Urs Alexander Fichtner

Background: Continued analgesic prescription after elective total hip arthroplasty (THA) or total knee arthroplasty (TKA) indicates persistent pain and increases the risk of adverse drug reactions, particularly in older patients or those with chronic conditions. The aim of this study was to identify independent risk factors for long-term analgesic prescription in patients who have undergone arthroplasty followed by inpatient orthopaedic rehabilitation. Methods: The study is based on nationwide claims data from Germany’s largest statutory health insurance provider (AOK) for the period from 2020 to 2024. Potential risk factors included demographic characteristics as well as factors related to the hospital stay/surgery and outpatient treatment in the 12 months prior to surgery. Adjusted odds ratios (OR) were calculated using a multivariable logistic regression model. In addition, we examined the extent to which model performance, measured by the area under the curve (AUC), improved when an additional variable category was included. Results: The strongest association with long-term analgesic prescription after arthroplasty was observed for intensive use of analgesics in the year prior to surgery, which showed a more than sixfold increase in the odds (THA: OR 6.7; TKA: OR 7.5). A higher care dependency level, substance use disorders, a high BMI (≥ 40 kg/m ² ), and various pain conditions showed significant associations, with adjusted ORs of up to 2.3 in both indications. Including risk factors from the 12-month pre-observation period into the regression model enhanced model performance strongly. Conclusion: The results of this observational study based on a large nationwide database may provide valuable clinical insights and establish a robust framework for future confirmatory trials. Trial registration: Not applicable. This study is a retrospective analysis of routinely collected billing data and does not involve health interventions.

Introduction: Prostate biopsy is a key diagnostic tool for prostate cancer and is often associated with physical, emotional, and social challenges. To enhance future multicenter trial designs for diagnostic precision, understanding patient-relevant outcomes is essential. Current evidence on patient-reported outcomes (PROMs) and patient-reported experience measures (PREMs) in the context of prostate biopsies remains limited, particularly regarding perioperative biopsychosocial impacts. This study aimed to explore patient-relevant factors, including concerns, side effect tolerance, and preferences, to inform future trials through patient and public involvement (PPI). Methodology: A prospective monocentric qualitative study was conducted with 12 male patients (mean age: 69.8 years) who underwent prostate biopsy. Preprocedure semistructured telephone-based interviews were conducted from May to August 2024 in Freiburg, Germany, transcribed verbatim, and analyzed via deductive-inductive content analysis. Intercoder reliability reached a kappa of 0.73. A short questionnaire was used to collect background data. The interviews addressed themes such as study motivation, fears, diagnostic precision, side effects, communication preferences, and other outcomes relevant to patients. Results: The participants expressed fears about physical side effects (e.g., pain, incontinence, and erectile dysfunction) and potential cancer diagnoses. While most patients tolerate temporary side effects for the sake of diagnostic accuracy, potential long-term effects raise concerns. Trust in the medical team’s expertise, the reputation of the medical center, and transparent communication were identified as crucial for patient satisfaction. Many participants showed altruistic motivation to contribute to research but emphasized the importance of shorter waiting times and clear communication regarding biopsy risks and benefits. The biopsychosocial model was evident, as patients reported interconnected physical, psychological, and social burdens. Preferences for open, empathetic communication and reduced procedural invasiveness were recurrent themes. Conclusions: This study highlights the multidimensional nature of patient experiences with prostate biopsy, emphasizing the importance of patient-centered research. Transparent communication, trust, and minimizing invasiveness while ensuring diagnostic accuracy are essential for improving patient satisfaction and reducing anxiety. The findings provide valuable insights for designing future studies and underline the importance of incorporating patient-relevant outcomes in clinical research and decision-making. Trial registration: This study was registered at the University Medical Center of Freiburg Clinical Trial Register (FRKS005027).

Background: Medical screening is employed to detect early signs of diseases in asymptomatic populations, potentially improving patient outcomes through early intervention. However, the psychosocial impact of screenings remains a field of discussion. Inconsistent findings from studies, mainly originally from cancer research, are not easily transferable to the context of liver screening. This study aimed to identify predictors of psychosocial consequences in asymptomatic adults screened for early-stage liver cirrhosis, thereby contributing to the current knowledge on screening impact. Methods: We analyzed data from 487 participants who underwent a systematic liver disease screening in Germany from January 2018 to February 2021. The screening involved blood tests, advanced diagnostics, and potentially, liver biopsies. We used bootstrapped LASSO regression with 10-fold validation to evaluate the influence of various predictors on psychosocial outcomes measured by the Psychological Consequences of Screening Questionnaire (PCQ). Results: The results show that severity of comorbidities (beta = 0.44–2.72), subjective social status (beta = −0.30–−0.86), and social support (beta = −0.33–−0.98) were consistent predictors across all psychosocial outcome measures by not covering zero in the confidence intervals. Older age (beta = −0.03–−0.08), the existence of a steady partnership (beta = −1.08–−0.48) and higher health literacy regarding the application of medical information (beta = 0.33–0.48) were associated with less psychosocial dysfunction, indicating their protective roles to prevent psychosocial burden of screening. Conclusion: The study underscores the importance of considering individual patient characteristics in predicting psychosocial consequences of medical screening. Medical practitioners should consider personalized communication strategies taking into account the individual context of patients. The protective role of social support and stable personal relationships suggests that integrating psychosocial support services within screening programs could mitigate negative outcomes. Furthermore, increasing patient health literacy might help to demystify the screening process and can reduce psychosocial burden even if patients come from a segment of lower subjective social status.

Zusammenfassung: Ziel Die REHA-KNOWS-Studie exploriert die Wahrnehmung von Praxisvertreter:innen südwestdeutscher Rehabilitationseinrichtungen hinsichtlich (Versorgungs-)Forschung und zeigt Nutzen und Barrieren im Wissenstransfer aus Sicht der Praxis auf. Hierfür wurde ein Instrument mit 12 5-stufigen Items entwickelt, das in dieser Arbeit explorativ untersucht wird. Das Instrument umfasst Aussagen über Nutzen, Aufwand und Mehrwert von Reha-Forschungsprojekten sowie über Rahmenbedingungen in den Einrichtungen. Von März bis Mai 2023 wurden Daten von Verterter:innen aus 206 Reha-Einrichtungen in Baden-Württemberg und im Saarland mithilfe eines Online-Fragebogens gesammelt. Methodik Es erfolgte eine deskriptive Analyse der Verteilungseigenschaften. Weiterhin wurde eine explorative Faktorenanalyse mittels Parallelanalyse nach Horn sowie Veliciers Minimum Average Partial zur Bestimmung der zugrundeliegenden Faktorstruktur und Eindimensionalität durchgeführt. Außerdem wurden Mann-Whitney-U-Tests berechnet zur Ermittlung von Unterschieden in den Antworten zwischen den Vertreter:innen aus den Bereichen Medizin, Pflege und Therapie und Personal mit administrativen und Managementaufgaben. Ergebnisse Insgesamt wies das Instrument wenige fehlende Werte bei einer akzeptablen Streuung und geringer Itemschwierigkeit auf. Boden- und Deckeneffekte waren vernachlässigbar gering, traten aber bei drei Items auf. Unterschiede im Antwortverhalten zwischen den Berufsgruppen ergaben sich deskriptiv für die Items 2, 10 und 12. Diese waren jedoch unter Berücksichtigung von multiplem Testen nicht signifikant. Vier Items wurden aufgrund schlechter Eignung aus der Faktorenanalyse ausgeschlossen, die dann eine einfaktorielle Lösung mit 31% Varianzaufklärung ergab. Der Fit für das Gesamtmodell zur Prüfung der Eindimensionalität ist als unbefriedigend einzustufen. Der identifizierte Faktor lässt sich als „Einstellung gegenüber dem Nutzen von Forschung für die Praxis” beschreiben. Die Antworten auf die offene Frage nach den bisherigen Erfahrungen mit Forschungsaktivitäten geben Hinweise darauf, dass weitere Items generiert werden sollten, die das Kosten-Nutzen-Verhältnis mit Schwerpunkt auf die monetäre Vergütung des anfallenden (Personal-)Aufwands abdecken sollten. Schlussfolgerung Das neu entwickelte Instrument setzt einen Grundstein zur systematischen Erfassung von Einstellungen von Vertreter:innen von Reha-Einrichtungen gegenüber (Versorgungs-)Forschung. Es bedarf weiterer Studien, um das Messinstrument zum Erheben dieser komplexen Thematik zu verbessern.

Background: The advancement of Artificial Intelligence, particularly Large Language Models (LLMs), is rapidly progressing. LLMs, such as OpenAI’s GPT, are becoming vital in scientific and medical processes, including text production, knowledge synthesis, translation, patient communication and data analysis. However, the outcome quality needs to be evaluated to assess the full potential for usage in statistical applications. LLMs show potential for all research areas, including teaching. Integrating LLMs in research, education and medical care poses opportunities and challenges, depending on user competence, experience and attitudes. Objective: This project aims at exploring the use of LLMs in supporting statistical consulting by evaluating the utility, efficiency and satisfaction related to the use of LLMs in statistical consulting from both advisee and consultant perspective. Within this project, we will develop, execute and evaluate a training module for the use of LLMs in statistical consulting. In this context, we aim to identify the strengths, limitations and areas for potential improvement. Furthermore, we will explore experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg. Materials and methods: This multimodal study includes four study parts using qualitative and quantitative methods to gather data. Study part (I) is designed as mixed mode study to explore the use of LLMs in supporting statistical consulting and to evaluate the utility, efficiency and satisfaction related to the use of LLMs. Study part (II) uses a standardized online questionnaire to evaluate the training module. Study part (III) evaluates the consulting sessions using LLMs from advisee perspective. Study part (IV) explores experiences, attitudes, fears and current practices regarding the use of LLMs of the staff at the Medical Center and the University of Freiburg. This study is registered at the Freiburg Registry of Clinical Studies under the ID: FRKS004971.

Zusammenfassung: Einleitung: Diagnose und Behandlung einer Krebserkrankung im Kindesalter gehen mit einer Vielzahl von körperlichen und psychosozialen Anforderungen einher. In der hier vorgestellten Studie wurden soziodemografische, medizinische und biopsychosoziale Einflussfaktoren von Bedürfnissen in den Bereichen körperliche Unterstützung, Unterstützung bei emotionaler Beanspruchung, soziale Teilhabe sowie Sicherheit und Kontrollerleben identifiziert, die für die Prävention psychosozialer Beeinträchtigungen bei jungen Onkologiepatient*innen genutzt werden können. Materialien und Methoden: Die Teilnehmenden (N = 117; im Alter von 8–13 Jahren) der Querschnittstudie wurden unter Einsatz eines kindspezifischen Erhebungsinstruments (KiWuF-PädOnk) befragt. Es wurden multiple lineare Regressionen durchgeführt. Ergebnisse: Das Bedürfnis nach körperlicher Unterstützung wurde signifikant von der Diagnose, dem zeitlichen Abstand zur Diagnose und der schulischen Lebensqualität beeinflusst. Die Schulform und die psychische Lebensqualität hatten den größten Einfluss auf das Bedürfnis nach Unterstützung bei emotionaler Beanspruchung. Insbesondere die schulische Lebensqualität erwies sich als eine wesentliche Determinante, über die sich Voraussagen zum Bedürfnis nach sozialer Teilhabe sowie zum Bedürfnis nach Sicherheit und Kontrollerleben ableiten ließen. Schlussfolgerung: Neben der schulischen Lebensqualität scheint auch die Schulform ein relevanter Faktor zu sein, was darauf hindeutet, dass die sozialen Umstände einen Einfluss auf die Bedürfnisse onkologisch erkrankter Kinder haben. Es ist weitere Forschung in diesem Bereich angezeigt, um die Unterstützung junger Krebspatient*innen zu optimieren.

Background: Artificial intelligence (AI) has experienced an explosive growth in the healthcare sector and the scientific field. Large Language Models (LLMs) are investigated as potential tool to be used in medical treatment, by e.g. producing doctor’s reports, supporting personalized medicine or educating patients. However, limitations are broadly discussed addressing patient safety and ethical concerns due to false and misleading content. Therefore, LLMs face criticism among users not only towards their integration in the patient-provider-interaction, but also in its use in medical research and health care education. In the ongoing EXPOLS (Exploring the Potential of LLMs in Statistical Consulting) study, we address the question ‘What are the attitudes, fears and experiences regarding the integration of AI tools in the clinical/scientific work routine?’ Methods: We implemented an online survey that will be accessible in 07/2024. All employees at the University and Medical Center Freiburg will be asked to participate in the survey via online media. We expect a sample size of n = 600-1,200. The survey combines published measurements (e.g. TRI 2.0, result expectation measure), as well as a self-designed instrument with 15 items aiming to measure fears and attitudes towards AI. Latter was developed within a multidisciplinary team making use of ChatGPT as item generator. We will investigate its psychometric properties using exploratory factor analysis and describe distribution characteristics. Results: At the time of the conference, the project will be completed and both psychometric insights and content-related results will be reported. The results could have important public health implications, since attitudes towards AI will steer its integration in the medical and clinical routine. Conclusions: The EXPOLS study makes a current inventory among medical scientists in Freiburg following a modern approach in instrument development by including ChatGPT as collegial advisor. Key messages: • This study explores attitudes, fears and experiences towards the integration of AI tools in the work routine from medical and scientific staff at the University of Freiburg. • The findings might be crucial in determining the integration of AI based tools in the medical and clinical work routine.