The understanding of phenylketonuria (PKU), guidelines, and treatment landscape have evolved dramatically over the decades since newborn screen implementation. We capture this rich history from the stories and experiences of a multidisciplinary provider team from Boston Children\'s Hospital\'s PKU Clinic, who treated PKU from the early years of newborn screening and who worked together for over 40 years.

OBJECTIVE: Hospitalized patients often have acute kidney disease (AKD) or chronic kidney disease (CKD), with important metabolic and nutritional consequences. Moreover, in case kidney replacement therapy (KRT) is started, the possible impact on nutritional requirements cannot be neglected. On this regard, the present guideline aims to provide evidence-based recommendations for clinical nutrition in hospitalized patients with KD.
METHODS: The standard operating procedure for ESPEN guidelines was used. Clinical questions were defined in both the PICO format, and organized in subtopics when needed, and in non-PICO questions for the more general topics. The literature search was from January 1st, 1999 until January 1st, 2020. Each question led to one or more recommendation/statement and related commentaries. Existing evidence was graded, as well as recommendations and statements were developed and agreed upon in a multistage consensus process.
RESULTS: The present guideline provides 32 evidence-based recommendations and 8 statements, defining how to assess nutritional status, how to define patients at risk, how to choose the route of feeding, and how to integrate nutrition with KRT. In the final online voting, a strong consensus was reached in 84% at least of recommendations and 100% of statements.
CONCLUSIONS: The presence of KD in hospitalized patients identifies a highly heterogeneous group of subjects with widely varying nutrient needs and intakes. Considering the high nutritional risk related with this clinical condition, an individualized approach consisting of nutritional status evaluation and monitoring, frequent evaluation of nutritional requirements, and careful integration with KRT should be planned to avoid both underfeeding and overfeeding. Practical recommendations and statements were developed, aiming at defining suggestions for everyday clinical practice in the individualization of nutritional support in this patient setting. Literature areas with scarce or without evidence were also identified, thus requiring further basic or clinical research.

BACKGROUND: Type-2 Diabetes Mellitus (T2D) is a growing concern worldwide, and family doctors are called to help diabetic patients manage this chronic disease, also with Medical Nutrition Therapy (MNT). However, MNT for Diabetes is usually standardized, while it would be much more effective if tailored to the patient. There is a gap in patient-tailored MNT which, if addressed, could support family doctors in delivering effective recommendations. In this context, decision support systems (DSSs) are valuable tools for physicians to support MNT for T2D patients - as long as DSSs are transparent to humans in their decision-making process. Indeed, the lack of transparency in data-driven DSS might hinder their adoption in clinical practice, thus leaving family physicians to adopt general nutrition guidelines provided by the national healthcare systems.
METHODS: This work presents a prototypical ontology-based clinical Decision Support System (OnT2D- DSS) aimed at assisting general practice doctors in managing T2D patients, specifically in creating a tailored dietary plan, leveraging clinical expert knowledge. OnT2D-DSS exploits clinical expert knowledge formalized as a domain ontology to identify a patient\'s phenotype and potential comorbidities, providing personalized MNT recommendations for macro- and micro-nutrient intake. The system can be accessed via a prototypical interface.
RESULTS: Two preliminary experiments are conducted to assess both the quality and correctness of the inferences provided by the system and the usability and acceptance of the OnT2D-DSS (conducted with nutrition experts and family doctors, respectively).
CONCLUSIONS: Overall, the system is deemed accurate by the nutrition experts and valuable by the family doctors, with minor suggestions for future improvements collected during the experiments.

BACKGROUND: For hospitalized adults, it is important to initiate the early reintroduction of oral food in accordance with nutrition support team guidelines. The aim of this study was to develop and validate a machine learning-based algorithm that predicts the early termination of medical nutritional therapy (the transition to oral feeding).
METHODS: This retrospective cohort study included consecutive adult patients admitted to the Hacettepe hospital (from 1 January 2018 to 31 December 2022). The outcome of the study was the prediction of an early transition to adequate oral feeding before discharge. The dataset was randomly (70/30) divided into training and test datasets. We used six ML algorithms with multiple features to construct prediction models. ML model performance was measured according to the accuracy, area under the receiver operating characteristic curve, and F1 score. We used the Boruta Method to determine the important features and interpret the selected features.
RESULTS: A total of 2298 adult inpatients who were followed by a nutrition support team for medical nutritional therapy were included. Patients received parenteral nutrition (1471/2298, 64.01%), enteral nutrition (717/2298, 31.2%), or supplemental parenteral nutrition (110/2298, 4.79%). The median (interquartile range) Nutritional Risk Screening (NRS-2002) score was 5 (1). Six prediction algorithms were used, and the artificial neural network and elastic net models achieved the greatest area under the ROC in all outcomes (AUC = 0.770). Ranked by z-value, the 10 most important features in predicting an early transition to oral feeding in the artificial neural network and elastic net algorithms were parenteral nutrition, surgical wards, surgical outcomes, enteral nutrition, age, supplemental parenteral nutrition, digestive system diseases, gastrointestinal complications, NRS-2002, and impaired consciousness.
CONCLUSIONS: We developed machine learning models for the prediction of an early transition to oral feeding before discharge. Overall, there was no discernible superiority among the models. Nevertheless, the artificial neural network and elastic net methods provided the highest AUC values. Since the machine learning model is interpretable, it can enable clinicians to better comprehend the features underlying the outcomes. Our study could support personalized treatment and nutritional follow-up strategies in clinical decision making for the prediction of an early transition to oral feeding in hospitalized adult patients.

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Malnutrition plays a crucial role as a risk factor in patients undergoing major abdominal surgery. To mitigate the risk of complications, nutritional prehabilitation has been recommended for malnourished patients and those at severe metabolic risk. Various approaches have been devised, ranging from traditional short-term conditioning lasting 7-14 days to longer periods integrated into a comprehensive multimodal prehabilitation program. However, a significant challenge is the considerable heterogeneity of nutritional interventions, leading to a lack of clear, synthesizable evidence for specific dietary recommendations. This narrative review aims to outline the concept of nutritional prehabilitation, offers practical recommendations for clinical implementation, and also highlights the barriers and facilitators involved.

Nutritional interventions are a key component of type 2 diabetes management; making health-supporting changes in eating patterns can improve postprandial glycemic excursions and lower HbA1c to reduce diabetes-related morbidity and mortality. Research around implementing calorie-restricted and/or low-carbohydrate diets is plentiful, though the ability to sustain physiologic and behavioral changes for longer than 12 months is a concern. An understanding of intervention goals and adherence is needed to apply this research to patient care and translate expectations to real-world living contexts. Diverse dietary patterns including a Mediterranean eating pattern, vegetarian or plant-based eating pattern, or others that emphasize high-quality carbohydrates (e.g., whole grains), vegetables, whole fruits, legumes, and fish can support achievement of glycemic targets. Counseling strategies like motivational interviewing can be used to build eating competence. These approaches prioritize collaborative decision-making with the goal of increasing patient empowerment and self-efficacy. Strategies for incorporating these tools and frameworks in a clinical setting are highlighted. Providing ongoing diabetes and nutrition education, paired with appropriate support to address the challenges in implementing and sustaining behavior changes, is warranted. Further, social determinants of health including environmental context, education, socioeconomic status, access to healthcare, and experiences of systemic stigma (e.g., racism or weight bias) can interfere with individuals\' diabetes self-care and nutrition behaviors. Providing medical nutrition therapy and tailoring nutrition interventions to individual needs and circumstances can be an important way physicians, dietitians, and diabetes providers can support individuals with type 2 diabetes.

BACKGROUND: Food as medicine (FAM) interventions have been associated with improved health outcomes. However, there is limited FAM evidence in food retail settings.
OBJECTIVE: The objective was to evaluate the feasibility of a registered dietitian nutritionist-led FAM program that aims to detect changes in participants\' nutrition problems and related nutrition and health outcomes, as documented by the Nutrition Care Process framework.
METHODS: The study was a descriptive feasibility nutrition intervention cohort analysis.
UNASSIGNED: A convenience sample of online food shoppers were enrolled in collaboration with a food retail chain (n = 39 participants completed the intervention and were included in primary analyses).
METHODS: Participants received nutrition care for 6 months either in person or via telehealth. The FAM intervention included tailored nutrition care that integrated software-generated meal plans and food shopping lists to support online food shopping.
METHODS: Progress of nutrition problems and diet quality (assessed via the Picture your Plate survey) were measured. Measurements included changes in anthropometric and biochemical parameters, blood pressure, and quality of life (assessed via the Centers for Disease Control and Prevention\'s Health Related Quality of Life-14 survey).
METHODS: Mann-Whitney U test, Pearson\'s χ2, and Wilcoxon signed-rank tests were used to detect differences.
RESULTS: The most prevalent nutrition problems demonstrated improvement rates as follows: excessive energy intake, 81% (n = 21 of 26); excessive carbohydrate intake, 88% (n = 7 of 8); and obesity, 100% (n = 5 of 5). Exposure to the FAM intervention improved dietary quality, quality of life, body weight, waist circumference, and systolic pressure.
CONCLUSIONS: FAM interventions can be carried out by in-store registered dietitian nutritionists in the supermarket setting. This feasibility study highlighted the need and opportunity for larger studies in which registered dietitian nutritionist-led FAM interventions, in collaboration with food retailers, may improve people\'s nutrition and health.

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OBJECTIVE: The purpose of this study was to assess participants\' perceptions and experiences while participating in a Food is Medicine medically tailored meal plus intensive nutrition counseling intervention to create a theoretical explanation about how the intervention worked.
METHODS: This interpretive qualitative study included the use of semi-structured interviews with active participants in a randomized controlled trial aimed at understanding how a medically tailored meal plus nutrition counseling intervention worked for vulnerable individuals with lung cancer treated at four cancer centers across the USA. During the 8-month long study, participants in the intervention arm were asked to be interviewed, which were recorded, transcribed verbatim, and analyzed using conventional content analysis with principles of grounded theory.
RESULTS: Twenty individuals participated. Data analysis resulted in a theoretical explanation of the intervention\'s mechanism of action. The explanatory process includes three linked and propositional categories leading to patient resilience: engaging in treatment, adjusting to diagnosis, and active coping. The medically tailored meals plus nutrition counseling engaged participants throughout treatment, which helped participants adjust to their diagnosis, leading to active coping through intentional self-care, behavior change, and improved quality of life.
CONCLUSIONS: These findings provide evidence that a Food is Medicine intervention may buffer some of the adversity related to the diagnosis of lung cancer and create a pathway for participants to experience post-traumatic growth, develop resilience, and change behaviors to actively cope with lung cancer. Medically tailored meals plus intensive nutrition counseling informed by motivational interviewing supported individuals\' adjustment to their diagnosis and resulted in perceived positive behavior change.