BACKGROUND:Patients with out-of-hospital cardiac arrest and in-hospital cardiac arrest have a poor prognosis. Laboratory biomarkers that are frequently altered in critically ill patients with cardiac arrest are liver function tests. However, the predictive value of abnormal liver function tests in the cardiac arrest setting remains unclear. METHODS:Four hundred seven patients who were treated after cardiac arrest in an intensive care unit at a tertiary-care hospital were included in the analysis. To classify LFT abnormalities, we used established upper limit of normal values and multiples thereof according to the NIH Common Terminology Criteria for Adverse Events (CTCAE). Kaplan-Meier estimates and cox proportional hazard models combined with the CardShock risk score were performed to investigate the association between liver function abnormalities and patient outcomes. RESULTS:Thirty-nine different combinations of elevated liver function tests have been observed in the study cohort. The most common abnormalities included an increase in aspartate aminotransferase (AST) levels, followed by an increase in alanine aminotransferase (ALT) and gamma-glutamyl transferase (GGT) levels. Kaplan-Meier estimates showed significant differences in 90-day survival rates depending on severity of AST, ALT, bilirubin, and INR elevations. A cox proportional hazard model analysis demonstrated that a combined increase in bilirubin and INR together with the CardShock risk score allowed the highest mortality prediction. CONCLUSIONS:Abnormal liver function tests can be frequently observed after cardiac arrest, with different patterns of damage having different prognostic relevance. The combination of elevated bilirubin and INR offers important prognostic information regarding 90-day mortality, particularly when added to validated risk tools, and can be used to identify patients at risk.
Abstract Objective This pilot study evaluated ChatGPT’s ability to answer standard emergency room (ER) case questions compared with that of junior residents at a level 1 trauma centre. Since its release in March 2023, ChatGPT‑4 has seen widespread adoption in education, research, and clinical practice, prompting interest in its medical utility. Despite concerns regarding accountability and trust, large language models (LLMs) have shown potential by-passing medical exams and generating differential diagnoses. Materials and methods The study was conducted at a level 1 trauma centre with an interdisciplinary ER from 21st to 27th February 2025. 21 fictional medical cases commonly encountered in the surgical ER were used. Seven junior residents with varying levels of training were included for comparison. ChatGPT and the doctors were prompted to answer these cases under identical conditions. Two board‑certified trauma surgeons independently rated responses for correctness, completeness, and adaptability; results were statistically analyzed. Results ChatGPT achieved mean scores of 4.62 ± 0.79 (correctness), 4.67 ± 0.56 (completeness), and 4.52 ± 0.66 (adaptability). Residents in years 1–3 scored 4.19 ± 0.05, 3.95 ± 0.48, and 4.05 ± 0.1, respectively; years 4–6 scored 3.99 ± 0.19, 3.71 ± 0.3, and 3.96 ± 0.2. ChatGPT and residents both performed best in lower extremity cases (14.5 vs. 12.9 points). Conclusions This pilot study indicates that ChatGPT can generate ER case responses comparable in quality to those of junior residents, particularly in completeness and correctness. Given the small sample size and vignette-based design, these findings do not support replacing physicians but highlight the potential of large language models as supportive or educational tools requiring clinician oversight. Establishing safe and ethical frameworks for AI use in medicine remains essential.
The standard technique used for full-thickness reconstruction of the lower eyelid is the Hughes tarsoconjunctival flap. Despite its widespread use, objective postoperative assessments of eyelid morphology and tension remain rare. This cross-sectional clinical study included patients who underwent the Hughes procedure at the Department of Ophthalmology, University of Cologne. Eyelid morphology was evaluated using the VECTRA M3 stereophotogrammetry system in neutral position, manual downward traction, and standardized hook distraction with a 15.9 g eyelid hook. Seventeen anatomical landmarks were identified per eye, measuring eight linear distances, two angles, and eyelid area. Operated and non-operated eyes were compared. Sixteen patients were included; 75 www.springer.com/00266 .
Abstract Background Age is a critical driver of the worldwide increasing cancer incidence rates, and with the growing number of older adults diagnosed with cancer, there is a rising need for specialized care. However, geriatric oncology (GO) education remains underrepresented in medical curricula. The gap between demand and adequately trained providers requires the development of more robust GO training programs. This study examined the current state of GO education, and the areas of interest within GO and the expected teaching methods for this specialized content. Methods A multi-center international online survey aimed at assessing the awareness and perceived significance of GO among early-career medical students and nursing trainees was conducted. Results Among 158 participants, only 36.5% had oncology training and 19.6% geriatrics training. Despite this, GO was consistently rated as highly important, with no difference by prior GO training (p = 0.853). Participants expressed strongest interest in mental health, palliative care, and quality-of-care topics, while satisfaction with current training was moderate. Teaching was predominantly lecture-based, although more interactive approaches such as seminars and bedside teaching were preferred. Over half of participants were willing to contribute to improving GO education through feedback or volunteering. Conclusion GO remains underrepresented in current training despite its high perceived importance among trainees. Participants preferred interactive teaching formats, particularly seminars and bedside teaching, and showed strong interest in mental health and palliative care topics. These findings support integrating geriatric oncology into curricula using more practice-oriented teaching strategies.
Abstract Background Myasthenia gravis has a variable disease course. Early identification of patients with a highly active disease is crucial to prevent myasthenic exacerbations and crisis, necessitating more aggressive immunotherapy. However, no biomarkers currently exist to identify patients at risk for highly active disease course. Objective The PROGNO-MG study aims to identify blood-based biomarker signatures associated with a highly active disease course in immunotherapy-naïve patients with acetylcholine-receptor-antibody positive (AChR+) generalized Myasthenia gravis (gMG). Methods This is an investigator-initiated prospective, multicentric, observational study. Seventy newly diagnosed immunotherapy-naïve AChR+ gMG patients will be enrolled and followed up for 24 months. Blood samples and clinical data will be collected biannually. Biomarkers (calprotectin, neurofilament light chain, ITIH3, complement activation, kappa free light chains, and exploratory proteome-analyses and immune cell phenotyping) will be measured and their association with clinical outcomes will be evaluated. Perspective The results will provide evidence for prognostic biomarkers, supporting risk stratification and early individualized treatment for AChR+ gMG patients. Trial registration The study is registered in the German clinical trial register (DRKS00035457).
