Conectar
by Julian Kylies, Fabian Haas, Anna Duprée, Tobias B. Huber, Karl-Heinz Frosch, Matthias Priemel, Dominik Kylies
BackgroundLiposarcomas (LS) of the extremities and trunk are aggressive soft-tissue sarcomas and surgical resection combined with multimodal therapy represents the cornerstone of curative treatment. Despite advances in surgical and medical management patients are still at risk of developing medical complications that negatively affect morbidity and mortality. Kidney dysfunction, sarcopenia and progressive loss of visceral adipose tissue have emerged as prognostically relevant and potentially treatable complications in surgical oncology. However, despite their growing relevance, little is known about their frequency and impact on survival and morbidity in the context of LS.
MethodsWe conducted a retrospective study of 47 adult patients with localized LS of the extremities and trunk who underwent curative-intent surgery. Kidney function, CT morphometry of muscle (skeletal muscle index, SMI) and visceral adipose tissue (VAT) as well as clinical assessments including ECOG score were recorded at diagnosis (t1) and after a median follow-up (t2) of 11 months. Kidney dysfunction, defined as a decrease in eGFR of ≥ 25% between time points, was analyzed in relation to survival, sequentially assessed CT-morphometry of muscle and adipose tissue as well as functional status assessed by ECOG scores.
ResultsAll patients underwent curative-intent surgical treatment with or without additional multimodal treatment (surgery only: 51.1%, additional radiation: 31.9%, additional chemotherapy: 38.3%). Kidney dysfunction was frequent in our cohort (53.2% of all patients) and significantly associated reduced overall survival in Kaplan–Meier, uni- and multivariate Cox proportional hazards regression models (multivariate hazard ratio: 6.7; p = 0.03). In addition, patients with kidney dysfunction experienced a significantly accelerated loss of SMI (p Conclusions
To our knowledge, this is among the first studies to investigate kidney dysfunction and its consequences in adult LS patients. In our cohort of surgically treated adult patients with LS of the extremities and trunk, kidney dysfunction was a frequent and clinically impactful complication. It was significantly associated with decreased overall survival, loss of muscle and adipose tissue in sequential CT morphometry assessments and progressive functional decline. Off note, CT-morphometry enabled objective, high-resolution tracking of body composition decline and may serve as a promising additional tool for risk stratification. Nonetheless, given the limited cohort size and retrospective single-center design, the generalizability of our findings is limited and the results should therefore be interpreted with caution. Despite these limitations, our findings call for future prospective studies and an awareness for heightened renal surveillance and integrated body composition assessments in the multimodal management of sarcoma patients.
To explore the perceptions of nursing professionals in high-demand healthcare services regarding the adoption of AI-based support systems for the prevention of medication errors.
A qualitative descriptive study was conducted between November 2024 and March 2025.
Sixteen semi-structured interviews were held with nurses from emergency and intensive care units, guided by conceptual dimensions of the Technology Acceptance Model framework. Participants were recruited using purposive and snowball sampling. ATLAS.ti v.9 software was used for an inductive thematic analysis.
Two major themes emerged: (i) professional reflections on medication safety and related risks; and (ii) integrating artificial intelligence into nursing practice to reduce such risks and prevent medication errors. While artificial intelligence was recognised as a promising resource to support clinical decision-making and reduce cognitive load, nurses identified barriers, including limited training, inadequate technological infrastructure, unreliable data sources, and ethical concerns that could compromise its safe implementation and thereby hinder its potential to prevent medication errors.
AI-based support systems are perceived as useful, but complex resources for addressing medication errors, which remain a critical challenge in healthcare. Its successful implementation depends not only on the availability of resources, but also on the organisational context and the ability to respond to the needs and concerns of healthcare professionals.
Integrating artificial intelligence into routine workflows to support clinical decision-making and reduce medication errors in high-demand settings requires more than infrastructure and technical training. Effective adoption demands participatory design, clear role delineation, and context-sensitive training aligned with medication-management processes. Lack of alignment may result in artificial intelligence increasing complexity instead of contributing to safer and more efficient medication administration.
Methods and findings are reported following SRQR recommendations.
No patient or public contribution.
The Research Domain Criteria (RDoC) approach initiated by the National Institute of Mental Health provides a comprehensive framework for guiding research on mental illness and health. Since retrospective studies have indicated associations between RDoC characteristics and clinically relevant as well as care-relevant outcomes, there is a need for prospective, theory-driven investigations that systematically link a priori defined assessments of RDoC constructs to clinically and care-relevant outcomes in a transdiagnostic psychiatric sample.
This prospective observational study assesses six domains—Positive Valence Systems, Negative Valence Systems, Cognitive Systems, Social Processes, Arousal and Regulatory Systems and Sensorimotor Systems—employing a comprehensive set of self-report and additional paradigms to assess cognitive functioning developed a priori in alignment with the RDoC framework while also assessing clinically and care-relevant variables (eg, length of hospital stay). A total of 300 adult participants will be recruited among in- and outpatients of two psychiatric hospitals in Germany (patient group) as well as from the general population (healthy control group). Including healthy individuals will allow for the investigation of continuous variations in psychological functioning rather than categorical distinctions between health and disease. Data collection includes self-reports, clinician ratings, file review and behavioural assessments. Electroencephalography is recorded in a subgroup of participants. A confirmatory factor analysis will be conducted to reproduce the factor structure and regression models will be used to investigate associations between RDoC domains and clinically relevant as well as care-related variables.
Ethics approval was obtained from the local ethics committee of the Brandenburg Medical School—Theodor Fontane (E-01-20220822). Results will be disseminated through peer-reviewed journals and academic conferences.
Treatment expectations are a key mechanism of placebo effects in clinical trials. In a previous study (PSY-HEART-I), preoperative expectation optimisation improved quality of life 6 months postcardiac surgery. However, barriers such as travel distance, staffing shortages and COVID-19 limited participation. This study evaluates the feasibility and acceptability of iEXPECT, a brief internet-based intervention designed to optimise expectations before heart surgery.
In this three-arm, multicentre randomised controlled trial, 160 patients undergoing elective coronary artery bypass graft surgery are randomised to: (a) standard of care (SOC); (b) SOC plus iEXPECT with phone-based guidance (iEXPECT enhanced) or (c) SOC plus iEXPECT with email-based guidance (iEXPECT limited). The intervention includes four 20 min online modules addressing surgical benefits, side effects and coping strategies. Modules are accompanied by personalised guidance provided through feedback on each module via email or telephone (three before surgery, three booster sessions at 6, 12 and 18 weeks postsurgery). Assessments occur at baseline (5–21 days before surgery), preoperatively (day before surgery), 7 days postsurgery and 6 months later. Primary feasibility outcomes include recruitment (≥1 participant/week/centre), retention (≥49% completing 6-month follow-up including biomarkers) and engagement (≥75% completing ≥1 presurgery module). Acceptability is measured by self-reported enjoyment, usefulness and impact, with acceptance defined as mean scores >3.4 (5-point Likert scale) and CSQ-I ratings. Secondary outcomes include psychological measures, inflammatory markers and heart rate variability.
Ethical approval was granted by the Ethics Committees of Philipps University Marburg (AZ 229/23 BO) and the University of Giessen (AZ 186/23). All participants provide written informed consent. Results will be shared via publications, conferences and public outreach with relevant consumer advocacy groups.
DRKS00033284.
Coronary artery bypass grafting (CABG) remains one of the most commonly performed cardiac surgeries worldwide. Despite surgical advancements, a significant proportion of patients experience psychological distress following surgery, with depression being particularly common. Current evidence regarding the effectiveness of preoperative psychological interventions in improving postoperative mental health outcomes remains inconclusive. There is a critical need for predictive models that can identify patients at risk of developing clinically significant depressive symptoms (CSDSs) and related psychological conditions after CABG. This multicentre observational study aims to develop and validate prognostic models for predicting CSDSs and other psychological outcomes, including anxiety, post-traumatic stress symptoms and quality of life, 6 weeks after elective CABG surgery.
The study will recruit 300 adult patients undergoing elective CABG (with or without valve intervention) across two Swiss hospitals. Data collected will include demographic, clinical, psychometric, inflammation-related and interoceptive variables. A training set (n=200) will be used to develop predictive models using machine learning, while a held-out test set (n=100) will be used for model validation. The primary outcome prediction will focus on CSDSs, assessed using the Patient Health Questionnaire-9 (PHQ-9), with analyses conducted both categorically (PHQ-9 total score ≥10) and continuously as complementary approaches. Secondary models will address anxiety, using the General Anxiety Disorder Scale-7, post-traumatic stress, using the post-traumatic stress disorder checklist for Diagnostic and Statistical Manual of Mental Disorders-5 and health-related quality of life, using the 12-item Short Form Survey. A simplified ‘light solution’ model with fewer predictors will also be developed for broader applicability. This study will address an important gap in perioperative mental healthcare by identifying key predictors of psychological morbidity following CABG, particularly CSDSs. The resulting models may inform future screening and preventive strategies and improve postsurgical outcomes through early identification and intervention in high-risk individuals.
The responsible ethics committee has reviewed and approved this project (Kantonale Ethikkommission Zürich, BASEC number: 2023-02040). The study minimises participant burden by integrating brief validated instruments and limiting psychiatric interviews to relevant outcomes, while ensuring ethical safeguards and respect for participant rights (including written consent). Results will be shared through peer-reviewed publications, conference presentations and stakeholder meetings involving clinicians and mental health professionals. Findings will also be communicated to participating centres and patient communities in accessible formats.
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