Trigonelline is an NAD+ precursor that improves muscle function during ageing and is reduced in human sarcopenia.

Mitochondrial dysfunction and low nicotinamide adenine dinucleotide (NAD+) levels are hallmarks of skeletal muscle ageing and sarcopenia1-3, but it is unclear whether these defects result from local changes or can be mediated by systemic or dietary cues. Here we report a functional link between circulating levels of the natural alkaloid trigonelline, which is structurally related to nicotinic acid4, NAD+ levels and muscle health in multiple species. In humans, serum trigonelline levels are reduced with sarcopenia and correlate positively with muscle strength and mitochondrial oxidative phosphorylation in skeletal muscle. Using naturally occurring and isotopically labelled trigonelline, we demonstrate that trigonelline incorporates into the NAD+ pool and increases NAD+ levels in Caenorhabditis elegans, mice and primary myotubes from healthy individuals and individuals with sarcopenia. Mechanistically, trigonelline does not activate GPR109A but is metabolized via the nicotinate phosphoribosyltransferase/Preiss-Handler pathway5,6 across models. In C. elegans, trigonelline improves mitochondrial respiration and biogenesis, reduces age-related muscle wasting and increases lifespan and mobility through an NAD+-dependent mechanism requiring sirtuin. Dietary trigonelline supplementation in male mice enhances muscle strength and prevents fatigue during ageing. Collectively, we identify nutritional supplementation of trigonelline as an NAD+-boosting strategy with therapeutic potential for age-associated muscle decline.

The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODTM.

A healthy diet can help to prevent or manage many important conditions and diseases, particularly obesity, malnutrition, and diabetes. Recent advancements in artificial intelligence and smartphone technologies have enabled applications to conduct automatic nutritional assessment from meal images, providing a convenient, efficient, and accurate method for continuous diet evaluation. We now extend the goFOODTM automatic system to perform food segmentation, recognition, volume, as well as calorie and macro-nutrient estimation from single images that are captured by a smartphone. In order to assess our system's performance, we conducted a feasibility study with 50 participants from Switzerland. We recorded their meals for one day and then dietitians carried out a 24 h recall. We retrospectively analysed the collected images to assess the nutritional content of the meals. By comparing our results with the dietitians' estimations, we demonstrated that the newly introduced system has comparable energy and macronutrient estimation performance with the previous method; however, it only requires a single image instead of two. The system can be applied in a real-life scenarios, and it can be easily used to assess dietary intake. This system could help individuals gain a better understanding of their dietary consumption. Additionally, it could serve as a valuable resource for dietitians, and could contribute to nutritional research.

Home-based cooking intervention with a smartphone app to improve eating behaviors in children aged 7-9 years: a feasibility study.

Objective: To develop and evaluate the feasibility of a mobile application in Swiss households and assess its impact on dietary behavior and food acceptability between children who cooked with limited parental support (intervention group) with children who were not involved in cooking (control group). Methods: A ten-week randomized controlled trial was conducted online in 2020. Parents were given access to a mobile-app with ten recipes. Each recipe emphasized one of two generally disliked foods (Brussels sprouts or whole-meal pasta). Parents photographed and weighed the food components from the child's plate and reported whether their child liked the meal and target food. The main outcome measures were target food intake and acceptability analyzed through descriptive analysis for pre-post changes. Results: Of 24 parents who completed the baseline questionnaires, 18 parents and their children (median age: 8 years) completed the evaluation phase. Mean child baseline Brussel sprouts and whole-meal pasta intakes were 19.0 ± 24.2 g and 86.0 ± 69.7 g per meal, respectively. No meaningful differences in intake were found post-intervention or between groups. More children reported a neutral or positive liking towards the whole-meal pasta in the intervention group compared to those in the control group. No change was found for liking of Brussel sprouts. Conclusions for practice: The intervention was found to be feasible however more studies on larger samples are needed to validate feasibility. Integrating digital interventions in the home and promoting meal preparation may improve child reported acceptance of some healthy foods. Using such technology may save time for parents and engage families in consuming healthier meals.

Assessing the Quality of Simulated Food Patterns with Reduced Animal Protein Using Meal Data from NHANES 2017-2018.

The nutritional consequences of progressively replacing meat products with plant-based foods need to be systematically evaluated. Modeling analyses provide insights into the predicted food consumption and nutritional adequacy of plant-based diets. We developed a novel methodology to simulate food patterns and evaluate diet quality. Meal data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 was used to create 100 7-day meal plans subject to various nutrient and food group optimization criteria. Omnivore (reference diet), flexitarian, pescatarian, and vegetarian food patterns were modeled using mixed integer linear programming. The modeled food patterns used the 25th and 75th percentiles of the US Usual Dietary Intakes to set the optimization constraints. The diet quality was determined using the Healthy Eating Index 2015 (HEI-2015). The modeled vegetarian, pescatarian, and flexitarian food patterns outperformed the omnivore diet on the HEI-2015, with the vegetarian pattern achieving the highest score (82 for females, 78 for males). Modeled flexitarian patterns, with a 25 to 75% reduction in animal protein, offer viable options for those seeking to reduce but not eliminate their animal protein intake while supporting the transition from omnivore to fully plant-based diets. This methodology could be applied to evaluate the nutrient and diet quality of different dietary patterns with various constraints.

MEDPass versus conventional administration of oral nutritional supplements - A randomized controlled trial comparing coverage of energy and protein requirements.

BACKGROUND & AIMS: The use of oral nutritional supplements (ONS) in the hospital setting is important to reach individual protein and energy goals in patients at risk for malnutrition. Compliance with ONS can be challenging but may be improved by prescribing ONS in smaller portions with medication rounds (MEDPass). We compared the likelihood of meeting energy and protein requirements in patients receiving ONS with MEDPass versus conventional ONS administration. METHODS: The MEDPass Trial is a randomized, controlled, open-label superiority trial conducted on medical and geriatric wards in a University Hospital in Switzerland. The MEDPass group was allocated to receive 50 ml of ONS four times per day with the medication rounds. The control group received ONS per conventional care between the meals. The primary outcome was the percentage of energy in relation to the individual requirement. Secondary outcomes included the coverage of protein intake in relation to the individual requirement, the amount of daily consumed ONS, the course of handgrip strength (HGS), body weight appetite and nausea. Furthermore, we compared 30-day mortality and hospital length of stay (LOS) was studied in medical patients. RESULTS: From November 22nd, 2018 until November 30th, 2021, 204 patients were included in the trial (MEDPass group n = 100, control group n = 104). A total of 203 patients at nutritional risk were analyzed in the intention-to-treat analysis (ITT). Regarding the primary endpoint, there was no difference in the coverage of energy requirement between the MEDPass and control group (82 vs. 85% (Δ -3%, 95%CI -11 to 4%), p = 0.38). Similarly, no differences were found for the secondary outcomes including coverage of protein requirement (101 vs. 104% (Δ -3%, 95% CI -12 -7%), p = 0.57, average daily intake of ONS (170 vs 173 ml (Δ - 3 ml, 95% CI -14 to 8 ml), p = 0.58) and 30-day mortality (3 vs. 8 patients, OR 0.4 (95% CI 0.1-1.4), p = 0.15). The course of HGS, body weight, appetite and nausea did not differ between the groups (p = 0.29, p = 0.14, p = 0.65 and p = 0.94, respectively). The per protocol analysis including 178 patients showed similar results. CONCLUSION: Within this controlled trial setting, we found a high compliance for ONS intake and high coverage of protein requirements but no further improvement when ONS was administered using MEDPass compared to conventional care. MEDPass administration may provide an alternative that is easy to integrate into nursing routines, which may lead to lower workload with cost benefits and reduction of food waste. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03761680.

Multimedia Data-Based Mobile Applications for Dietary Assessment.

Diabetes mellitus (DM) and obesity are chronic medical conditions associated with significant morbidity and mortality. Accurate macronutrient and energy estimation could be beneficial in attempts to manage DM and obesity, leading to improved glycemic control and weight reduction, respectively. Existing dietary assessment methods are subject to major errors in measurement, are time consuming, are costly, and do not provide real-time feedback. The increasing adoption of smartphones and artificial intelligence, along with the advances in algorithms and hardware, allowed the development of technologies executed in smartphones that use food/beverage multimedia data as an input, and output information about the nutrient content in almost real time. Scope of this review was to explore the various image-based and video-based systems designed for dietary assessment. We identified 22 different systems and divided these into three categories on the basis of their setting for evaluation: laboratory (12), preclinical (7), and clinical (3). The major findings of the review are that there is still a number of open research questions and technical challenges to be addressed and end users-including health care professionals and patients-need to be involved in the design and development of such innovative solutions. Last, there is a clear need that these systems should be validated under unconstrained real-life conditions and that they should be compared with conventional methods for dietary assessment.

A feasibility study to assess Mediterranean Diet adherence using an AI-powered system.

Mediterranean diet (MD) can play a major role in decreasing the risks of non-communicable diseases and preventing overweight and obesity. In order for a person to follow the MD and assess their adherence to it, proper dietary assessment methods are required. We have developed an Artificial Intelligence-powered system that recognizes the food and drink items from a single meal photo and estimates their respective serving size, and integrated it into a smartphone application that automatically calculates MD adherence score and outputs a weekly feedback report. We compared the MD adherence score of four users as calculated by the system versus an expert dietitian, and the mean difference was 3.5% and statistically not significant. Afterwards, we conducted a feasibility study with 24 participants, to evaluate the system's performance and to gather the users' and dietitians' feedback. The image recognition system achieved 61.8% mean Average Precision for the testing set and 57.3% for the feasibility study images (where the ground truth was taken as the participants' annotations). The feedback from the participants of the feasibility study was also very positive.

Association between hepatic steatosis and fibrosis indices and dietary habits, physical activity, and quality of life.

BACKGROUND AND STUDY AIMS: This cross-sectional study aimed to evaluate the association between hepatic steatosis and fibrosis indices and adherence to the Mediterranean diet (MD), physical activity (PA), and quality of life (QoL) in individuals unaware of the status of their liver. PATIENTS AND METHODS: Participants were asked to complete three questionnaires validated in Greek, namely: (1) the Chronic Liver Disease Questionnaire (CLDQ) for QoL assessment; (2) the semi-quantitative Food Frequency Questionnaire (FFQ), from which the MedDietScore was calculated; and (3) the International Physical Activity Questionnaire (IPAQ) for PA evaluation. Hepatic steatosis was evaluated using the Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), and Lipid Accumulation Product (LAP). Hepatic fibrosis was evaluated using the NAFLD Fibrosis Score (NFS), Fibrosis-4 (FIB-4), and AST-to-platelet ratio index (APRI). RESULTS: This study recruited 200 participants (90% men) aged 36 ± 6 years. Hepatic steatosis indices were not associated with MedDietScore and QoL. In terms of PA, univariable analysis showed that higher values of hepatic steatosis indices were associated with less intense activity. This association remained significant only for HSI during multivariable analysis (moderate activity vs. low activity: beta: -2.0, 95% confidence interval (CI): -3.5, -0.37, p = 0.016; and high activity vs. low activity: beta: -3.3, 95% CI: -5.03, -1.60, p < 0.001), after controlling for age, waist circumference, and the presence of metabolic syndrome. When using hepatic fibrosis indices, none of the participants had high probability of advanced hepatic fibrosis or cirrhosis (F3-F4). Consequently, we were unable to extensively evaluate the association between hepatic fibrosis indices and lifestyle characteristics or QoL. CONCLUSION: We showed that HSI, but not other steatosis indices, remained robustly associated with PA after adjusting for potential confounders in a population unaware of the presence of fatty liver.

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for dietary assessment that can be used for the identification and management of malnourished hospitalised patients. In this study, we propose an automated Artificial Intelligence (AI)-based system that receives input images of the meals before and after their consumption and is able to estimate the patient's energy, carbohydrate, protein, fat, and fatty acids intake. The system jointly segments the images into the different food components and plate types, estimates the volume of each component before and after consumption, and calculates the energy and macronutrient intake for every meal, based on the kitchen's menu database. Data acquired from an acute geriatric hospital as well as from our previous study were used for the fine-tuning and evaluation of the system. The results from both our system and the hospital's standard procedure were compared to the estimations of experts. Agreement was better with the system, suggesting that it has the potential to replace standard clinical procedures with a positive impact on time spent directly with the patients.

Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study.

BACKGROUND: Digital technologies have evolved dramatically in recent years, finding applications in a variety of aspects of everyday life. Smartphones and mobile apps are being used for a steadily increasing number of tasks, including health monitoring. A large number of nutrition and diet apps are available, and some of them are very popular in terms of user downloads, highlighting a trend toward diet monitoring and assessment. OBJECTIVE: We sought to explore the perspectives of end users on the features, current use, and acceptance of nutrition and diet mHealth apps with a survey. We expect that this study can provide user insights to assist researchers and developers in achieving innovative dietary assessments. METHODS: A multidisciplinary team designed and compiled the survey. Before its release, it was pilot-tested by 18 end users. A 19-question survey was finally developed and was translated into six languages: English, German, French, Spanish, Italian, and Greek. The participants were mainly recruited via social media platforms and mailing lists of universities, university hospitals, and patient associations. RESULTS: A total of 2382 respondents (1891 female, 79.4%; 474 male, 19.9%; and 17 neither, 0.7%) with a mean age of 27.2 years (SD 8.5) completed the survey. Approximately half of the participants (1227/2382, 51.5%) had used a nutrition and diet app. The primary criteria for selecting such an app were ease of use (1570/2382, 65.9%), free cost (1413/2382, 59.3%), and ability to produce automatic readings of caloric content (1231/2382, 51.7%) and macronutrient content (1117/2382, 46.9%) (ie, food type and portion size are estimated by the system without any contribution from the user). An app was less likely to be selected if it incorrectly estimated portion size, calories, or nutrient content (798/2382, 33.5%). Other important limitations included the use of a database that does not include local foods (655/2382, 27.5%) or that may omit major foods (977/2382, 41%). CONCLUSIONS: This comprehensive study in a mostly European population assessed the preferences and perspectives of potential nutrition and diet app users. Understanding user needs will benefit researchers who develop tools for innovative dietary assessment as well as those who assist research on behavioral changes related to nutrition.

Nutritional Risk Screening in Cancer Patients: The First Step Toward Better Clinical Outcome.

Disease-related malnutrition is highly prevalent among cancer patients, with 40-80% suffering from it during the course of their disease. Malnutrition is associated with numerous negative outcomes such as: longer hospital stays, increased morbidity and mortality rates, delayed wound healing, as well as decreased muscle function, autonomy and quality of life. In cancer patients, malnutrition negatively affects treatment tolerance (including anti-cancer drugs, surgery, chemo- and radiotherapy), increases side effects, causes adverse reactions, treatment interruptions, postoperative complications and higher readmission rates. Conversely, anti-cancer treatments are also known to affect body composition and impair nutritional status. Tailoring early nutritional therapy to patients' needs has been shown to prevent, treat and limit the negative consequences of malnutrition and is likely to improve overall prognosis. As the optimisation of treatment outcomes is top priority and evidence for nutritional therapy is growing, it is increasingly recognized as a significant intervention and an autonomous component of multimodal cancer care. The proactive implementation of nutritional screening and assessment is essential for patients suffering from cancer - given the interaction of clinical, metabolic, pharmacological factors with systemic inflammation; and suppressed appetite with accelerated muscle protein catabolism. At the same time, a nutritional care plan must be established, and adequate individualized nutritional intervention started rapidly. Screening tools for nutritional risk should be validated, standardized, non-invasive, quick and easy-to-use in daily clinical practice. Such tools must be able to identify patients who are already malnourished, as well as those at risk for malnutrition, in order to prevent or treat malnutrition and reduce negative outcomes. This review investigates the predictive value of commonly used screening tools, as well as the sensitivity and specificity of their individual components for improving clinical outcomes in oncologic populations. Healthcare professionals' awareness of malnutrition in cancer patients and the pertinence of early nutritional screening must be raised in order to plan the best possible intervention and follow-up during the patients' ordeal with the disease.

Energy and protein intake in medical and geriatric inpatients with MEDPass versus conventional administration of oral nutritional supplements: study protocol for the randomized controlled MEDPass Trial.

BACKGROUND: Disease-related malnutrition is highly prevalent in hospitalized medical and geriatric inpatients. It is associated with negative outcomes such as muscle wasting, decline of functional status, and increased morbidity and mortality. Oral nutritional supplements (ONS) are frequently used in nutritional therapy to increase intake. However, compliance to ONS is often limited and maybe improved by prescribing ONS in small portions timed with the medication (MEDPass). However, it is unknown whether the MEDPass administration enhances patients' total energy and protein intake. METHODS: The MEDPass Trial is a randomized, controlled, open-label superiority trial. Patients in the MEDPass group receive 50 ml of ONS four times per day, distributed with the medication rounds. Patients in the control group receive ONS between meals. The primary outcome is average daily energy intake (% of calculated daily requirement). For our power analysis, we assumed that administration of ONS in the MEDPass administration mode increases energy intake by at least 10% (i.e., by 200 kcal for an average energy requirement of 2200 kcal/day). Thus, with the inclusion of 200 patients, this trial has 80% power to demonstrate that intervention group patients have an average intake of 2200 kcal/day (SD 500 kcal) versus 2000 kcal/day (SD 500 kcal) in control group patients. Energy and protein intakes from ONS and all food consumed are monitored continuously throughout the hospital stay and are statistically compared to the patient's requirements. Secondary outcomes include average daily protein intake (% of calculated daily requirement), average intake of ONS/day, the course of body weight, handgrip strength, appetite, and nausea. Furthermore, hospital length of stay and 30-day mortality are assessed. The primary statistical analysis will be performed as an intention-to-treat analysis adjusted for the stratification factors used in randomization. DISCUSSION: To our knowledge, this is the first randomized controlled trial assessing total energy and protein intake for the entire hospitalization period in patients receiving MEDPass versus conventional ONS administration. Thus, the MEDPass Trial will fill a gap and answer this relevant clinical question. TRIAL REGISTRATION: ClinicalTrials.gov NCT03761680 . Registered on 3 December 2018. Kofam.ch SNCTP000003191 . Registered on 15 October 2018.

The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App.

BACKGROUND: Technological advancements have enabled nutrient estimation by smartphone apps such as goFOOD. This is an artificial intelligence-based smartphone system, which uses food images or video captured by the user as input and then translates these into estimates of nutrient content. The quality of the data is highly dependent on the images the user records. This can lead to a major loss of data and impaired quality. Instead of removing these data from the study, in-depth analysis is needed to explore common mistakes and to use them for further improvement of automated apps for nutrition assessment. OBJECTIVE: The aim of this study is to analyze common mistakes made by participants using the goFOOD Lite app, a version of goFOOD, which was designed for food-logging, but without providing results to the users, to improve both the instructions provided and the automated functionalities of the app. METHODS: The 48 study participants were given face-to-face instructions for goFOOD Lite and were asked to record 2 pictures (1 recording) before and 2 pictures (1 recording) after the daily consumption of each food or beverage, using a reference card as a fiducial marker. All pictures that were discarded for processing due to mistakes were analyzed to record the main mistakes made by users. RESULTS: Of the 468 recordings of nonpackaged food items captured by the app, 60 (12.8%) had to be discarded due to errors in the capturing procedure. The principal problems were as follows: wrong fiducial marker or improper marker use (19 recordings), plate issues such as a noncompatible or nonvisible plate (8 recordings), a combination of various issues (17 recordings), and other reasons such as obstacles (hand) in front of the camera or matching recording pairs (16 recordings). CONCLUSIONS: No other study has focused on the principal problems in the use of automatic apps for assessing nutritional intake. This study shows that it is important to provide study participants with detailed instructions if high-quality data are to be obtained. Future developments could focus on making it easier to recognize food on various plates from its color or shape and on exploring alternatives to using fiducial markers. It is also essential for future studies to understand the training needed by the participants as well as to enhance the app's user-friendliness and to develop automatic image checks based on participant feedback.

Assessing Mediterranean Diet Adherence with the Smartphone: The Medipiatto Project.

The Mediterranean diet (MD) is regarded as a healthy eating pattern with beneficial effects both for the decrease of the risk for non-communicable diseases and also for body weight reduction. In the current manuscript, we propose an automated smartphone application which monitors and evaluates the user's adherence to MD using images of the food and drinks that they consume. We define a set of rules for automatic adherence estimation, which focuses on the main MD food groups. We use a combination of a convolutional neural network (CNN) and a graph convolutional network to detect the types of foods and quantities from the users' food images and the defined set of rules to evaluate the adherence to MD. Our experiments show that our system outperforms a basic CNN in terms of recognizing food items and estimating quantity and yields comparable results as experienced dietitians when it comes to overall MD adherence estimation. As the system is novel, these results are promising; however, there is room for improvement of the accuracy by gathering and training with more data and certain refinements can be performed such as re-defining the set of rules to also be able to be used for sub-groups of MD (e.g., vegetarian type of MD).

goFOODTM: An Artificial Intelligence System for Dietary Assessment.

Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOODTM. The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food images captured by a smartphone. goFOODTM requires an input of two meal images or a short video. For conventional single-camera smartphones, the images must be captured from two different viewing angles; smartphones equipped with two rear cameras require only a single press of the shutter button. The deep neural networks are used to process the two images and implements food detection, segmentation and recognition, while a 3D reconstruction algorithm estimates the food's volume. Each meal's calorie and macronutrient content is calculated from the food category, volume and the nutrient database. goFOODTM supports 319 fine-grained food categories, and has been validated on two multimedia databases that contain non-standardized and fast food meals. The experimental results demonstrate that goFOODTM performed better than experienced dietitians on the non-standardized meal database, and was comparable to them on the fast food database. goFOODTM provides a simple and efficient solution to the end-user for dietary assessment.

What Healthcare Professionals Think of "Nutrition & Diet" Apps: An International Survey.

Accurate dietary assessment is crucial for both the prevention and treatment of nutrition-related diseases. Since mobile-based dietary assessment solutions are promising, we sought to examine the acceptability of "Nutrition and Diet" (ND) apps by Healthcare Professionals (HCP), explore their preferences on apps' features and identify predictors of acceptance. A 23 question survey was developed by an interdisciplinary team and pilot-tested. The survey was completed by 1001 HCP from 73 countries and 6 continents. The HCP (dietitians: 833, doctors: 75, nurses: 62, other: 31/females: 847, males: 150, neither: 4) had a mean age (SD) of 34.4 (10.2) years and mean job experience in years (SD): 7.7 (8.2). There were 45.5% who have recommended ND apps to their clients/patients. Of those who have not yet recommended an app, 22.5% do not know of their existence. Important criteria for selecting an app were ease of use (87.1%), apps being free of charge (72.6%) and validated (69%). Significant barriers were the use of inaccurate food composition database (52%), lack of local food composition database support (48.2%) and tech-savviness (43.3%). Although the adoption of smartphones is growing and mobile health research is advancing, there is room for improvement in the recommendation of ND apps by HCP.

Management of Refeeding Syndrome in Medical Inpatients.

Refeeding syndrome (RFS) is the metabolic response to the switch from starvation to a fed state in the initial phase of nutritional therapy in patients who are severely malnourished or metabolically stressed due to severe illness. It is characterized by increased serum glucose, electrolyte disturbances (particularly hypophosphatemia, hypokalemia, and hypomagnesemia), vitamin depletion (especially vitamin B1 thiamine), fluid imbalance, and salt retention, with resulting impaired organ function and cardiac arrhythmias. The awareness of the medical and nursing staff is often too low in clinical practice, leading to under-diagnosis of this complication, which often has an unspecific clinical presentation. This review provides important insights into the RFS, practical recommendations for the management of RFS in the medical inpatient population (excluding eating disorders) based on consensus opinion and on current evidence from clinical studies, including risk stratification, prevention, diagnosis, and management and monitoring of nutritional and fluid therapy.

Management of Dehydration in Patients Suffering Swallowing Difficulties.

Swallowing difficulties, also called dysphagia, can have various causes and may occur at many points in the swallowing process. The treatment and rehabilitation of dysphagia represent a major interdisciplinary and multiprofessional challenge. In dysphagic patients, dehydration is frequent and often accelerated as a result of limited fluid intake. This condition results from loss of water from the intracellular space, disturbing the normal levels of electrolytes and fluid interfering with metabolic processes and body functions. Dehydration is associated with increased morbidity and mortality rates. Dysphagic patients at risk of dehydration thus require close monitoring of their hydration state, and existing imbalances should be addressed quickly. This review gives an overview on dehydration, as well as its pathophysiology, risk factors, and clinical signs/symptoms in general. Available management strategies of dehydration are presented for oral, enteral, and parenteral fluid replacement.

Challenges and Perspectives in Nutritional Counselling and Nursing: A Narrative Review.

Nutritional counselling has been recognised as the first line approach in the management of numerous chronic diseases. Though usually carried out by dietitians, nutritional counselling may be used by nurses, or other healthcare professionals to improve nutritional status and meet healthcare goals. Healthcare professionals require training and education to facilitate a patient centred approach to effective counselling. Advances in digital technology have the potential to improve access to nutritional counselling for some patients such as those in primary care. However, caution is required to ensure that valuable interpersonal relationships are not lost, as these form the cornerstone of effective nutritional counselling. The aim of this narrative review is to explore aspects of effective nutritional counselling, including advances in e-counselling and areas where nursing input in nutritional counselling might enhance overall nutritional care.

Nutritional Management and Outcomes in Malnourished Medical Inpatients: Anorexia Nervosa.

BACKGROUND: Anorexia Nervosa (AN) is a psychiatric disorder characterised by a physical and psychosocial deterioration due to an altered pattern on the intake and weight control. The severity of the disease is based on the degree of malnutrition. The objective of this article is to review the scientific evidence of the refeeding process of malnourished inpatients with AN; focusing on the clinical outcome. METHODS: We conducted an extensive search in Medline and Cochrane; on April 22; 2019; using different search terms. After screening all abstracts; we identified 19 papers that corresponded to our inclusion criteria. RESULTS: The article focuses on evidence on the characteristics of malnutrition and changes in body composition; energy and protein requirements; nutritional treatment; physical activity programmes; models of organisation of the nutritional treatment and nutritional support related outcomes in AN patients. CONCLUSION: Evidence-based standards for clinical practice with clear outcomes are needed to improve the management of these patients and standardise the healthcare process.