Malnutrition is a critical complication among cancer patients, affecting up to 80% of individuals depending on cancer type, stage, and treatment. Artificial Intelligence (AI) has emerged as a promising tool in healthcare, with potential applications in nutritional management to improve early detection, risk stratification, and personalized interventions. This systematic review evaluates the role of AI in identifying and managing malnutrition in cancer patients, focusing on its effectiveness in nutritional status assessment, prediction, clinical outcomes, and body composition monitoring. A systematic search was conducted across PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, and Excerpta Medica Database from June to July 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Quantitative primary studies investigating AI-based interventions for malnutrition detection, body composition analysis, and nutritional optimization in oncology were included. Study quality was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Tools, and evidence certainty was evaluated with the Oxford Centre for Evidence-Based Medicine framework. Eleven studies (n=52,228 patients) met the inclusion criteria and were categorized into three overarching domains: Nutritional Status Assessment and Prediction, Clinical and Functional Outcomes, and Body Composition and Cachexia Monitoring. AI-based models demonstrated high predictive accuracy in malnutrition detection (AUC >0.80). Machine learning algorithms, including decision trees, random forests, and support vector machines, outperformed conventional screening tools. Deep learning models applied to medical imaging achieved high segmentation accuracy (Dice Similarity Coefficient: 0.92-0.94), enabling early cachexia detection. AI-driven virtual dietitian systems improved dietary adherence (84%) and reduced unplanned hospitalizations. AI-enhanced workflows streamlined dietitian referrals, reducing referral times by 2.4 days. AI has demonstrated significant potential in optimizing malnutrition screening, body composition monitoring, and personalized nutritional interventions for cancer patients. Its integration into oncology nutrition care could enhance patient outcomes and optimize healthcare resource allocation. Further research is necessary to standardize AI models and ensure clinical applicability. 10.17605/OSF.IO/A259M STATEMENT OF SIGNIFICANCE: This systematic review highlights the transformative potential of Artificial Intelligence in oncology nutrition by demonstrating its superior accuracy in malnutrition detection, body composition monitoring, and personalized dietary interventions. Unlike previous studies, which focused on isolated AI applications, this work comprehensively evaluates AI-driven models across multiple clinical domains, emphasizing their integration into routine cancer care to enhance early detection, treatment personalization, and overall patient outcomes.

Subcutaneous once-weekly (ow) semaglutide is a recent treatment option for type 2 diabetes (T2D) and obesity, but real-world data on weight loss and associated changes in body composition, nutrients intake, and quality of life are still scarce. This observational, prospective clinical study involved all T2D patients starting ow semaglutide according to routine care between December 2021 and February 2022. Clinical information was collected after 6 months (T6) and 12 months (T12) from semaglutide initiation (T0). Bioelectrical Impedance Analysis (BIA) was performed to measure changes in body composition. Diabetes Treatment Satisfaction Questionnaire (DTSQ) and the 36 – items Short Form Health Survey (SF-36) were administered as patient-reported outcomes (PROs). Changes in continuous endpoints (weight, body composition, nutrients intake, other clinical parameters, and PROs) were assessed using mixed models for repeated measurements. Overall, 90 patients (age 63.0 ± 10.0 years; diabetes duration 7.6 ± 5.9 years; 58.9% men; HbA1c 7.7 ± 1.1%; weight 95.4 ± 19.4 Kg, BMI 34.6 ± 6.4 Kg/m²; 36.7% naïve to diabetes treatment, 43.3% on metformin, 10.0% on dual oral therapy, and 10.0% treated with schemes including insulin) were included in the study. After 6 months from semaglutide initiation, body weight significantly decrease by -4.69 Kg (95%CI -6.19;-3.19) (primary endpoint). After 12 months, body weight was further reduced (-5.38 Kg; 95%CI -7.79;-2.97). At BIA, fat mass was significantly reduced by 2.1 Kg after 6 months but only slightly reduced after 12 months vs. baseline; lean mass was also significantly reduced by over 3 Kg both at 6 and 12 months. Intake of all nutrients declined in the first 6 months of therapy, although only lipids reduction reached the statistical significance (-6.73 g; p=0.02). Statistically significant improvements in BMI, waist circumference, glycemic control, blood pressure and lipid profile were documented. Satisfaction with treatment (DTSQ questionnaire) and mental health (MCS score of SF-36 questionnaire) significantly increased during the follow-up. The study documented real-world benefits of semaglutide for treating obesity in T2D subjects, with important changes on clinical and patient-reported outcomes. Loss of lean mass associated with weight loss warrants attention; parallel strategies to preserve skeletal muscle and improve physical function, i.e. nutritional education and structured exercise, are of great importance.

Background: Lifestyle medicine (LM) is a contemporary scientific discipline with a multidisciplinary approach. Case Management offers a viable alternative for the care of patients with Type 2 Diabetes (T2D). This study aimed to identify the role and clinical applications of the lifestyle medicine case manager nurse (LMCMN) for T2D patients internationally and to analyze the role of specialist nurses in Italy through a narrative review. A secondary objective was to define a job description (JD) for a future Delphi method. Methods: A narrative review of the literature was conducted using PubMed/Medline, Scopus, and grey literature sources to analyze the international and Italian regulatory contexts. Subsequently, a JD for the LMCMN was developed for application in a future Delphi Study. Results: Nurses play a strategic role in managing T2D, and the LM approach has demonstrated strong evidence of effectiveness. This study developed a specific JD for the LMCMN suitable for both Italian and international contexts. Conclusions: The specific role of the LMCMN is still underdeveloped internationally. In the context of territorial assistance and chronic disease management, this professional is crucial for delivering quality care and shaping health policies that meet community needs.

Background/Objectives: Human papillomavirus (HPV) is a leading cause of cervical cancer. Despite the proven effectiveness of vaccination programs, global coverage remains uneven, with significant disparities across regions due to various socioeconomic, cultural, and political factors. This study explores the primary barriers to HPV vaccination worldwide and proposes recommendations to improve access to screening and vaccination programs. Methods: A systematic literature review was conducted, analyzing studies published in the past ten years from databases such as PubMed, Scopus, and Embase, following the PRISMA methodology. Study selection involved multiple researchers, with discrepancies resolved through consultation. The quality of the included studies was assessed using CASP checklists. The protocol was registered on Open Science Framework (OSF). Results: Out of 2119 records, eight studies were included. The findings indicate that the main barriers to HPV vaccination include insufficient public awareness, cultural and religious resistance, financial constraints, and limited access in rural and underserved areas. Additionally, political factors, such as low prioritization of HPV vaccination and the absence of supportive policies, were identified as significant obstacles. Multidisciplinary and cross-cultural collaboration, along with the integration of HPV vaccination into existing health programs, was suggested as a strategic approach to improve vaccine uptake. Conclusions: Barriers to HPV vaccination, including limited awareness, inadequate healthcare infrastructure, and socioeconomic factors, vary across regions but must be addressed to improve global coverage. Targeted interventions such as health education, inclusive policies, and culturally sensitive campaigns can significantly boost vaccine uptake. Strengthening local health systems and fostering international collaboration are key strategies to overcoming these barriers and ensuring equitable access to HPV vaccination.

Background/Objectives: The Internet of Things (IoT) technology connects objects to the internet, and its applications are increasingly used in healthcare to improve the quality of care. However, the use of IoT for the nutritional management of patients with chronic neurological cognitive impairment is still in development. This scoping review aims to describe the integration of IoT and its applications to support monitoring, interventions, and nutritional education for patients with chronic neurological cognitive impairment. Methods: A scoping review was conducted using the Cochrane, PubMed/Medline, CINAHL, Embase, Scopus, and Web of Science databases following the Arksey and O’Malley framework. Results: Of the 1424 records identified, 10 were included in the review. Most of the articles were peer-reviewed proceedings from technology conferences or publications in scientific and technology journals. IoT-based innovations in nutritional management were discussed in methodological articles, case studies, or project descriptions. Innovations were identified across three key areas: monitoring, intervention, and education. Conclusions: IoT technology offers promising innovations for the nutritional management of patients with chronic neurological cognitive impairment. However, IoT capabilities in this field are still in the early stages of development and are not yet highly specific.

Introduction: Type 1 diabetes (T1D) is a disease that primarily occurs in pediatric populations. A school nurse (SN) can provide valuable support in the school setting for minors affected by this condition. Methods: The main objective of this study was to evaluate the impact of nursing care provided to adolescents and children with T1D using technological devices in school. Qualitative and quantitative outcomes considered in the included studies were collected and discussed. A systematic review was conducted in the PubMed, CINAHL, and Scopus databases and reported thought the PRISMA guidelines. Results: Eleven studies were included. The results showed that SNs need to enhance both their skills and organization to effectively manage young patients with T1D using technology. The response of both the pediatric population and their caregivers to the disease management by a SN has been positive. Conclusions: The management of chronic diseases is one of the most urgent public health issues, especially for Western healthcare systems. Proper management of patients with T1D at the school level is definitely an aspect that policymakers and healthcare managers should consider to improve the quality of life of this extremely vulnerable population, particularly those using technological management T1D.