometric dimensions, can serve multiple purposes including patient metabolic disease risk stratification in clinical settings.
UNASSIGNED: Manifold regression 3D avatar prediction equations were developed on a sample of 570 adults who completed 3D optical scans, dual-energy X-ray absorptiometry (DXA), and bioimpedance analysis (BIA) evaluations. A new prospective sample of 84 adults had ground-truth measurements of 6 body circumferences, 7 volumes, and 7 surface areas with a 20-camera 3D reference scanner. 3D humanoid avatars were generated on these participants with manifold regression including age, weight, height, DXA %fat, and BIA impedances as potential predictor variables. Ground-truth and predicted avatar anthropometric dimensions were quantified with the same software.
UNASSIGNED: Following exploratory studies, one manifold prediction model was moved forward for presentation that included age, weight, height, and %fat as covariates. Predicted and ground-truth avatars had similar visual appearances; correlations between predicted and ground-truth anthropometric estimates were all high (R2s, 0.75-0.99; all p < 0.001) with non-significant mean differences except for arm circumferences (%D ~ 5%; p < 0.05). Concordance correlation coefficients ranged from 0.80-0.99 and small but significant bias (p < 0.05 - 0.01) was present with Bland-Altman plots in 13 of 20 total anthropometric measurements. The mean waist to hip circumference ratio predicted by manifold regression was non-significantly different from ground-truth scanner measurements.
UNASSIGNED: 3D avatars predicted from demographic, physical, and other accessible characteristics can produce body representations with accurate anthropometric dimensions without a 3D scanner. Combining manifold regression algorithms into established body composition methods such as DXA, BIA, and other accessible methods provides new research and clinical opportunities.

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BACKGROUND: Patients during radiotherapy due to head and neck cancers experience a lot of side effects which may have a considerable impact on the patients\' ability to meet individual daily energy demands by means of oral diet.
METHODS: The study included 104 head and neck cancer patients who qualified for radical radiotherapy. Radical treatment takes 6 weeks and every week the patients were assessed for dietary intake. The subjects were covered with the constant care of a dietician, received FSMP (food for special medical purposes), and, if necessary, enteral nutrition.
RESULTS: In the first week of treatment, the patients, from the kitchen diet alone, met 91.5% of the energy demand, while in the last week of treatment, only 40.9%. After introducing the FSMP or enteral nutrition, the patients met 120% of the demand in the first week of therapy and 95% in the last week, respectively. The patients who followed the dietary recommendations were characterized by significantly lower weight loss (3.07 kg) compared to non-adherent patients (5.56 kg).
CONCLUSIONS: The used therapy significantly contributed to decreasing nutritional intake in the subsequent weeks of treatment. On the other hand, incorporating FSMP in the diet and enteral nutrition with industrial diets significantly increased the fulfilled energy demand of patients.

Individuals receiving hemodialysis are at increased risk of malnutrition; however, regular diagnosis of malnutrition using subjective global assessment (SGA) is time-consuming. This study aimed to determine whether the Canadian Nutrition Screening Tool (CNST) or the Geriatric Nutrition Risk Index (GNRI) screening tools could accurately identify hemodialysis patients at risk for malnutrition. A retrospective medical chart review was conducted for in-centre day shift hemodialysis patients (n = 95) to obtain the results of the SGA assessment and the CNST screener and to calculate the GNRI score. Sensitivity and specificity analyses showed only a fair agreement between the SGA and CNST (sensitivity = 20%; specificity 96%; κ = .210 (95% CI, -0.015 to .435), p < .05) and between the SGA and GNRI (sensitivity = 35%; specificity = 88%; κ = .248 (95% CI, .017 to .479), p < .05). There was no significant statistical difference between the accuracy of either tool in identifying patients at risk of malnutrition (p = .50). The CNST and GNRI do not accurately screen for risk of malnutrition in the hemodialysis population; therefore, further studies are needed to determine an effective malnutrition screening tool in this population.

Malnutrition among the population of the world is a frequent yet underdiagnosed problem in both children and adults. Development of malnutrition screening and diagnostic tools for early detection of malnutrition is necessary to prevent long-term complications to patients\' health and well-being. Most of these tools are based on predefined questionnaires and consensus guidelines. The use of artificial intelligence (AI) allows for automated tools to detect malnutrition in an earlier stage to prevent long-term consequences. In this study, a systematic literature review was carried out with the goal of providing detailed information on what patient groups, screening tools, machine learning algorithms, data types, and variables are being used, as well as the current limitations and implementation stage of these AI-based tools. The results showed that a staggering majority exceeding 90% of all AI models go unused in day-to-day clinical practice. Furthermore, supervised learning models seemed to be the most popular type of learning. Alongside this, disease-related malnutrition was the most common category of malnutrition found in the analysis of all primary studies. This research provides a resource for researchers to identify directions for their research on the use of AI in malnutrition.

OBJECTIVE: Equations estimating fat-free mass (FFM) in people living with the human immunodeficiency virus (HIV) show differences in the validation process. The current study aimed to verify the validity of FFM estimation equations derived from bioelectrical impedance (BIA) in people living with HIV aged 40 years and older.
METHODS: A cross-sectional study was conducted with 68 participants evaluated using dual-energy X-ray absorptiometry (DXA) and by two BIA devices (Analyzer and Biodynamics). The study aimed to determine the validity of six different FFM equations from four different studies by Lukaski and Bolonchuk (1987), Kotler et al. (1996), Beraldo et al. (2015) and Hegelund et al. (2017). Comparisons were made using the t-test or Wilcoxon test. To verify the validity between DXA and two BIA devices, the following statistical analyses were performed: Lin\'s concordance correlation coefficient, intraclass correlation coefficient, coefficient of determination, standard error of the estimate, differences in the limits of agreement by Bland and Altman analysis, correlation between the average and the differences of the methods by Pearson or Spearman correlation.
RESULTS: Only equation 2 of Kotler et al. (1996) for males by Biodynamics BIA showed no difference in FFM. The Lin\'s concordance correlation coefficient was excellent (0.96), irrespective of sex, for Equation 2 of Kotler et al. (1996) by BIA Analyzer. All equations were reproducible (>0.85). The coefficient of determination ranged from 68% to 92%, and the standard error of the estimates ranged from 1.8 kg to 5.0 kg. The differences between the limits of agreement ranged from 7.2 kg to 14.9 kg, and the correlations between the average and the differences of the methods showed differences in FFM for three equations (p < 0.01).
CONCLUSIONS: The choice of equations must consider the equipment used and the sex of the sample investigated. Only Equation 2 of Kotler et al. (1996) was considered valid, irrespective of sex, to estimate the FFM by BIA Analyzer.