Materiały źródłowe

• #1 Malnutrition Screening and Assessment

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9228435/

  Malnutrition is a serious problem with a negative impact on the quality of life and the evolution of patients, contributing to an increase in morbidity, length of hospital stay, mortality, and health spending. […] The consequences of malnutrition are a reduction in quality of life, as well as an increase in morbidity, the appearance of infections, poor wound healing, functional alterations in immune defense, a reduction in overall muscle strength, especially in pulmonary ventilation, and increased mortality, length of hospital stay, and hospital costs. […] A systematic approach to addressing malnutrition in hospitals should begin with a nutritional risk assessment of all patients at admission, followed by a detailed assessment of the nutritional status of patients most at risk. […] The aim of this review is to show the most widely used methods for nutritional screening to identify individuals at risk of malnutrition with different diseases, and the methods then used for the assessment of the nutritional status of the at-risk patients.

• #2 Malnutrition Screening and Assessment

  https://www.mdpi.com/2072-6643/14/12/2392

  Malnutrition is a serious problem with a negative impact on the quality of life and the evolution of patients, contributing to an increase in morbidity, length of hospital stay, mortality, and health spending. […] Early identification is fundamental to implement the necessary therapeutic actions, involving adequate nutritional support to prevent or reverse malnutrition. […] Malnutrition is prevalent in many diseases, and especially in hospitalized patients, institutionalized elderly patients, and chronic patients. […] The consequences of malnutrition are a reduction in quality of life, as well as an increase in morbidity, the appearance of infections, poor wound healing, functional alterations in immune defense, a reduction in overall muscle strength, especially in pulmonary ventilation, and increased mortality, length of hospital stay, and hospital costs.

• #3 Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9144143/

  Background: Malnutrition predicts a worse outcome for critically ill patients. […] In-hospital mortality was 46.7% (n = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. […] PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS. […] Non-survivors were at a significantly higher nutritional risk on all four nutritional assessment scores included in the study, namely PNI, CONUT, NUTRIC, and mNUTRIC. […] Our study has shown that the non-invasive nutritional assessment of patients with severe COVID-19 admitted in the ICU, using the PNI, CONUT, NUTRIC, and mNUTRIC, effectively predicts in-hospital mortality. […] Non-invasive biological scores for nutritional risk assessment tools such as PNI, CONUT, NUTRIC, and mNUTRIC are effective independent predictors for the risk of in-hospital mortality in patients with severe COVID-19 and ARDS hospitalized in the ICU.

• #4 Association of malnutrition status with 30-day mortality in patients with sepsis using objective nutritional indices: a multicenter retrospective study in South Korea

  https://www.accjournal.org/journal/view.php?doi=10.4266/acc.2023.01613

  The Controlling Nutritional Status (CONUT) score and the prognostic nutritional index (PNI) have emerged as important nutritional indices because they provide an objective assessment based on data. We aimed to investigate how these nutritional indices relate to outcomes in patients with sepsis. […] The nutritional indices CONUT score and PNI showed significant associations with mortality of sepsis patients within 30 days. […] Malnutrition exhibits a significant association to poor outcomes in patients with sepsis, and these indices can be helpful for predicting mortality. […] In patients with sepsis, the nutritional indices Controlling Nutritional Status score and the prognostic nutritional index were correlated with mortality within 30 days. In sepsis patients and mechanically ventilated sepsis patients, nutritional status was correlated with mortality within 30 days.

• #5 Malnutrition Screening and Assessment

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9228435/

  Patients with a high NUTRIC score who receive an adequate nutritional intervention have a lower incidence of complications than those in whom the nutritional intervention is not satisfactory, who have poorer survival outcomes. […] Malnutrition affects large numbers of patients, particularly the very frail, such as elderly patients, patients with a chronic inflammatory process such as cancer or other kidney, respiratory, or heart diseases, and those with an acute inflammatory process, such as critical or surgical patients. […] For this reason, early detection must be a systematic objective pursued as soon as the relationship is established between the social or the healthcare system and the individual, as adequate nutritional intervention is shown to reduce mortality and complications in hospitalized patients.

• #6 Predicting the risk of mortality during hospitalization in sick severely malnourished children using daily evaluation of key clinical warning signs | BMC Medicine | Full Text

  https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-021-02074-6

  Despite adherence to WHO guidelines, inpatient mortality among sick children admitted to hospital with complicated severe acute malnutrition (SAM) remains unacceptably high. […] This study aimed to determine the prognostic value of monitoring clinical signs on a daily basis for assessing mortality risk during hospitalization in children with SAM. […] The presence of the following CWS during daily assessment were found to be independent predictors of inpatient mortality: symptomatic hypoglycemia, reduced consciousness, chest indrawing, not able to complete feeds, nutritional edema, diarrhea, and fever. […] Daily risk scores computed using these 7 CWS together with MUAC10.5cm at admission as additional CWS predict survival outcome of children with SAM with a C-index of 0.81 (95% CI 0.770.86).

• #7 Predicting the risk of mortality during hospitalization in sick severely malnourished children using daily evaluation of key clinical warning signs | BMC Medicine | Full Text

  https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-021-02074-6

  This study provides evidence for structured monitoring of daily CWS as recommended clinical practice as it improves prediction of inpatient mortality among sick children with complicated SAM. […] We propose a simple counting-tool to guide healthcare workers to assess treatment response for these children. […] The 7 identified daily CWS included, in order of decreasing daily HRdeath, symptomatic hypoglycemia, reduced consciousness, lower chest wall indrawing, not being able to complete feeds, nutritional edema, diarrhoea, and fever. […] Having 1 or 2 of these CWS on any day during hospitalization was associated with a 3 or 11-fold increased mortality risk compared with no signs, respectively. […] Monitoring CWS on a daily basis improved the accuracy of predicting mortality in children with SAM, compared to using admission predictors only. […] These results underscore that counting CWS could serve as an easily applicable tool for identification of changes in risk over time.

• #8 Disease-Related Malnutrition and Sarcopenia Predict Worse Outcome in Medical Inpatients: A Cohort Study

  https://www.mdpi.com/2072-6643/13/9/2937

  Disease-Related Malnutrition and Sarcopenia Predict Worse Outcome in Medical Inpatients: A Cohort Study […] (1) Background: Both sarcopenia and disease-related malnutrition (DRM) are unfortunately underdiagnosed and undertreated in our Western hospitals, which could lead to worse clinical outcomes. Our objectives included to determine the impact of low muscle mass (MM) and strength, and also DRM and sarcopenia, on clinical outcomes (length of stay, death, readmissions at three months, and quality of life). […] (4) Conclusions: In medical inpatients, mostly polymorbid, both DRM but specially sarcopenia are associated with poorer quality of life, more readmissions, and higher mortality. Low HGS proved to be a stronger predictor of worse outcomes than MM. […] […] (5) Conclusions: In medical polymorbid inpatients, both DRM (diagnosed with GLIM criteria) but mostly sarcopenia (with EWGSOP2 criteria) are associated with worse quality of life, more readmissions, and higher mortality. Low muscle strength measured by HGS, but not the amount of muscle mass, was also associated with worse quality of life, a higher readmission rate, and higher mortality. Therefore, we consider that an appropriate approach to DRM and especially to sarcopenia should be reinforced.

• #9 Inflammation-driven malnutrition: a new screening tool predicts outcome in Crohn’s disease | British Journal of Nutrition | Cambridge Core

  https://www.cambridge.org/core/journals/british-journal-of-nutrition/article/inflammationdriven-malnutrition-a-new-screening-tool-predicts-outcome-in-crohns-disease/D9B298A08E07B653007FCD60023C900A

  Malnutrition is a frequent feature in Crohns disease (CD), affects patient outcome and must be recognised. […] We aimed to design and evaluate a new screening tool that combines both malnutrition and inflammation parameters that might help predict clinical outcome. […] At 6 months, MIRT significantly predicted outcome in numerous nutritional and clinical parameters (SGA, CD-related flares, hospitalisations and surgeries). […] The newly developed MIRT was found to reliably predict clinical outcome in CD patients. […] This screening tool might be used to facilitate clinical decision making, including treatment of both inflammation and malnutrition in order to prevent complications. […] The prevalence of malnutrition at baseline and after 6 months was 216 %, which is in accordance with previous studies examining nutritional status of CD patients in remission. […] The nutritional parameter with the highest associations with clinical outcome in our study was unintentional weight loss. […] MIRT predicted clinical outcome in CD patients at 6 months.

• #10 Construction and validation of a predictive model for the risk of malnutrition in hospitalized patients over 65 years of age with malignant tumours: a single-centre retrospective cross-sectional study [PeerJ]

  https://peerj.com/articles/18685/

  Nutritional status is a critical indicator of overall health in individuals suffering from malignant tumours, reflecting the complex interplay of various contributing factors. This research focused on identifying and analysing the factors influencing malnutrition among older patients aged 65 with malignant tumours and aimed to develop a comprehensive risk model for predicting malnutrition. […] Malnutrition has been identified as an independent risk factor affecting the prognosis of patients with malignant tumours. […] The predictive model exhibited areas under the curve (AUC) of 0.793 (95% confidence interval (CI) [0.7760.810]) for the development cohort and 0.832 (95% CI [0.8010.863]) for the validation cohort. […] This study successfully devised a straightforward and efficient prediction model for malnutrition among older patients aged 65 and above with malignant tumours. The model represents a significant advancement as a clinical tool for identifying individuals at high risk of malnutrition, enabling early intervention with targeted nutritional support and improving patient outcomes.

• #11 Construction and validation of a predictive model for the risk of malnutrition in hospitalized patients over 65 years of age with malignant tumours: a single-centre retrospective cross-sectional study [PeerJ]

  https://peerj.com/articles/18685/

  Our findings revealed that 40.42% of hospitalized patients with malignancies were malnourished, consistent with the rates reported in studies by Arends et al. (2017) and Cederholm et al. (2019). […] Multivariate logistic regression analysis identified several significant risk factors for malnutrition, including age, TNM stage, presence of digestive system tumours, KPS, alcohol consumption, combined thoracic and abdominal fluid effusion, HGB and Cr levels, and the NLR. […] The proposed nomogram offers significant predictive value for clinical practice.

• #12 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text

  https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3

  This study aimed to evaluate the prognostic impact of nutritional and inflammatory measures (controlling nutritional status (CONUT) score, prognostic nutritional index (PNI), and modified Glasgow prognostic score (mGPS)) on overall survival (OS) in patients with stage IV colorectal cancer (CRC). […] After adjusting for known factors (age, gender, BMI, ECOG performance status, location of primary tumor, CEA levels, histological type, M category, and prior surgical treatment), all three measures were found to be independent prognostic factors for OS in patients with stage (CONUT score, p0.001; PNI, p0.001; mGPS, p0.001). […] CONUT score, PNI, and mGPS were found to be independent prognostic factors for OS in patients with stage IV CRC, suggesting that nutritional and inflammatory status is a useful host-related prognostic indicator in stage IV CRC.

• #13 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text

  https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3

  In the present study, we focused on stage IV CRC including curative resected stage IV CRC and unresectable metastatic CRC, and demonstrated that CONUT score, PNI, and mGPS are independent prognostic factors for OS in patients with stage IV CRC regardless of curative potential. […] These results suggest that nutritional and inflammatory measures may be a useful prognostic indicator regardless of treatment strategies. […] The present study revealed that CONUT score, PNI, and mGPS, which consist of these factors, are strongly correlated with prognosis in stage IV CRC patients. […] CONUT score, PNI, and mGPS were all independent prognostic factors for OS in patients with stage IV CRC, suggesting that nutritional and inflammatory status is a useful host-related prognostic indicator in stage IV CRC.

• #14 Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images | Scientific Reports

  https://www.nature.com/articles/s41598-025-91825-z

  In recent times, severe acute malnutrition (SAM) in India is considered a serious issue as per UNICEF 2022 records. […] This research utilizes an artificial intelligence-based image segmentation technique to predict malnutrition in children. […] The primary goal of this research is to use a deep learning model to eliminate the need for multiple manual diagnostic tests and simplify the prediction of malnutrition in kids. […] The model is 98.49% accurate in predicting the kids who are malnourished among the kids who are healthy. […] Hence, the proposed technique is effective in detecting malnutrition and diagnose it earlier, without using predictive analysis function or advice from the medical experts. […] The ResNet-based malnutrition detection model holds immense potential in healthcare facilities, where it assists clinicians in rapidly assessing a child’s nutritional status through facial images.

• #15 Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images | Scientific Reports

  https://www.nature.com/articles/s41598-025-91825-z

  This proposed ResNet-50, a 50-layer architecture, faces image segment detection. […] SAM calculations can commonly resolve malnutrition. […] The study uses the ResNet-50 deep learning model to find kids who aren’t getting enough food. […] The ResNet-50 is robust in identifying the variation of different facial images under various light conditions, and it accurately identifies malnutrition using facial images. […] The proposed model achieves high accuracy with a prediction of malnutrition and a higher residual block to get the desired result in quick response time. […] The proposed model analyzes and validates the malnutrition prediction using a facial image of children. […] The proposed study uses facial image segmentation for malnutrition analysis in kids which extract facial features like chin structure and the starting points of the nose to predict malnutrition which eliminates the medical expert need and traditional time-consuming process like BMI.

• #16 Predicting nutritional status for women of childbearing age from their economic, health, and demographic features: A supervised machine learning approach | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277738

  Malnutrition imposes enormous costs resulting from lost investments in human capital and increased healthcare expenditures. […] This paper attempts to fill out this knowledge gap by predicting the BMI and the risks of malnutrition outcomes for Bangladeshi women of childbearing age from their economic, health, and demographic features. […] Study findings demonstrate that the support vector machine and k-nearest neighbor are the two best-performing methods in BMI prediction based on the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). […] The combined predictor algorithms consistently yield top specificity, Cohens kappa, F1-score, and AUC in classifying the malnutrition status, and their performance is robust to alternative standards. […] To the best of our knowledge, this is the first study that predicts BMI and one of the pioneer studies to classify all three malnutrition outcomes for women of childbearing age in Bangladesh, let alone in any lower-middle income country, using SML techniques. […] Therefore, study findings can aid policymakers in designing policy and programmatic approaches to address the double burden of malnutrition among Bangladeshi women, thereby reducing the countrys economic burden.

• #17 Predicting the burden of acute malnutrition in drought-prone regions of Kenya: a statistical analysis | medRxiv

  https://www.medrxiv.org/content/10.1101/2025.03.19.25324283v1.full-text

  In drought-prone regions, timely and granular predictions of the burden of acute malnutrition could support decision-making. […] The study did not identify a model that could very accurately predict malnutrition burden, but analyses relying on larger datasets with a wider range of predictors and encompassing multiple drought periods may yield sufficient performance and are warranted given the potential utility and efficiency of predictive models in lieu of assumptions or expensive and untimely ground data collection. […] We identified generalized linear and, perhaps more promisingly, machine learning (random forest) models that yielded moderate predictive performance for different indicators of acute childhood malnutrition in Kenya. The models for GAM in particular could potentially be used in lieu of educated guesses to support real-time situational awareness of and decision-making on deteriorating nutrition.

• #18 Predicting the burden of acute malnutrition in drought-prone regions of Kenya: a statistical analysis | medRxiv

  https://www.medrxiv.org/content/10.1101/2025.03.19.25324283v1.full

  We identified generalized linear and, perhaps more promisingly, machine learning (random forest) models that yielded moderate predictive performance for different indicators of acute childhood malnutrition in Kenya. The models for GAM in particular could potentially be used in lieu of educated guesses to support real-time situational awareness of and decision-making on deteriorating nutrition.

• #19 Predicting the burden of acute malnutrition in drought-prone regions of Kenya: a statistical analysis | medRxiv

  https://www.medrxiv.org/content/10.1101/2025.03.19.25324283v1.full

  In drought-prone regions, timely and granular predictions of the burden of acute malnutrition could support decision-making. […] The study did not identify a model that could very accurately predict malnutrition burden, but analyses relying on larger datasets with a wider range of predictors and encompassing multiple drought periods may yield sufficient performance and are warranted given the potential utility and efficiency of predictive models in lieu of assumptions or expensive and untimely ground data collection. […] Knowing the population burden (prevalence) of acute malnutrition serves multiple purposes, including the selection of appropriately scaled food security, nutritional and health interventions (e.g. cash transfers; blanket feeding distributions; management of severe and/or moderate malnutrition), resource mobilisation, logistical planning for an expected incident level of cases and monitoring of an ongoing response.

• #20 Malnutrition in Hospitalized Adults | Effective Health Care (EHC) Program

  https://effectivehealthcare.ahrq.gov/products/malnutrition-hospitalized-adults/protocol

  Malnutrition among hospitalized patients remains a serious issue affecting more than 30 percent of hospitalized patients in the United States. Malnutrition is associated with high mortality and morbidity, functional decline, prolonged hospital stays, and increased health care costs. Post discharge, malnourished patients are also at risk for more frequent re-admissions. According to an Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) Statistical Brief, 30-day all cause readmission was nearly 50% higher among patients with malnutrition compared to patients with no associated malnutrition. Early identification and treatment of malnutrition are critical to prevent poor outcomes in hospitalized adult patients. The purpose of this systematic review is to support the efforts of the panel by identifying published literature that will help clearly establish the association between malnutrition and clinical outcomes among hospitalized patients, particularly those who may be at greater risk. This review will also evaluate the effectiveness of screening and/or diagnostic assessment of malnutrition on diagnosis, treatment, and clinical outcomes of hospitalized patients. Ultimately, the findings of this review will aid in the development of quality measures that will reduce malnutrition in hospitalized adults and lead to improvements in clinical outcomes.

• #21 Malnutrition Screening and Assessment

  https://www.mdpi.com/2072-6643/14/12/2392

  However, malnutrition is preventable if the problem is diagnosed early. […] A systematic approach to addressing malnutrition in hospitals should begin with a nutritional risk assessment of all patients at admission, followed by a detailed assessment of the nutritional status of patients most at risk. […] An appropriate nutritional intervention, tailored to the individual needs of patients identified as malnourished or at nutritional risk, should be implemented. […] The aim of this review is to show the most widely used methods for nutritional screening to identify individuals at risk of malnutrition with different diseases, and the methods then used for the assessment of the nutritional status of the at-risk patients. […] Malnutrition continues to be an under-recognized, under-diagnosed, and, hence, under-treated problem.

• #22 Malnutrition Screening and Assessment

  https://www.mdpi.com/2072-6643/14/12/2392

  Malnutrition affects large numbers of patients, particularly the very frail, such as elderly patients, patients with a chronic inflammatory process such as cancer or other kidney, respiratory, or heart diseases, and those with an acute inflammatory process, such as critical or surgical patients. […] For this reason, early detection must be a systematic objective pursued as soon as the relationship is established between the social or the healthcare system and the individual, as adequate nutritional intervention is shown to reduce mortality and complications in hospitalized patients. […] Nutritional assessment initiatives are essential for optimal nutrition care.

• #23 Geriatric patients diagnosed in PCC with malnutrition | CIA

  https://www.dovepress.com/prediction-of-prognosis-in-geriatric-palliative-care-patients-with-dia-peer-reviewed-fulltext-article-CIA

  Malnutrition is very commonly encountered in palliative care centers (PCC), especially in geriatric patients. It is known that development of malnutrition increases morbidity and mortality. In this study, we aimed to investigate the effectiveness of commonly used nutritional assessment parameters in predicting prognosis in geriatric patients diagnosed in PCC with malnutrition. […] We found that BMI had no prognostic predictive effects in geriatric PCC patients with malnutrition. We concluded that NRS-2002 and high CRP and low albumin and prealbumin can be used to predict mortality. In addition, we found that low albumin indicates a poor prognosis and predicts patients to be transferred to ICU. […] Our results showed that; BMI has no prognostic predictive effect, high NRS-2002 and CRP and low albumin and prealbumin levels can be used to predict mortality, and low albumin indicates poor prognosis and can predict patients who will be transferred to the ICU.

• #24 Geriatric patients diagnosed in PCC with malnutrition | CIA

  https://www.dovepress.com/prediction-of-prognosis-in-geriatric-palliative-care-patients-with-dia-peer-reviewed-fulltext-article-CIA

  In our study, we found that low albumin level is a risk factor for mortality. In addition, it was shown in various studies that low albumin level is associated with poor prognosis. […] We also found that a decrease in ALB level below 2.44 increased the rate of transfer to the ICU by 2.12 times, and a decrease below 2.56 increased mortality 2.08 times. […] We concluded that high NRS-2002 and CRP, and low albumin and prealbumin levels can be used to predict mortality in patients diagnosed with malnutrition aged 65 years in PCC. We found that low albumin also indicates a poor prognosis and can predict patients who will be transferred to the ICU.

• #25 Establishing a Prediction Model for Weight Loss Outcomes After LSG in | DMSO

  https://www.dovepress.com/establishing-a-prediction-model-for-weight-loss-outcomes-after-lsg-in–peer-reviewed-fulltext-article-DMSO

  In obese Chinese patients with a BMI 32.5 kg/m2, the Inbody-based nomogram integrating REE/BW, FFMI, and WC offers an effective preoperative tool for predicting weight loss outcomes one year after LSG, facilitating surgical planning and postoperative management. […] The preoperative resting energy expenditure to body weight ratio (REE/BW), fat-free mass index (FFMI), and waist circumference (WC) emerged as independent predictive factors for weight loss outcomes at one year post-LSG. […] This study aims to identify key body composition indicators that can predict weight loss outcomes in Chinese patients undergoing LSG and to establish a preoperative predictive model, providing valuable insights for clinical decision-making by bariatric surgeons. […] The five most influential variables were subsequently included in a multivariate logistic regression model, which indicated that REE/BW, FFMI, and WC were independent predictors of weight loss outcomes. […] This study developed a preoperative predictive model for weight loss outcomes following LSG by integrating three key indicators: REE/BW, FFMI, and WC.

• #26 Malnutrition in Hospitalized Adults | Effective Health Care (EHC) Program

  https://effectivehealthcare.ahrq.gov/products/malnutrition-hospitalized-adults/protocol

  Proper diagnosis of malnutrition is essential to identifying and utilizing appropriate interventions. However, diagnosing malnutrition is challenging in certain populations, such as patients with obesity and/or sarcopenia. […] The GLIM taskforce recommended a two-step approach to identifying malnutrition that involves 1) screening for malnutrition using a valid tool, and 2) performing a formal diagnostic assessment. […] The framework begins with a rectangle that depicts the population of interest, which for all key questions is hospitalized patients. […] The questions in this review underpin the pathway of care that links patients at risk of malnutrition to clinical outcomes.

• #27 Malnutrition Screening and Assessment

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9228435/

  Nutritional assessment is the ideal process to identify patients requiring nutritional support, however, it is time consuming to complete. Nutritional screening tools are useful for the rapid and early identification of malnutrition, but need to be paired with nutritional assessment for accurate malnutrition identification.

• #28 Malnutrition Screening and Assessment

  https://www.mdpi.com/2072-6643/14/12/2392

  Nutritional screening is defined in a similar way according to both the American Society of Parenteral and Enteral Nutrition (ASPEN) and the European Society for Clinical Nutrition and Metabolism (ESPEN): as a process to identify an individual who is malnourished, or at risk of malnutrition, to determine if a detailed nutritional assessment is required. […] Nutritional risk detection tools are of major help in the daily routine to detect potential or manifested malnutrition in a timely fashion. […] The choice of screening method depends on the available infrastructure and resources, the possibility of automation, and the healthcare setting, among others. […] Although a wide range of tools, such as imaging, and functional and biological markers for malnutrition, are available, the objective measurement of the malnutrition domains is hampered by limitations intrinsic to the screening and assessment tools.

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