Background/Objectives: Artificial intelligence (AI), machine-learning (ML), and deep-learning (DL) models are increasingly used for prognostic prediction in intensive care unit (ICU) sepsis, but their clinical readiness remains uncertain. This systematic review aimed to evaluate AI-, ML-, and DL-based models for mortality and clinically relevant outcome prediction in adult ICU patients with sepsis or septic shock. Methods: PubMed/MEDLINE, Scopus, and the Cochrane Library were searched up to April 2026. Eligible studies included adult ICU sepsis or septic shock cohorts evaluating AI/ML/DL-based prognostic models. Screening, full-text assessment, and data extraction were performed independently by two reviewers. Outcomes, model families, validation strategies, discrimination, calibration, clinical utility, explainability, comparative performance versus conventional severity scores, risk of bias, and reporting completeness were synthesized. Risk of bias was assessed using PROBAST domains supplemented by PROBAST + AI considerations, and reporting completeness was evaluated according to TRIPOD/TRIPOD + AI domains. Results: Seventy-five studies were included, comprising 50 PubMed-derived and 25 additional Scopus-derived studies. AUROC or C-statistic was extractable in 64 studies, external validation was reported in 27, prospective evaluation in three, calibration in 38, decision-curve analysis or clinical utility assessment in 37, and explainability in 64. Across 17 directly extractable within-study comparisons from nine studies, AI/ML models usually, but not uniformly, achieved higher discrimination than conventional severity scores, with a median paired ΔAUROC of +0.108 (IQR, +0.082 to +0.148; range, −0.013 to +0.203). Externally validated fixed-horizon models showed clinically relevant but heterogeneous discrimination across sepsis phenotypes, with stronger evidence in selected sepsis-induced coagulopathy cohorts and more variable transportability in respiratory and liver-injury subgroups. However, 45 studies were judged at high risk of bias, mainly because of limitations in the analysis domain. Conclusions: AI/ML models for adult ICU sepsis show a recurrent signal of prognostic discrimination and often perform comparably to or better than conventional severity scores in directly extractable within-study comparisons; however, this signal should be interpreted cautiously given clinical and methodological heterogeneity, limited prospective validation, incomplete calibration, and frequent high risk of bias. The strongest evidence comes from externally validated, phenotype-specific models, although routine clinical implementation remains limited by heterogeneous endpoints, incomplete calibration, insufficient prospective validation, and scarce workflow-level evaluation. Future studies should shift from retrospective AUROC optimization toward calibrated, externally validated, clinically actionable, and workflow-integrated decision-support tools tested in prospective ICU settings.

Inflammatory bowel disease (IBD) is a chronic disease of the gastrointestinal tract that has a profound impact on the quality of life of those afflicted with it. The scientific literature shows how the quality of life of people with IBD influences and is influenced by the clinical manifestations of the disease. Strongly connected with excretory functions, which have always been taboo in society, these clinical manifestations can lead to stigmatizing behaviours. The purpose of this study was to understand the lived experiences of the enacted stigma of people with IBD through Cohen’s phenomenological method. Two main themes (stigma in the workplace and stigma in social life) and one subtheme (stigma in love life) emerged from the data analysis. The data analysis revealed that stigma is associated with a multitude of negative health outcomes for the people targeted by it and can add to the already complex physical, psychological and social burdens endured by people with IBD. Having a better understanding of the stigma attached to IBD will facilitate the development of care and training interventions that can improve the quality of life of people suffering from IBD.

Background: Inflammatory bowel disease (IBD), encompassing ulcerative colitis and Crohn’s disease, is a heterogeneous chronic condition characterized by periods of relapse and remission. Ulcerative colitis involves inflammation of the colon and rectum mucosa, while Crohn’s disease causes deeper, transmural inflammation affecting all four gut layers from the mouth to the anus and can lead to complications such as fistulation. IBD significantly impacts patients’ physical and psychological well-being, thus reducing their quality of life (QoL). We aimed to evaluate the effectiveness of nursing intervention facilitated through telephone and email support in improving the quality of life (QoL) of Inflammatory Bowel Disease (IBD) patients. Methods: A pilot comparative observational design with pre-test and post-test assessments was employed, involving 50 participants assigned to either an intervention group (Group A, n = 26) or a control group (Group B, n = 24). Group A received regular telephone consultations and prompt email responses from trained nurses; Group B received standard care. Data were collected at baseline and six months post-intervention (T1) using the Patient-Reported Outcomes Measurement Information System (PROMIS^®) and Pittsburgh Sleep Quality Index. Results: Group A showed significant improvements in anxiety, depression, fatigue, and sleep quality, with p-values indicating the significance of these findings. Conclusions: Tailored nursing support via remote communication significantly benefits IBD patients by alleviating psychological distress and enhancing their overall well-being, underscoring the importance of integrating such interventions into standard IBD care practices.

Avoidant/Restrictive Food Intake Disorder (ARFID) and food neophobia present significant challenges in pediatric healthcare, particularly among children with food allergies (FAs). These eating disorders, characterized by the persistent avoidance or restriction of food, can lead to severe nutritional deficiencies and psychosocial impairments. The presence of FAs further complicates these eating behaviors, as the fear of allergic reactions exacerbates avoidance and restrictive patterns. This comprehensive review synthesizes current knowledge on ARFID and food neophobia, focusing on their definitions, characteristics, and the unique challenges they present in the context of FAs. The review explores the critical role of healthcare professionals, especially nurses, in integrating psychological and clinical care to improve outcomes for affected children. A multidisciplinary approach, including Cognitive Behavioral Therapy (CBT) and Family-Based Therapy (FBT), is emphasized as essential in addressing the complex needs of these patients. The review also highlights the need for standardized treatment protocols and further research on the long-term outcomes of these disorders, aiming to enhance therapeutic strategies and family support systems. Effective management of ARFID and food neophobia in the context of FAs requires a holistic and integrated approach to mitigate the profound impacts on a child’s growth, development, and overall well-being.

Introduction: Home-based cardiac telerehabilitation (HBCTR) is a multidisciplinary intervention aimed at optimizing functional, psychological, and social recovery in patients undergoing percutaneous coronary intervention (PCI). This rehabilitation model serves as an effective alternative to traditional center-based rehabilitation, providing a cost-effective and clinically advantageous approach. Methods: Following PRISMA guidelines, we conducted a systematic literature search across multiple databases (PubMed, CINAHL, Cochrane, Scopus, Web of Science). We included randomized controlled trials (RCTs), cohort, and observational studies assessing telerehabilitation in post-PCI patients. Primary outcomes focused on health-related quality of life (HRQoL) and adherence, while secondary outcomes included functional capacity (6 min walk test, VO₂max), cardiovascular risk factor control, and psychological well-being. Risk of bias was assessed using the Cochrane RoB 2.0 and ROBINS-I tools. Results: A total of 3575 articles were identified after removing duplicates, of which 877 were selected based on title and abstract, and 17 met the inclusion criteria, with strong RCT representation ensuring robust evidence synthesis. HBCTR was associated with significant improvements in exercise capacity, with increases in VO₂max ranging from +1.6 to +3.5 mL/kg/min and in 6 min walk distance from +34.7 to +116.6 m. HRQoL scores improved significantly, with physical and mental component scores increasing by +6.75 to +14.18 and +4.27 to +11.39 points, respectively. Adherence to telerehabilitation programs was consistently high, often exceeding 80%, and some studies reported reductions in hospital readmissions of up to 40%. Wearable devices and smartphone applications facilitated self-monitoring, enhancing adherence and reducing readmissions. Several studies also highlighted improvements in anxiety and depression scores ranging from 10% to 35%. Conclusions: HBCTR is a promising strategy for rehabilitation and quality-of-life improvement after PCI. It offers a patient-centered solution that leverages technology to enhance long-term outcomes. By integrating structured telerehabilitation programs, healthcare systems can expand accessibility, promote adherence, and improve equity in cardiovascular care.