Abstract Aims: Medical case vignettes play a crucial role in medical education, yet they often fail to authentically represent diverse patients. Moreover, these vignettes tend to oversimplify the complex relationship between patient characteristics and medical conditions, leading to biased and potentially harmful perspectives among students. Displaying aspects of patient diversity, such as ethnicity, in written cases proves challenging. Additionally, creating these cases places a significant burden on teachers in terms of labour and time. Our objective is to explore the potential of artificial intelligence (AI)-assisted computer-generated clinical cases to expedite case creation and enhance diversity, along with AI-generated patient photographs for more lifelike portrayal. Methods: In this study, we employed ChatGPT (OpenAI, GPT 3.5) to develop diverse and inclusive medical case vignettes. We evaluated various approaches and identified a set of eight consecutive prompts that can be readily customized to accommodate local contexts and specific assignments. To enhance visual representation, we utilized Adobe Firefly beta for image generation. Results: Using the described prompts, we consistently generated cases for various assignments, producing sets of 30 cases at a time. We ensured the inclusion of mandatory checks and formatting, completing the process within approximately 60 min per set. Conclusions: Our approach significantly accelerated case creation and improved diversity, although prioritizing maximum diversity compromised representativeness to some extent. While the optimized prompts are easily reusable, the process itself demands computer skills not all educators possess. To address this, we aim to share all created patients as open educational resources, empowering educators to create cases independently.
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BACKGROUND:Endotracheal suctioning causes discomfort, is associated with adverse effects, and is resource-demanding. An artificial secretion removal method, known as an automated cough, has been developed, which applies rapid, automated deflation, and inflation of the endotracheal tube cuff during the inspiratory phase of mechanical ventilation. This method has been evaluated in the hands of researchers but not when used by attending nurses. The aim of this study was to explore the efficacy of the method over the course of patient management as part of routine care.METHODS:This prospective, longitudinal, interventional study recruited 28 subjects who were intubated and mechanically ventilated. For a maximum of 7 d and on clinical need for endotracheal suctioning, the automatic cough procedure was applied. The subjects were placed in a pressure-regulated ventilation mode with elevated inspiratory pressure, and automated cuff deflation and inflation were performed 3 times, with this repeated if deemed necessary. Success was determined by resolution of the clinical need for suctioning as determined by the attending nurse. Adverse effects were recorded.RESULTS:A total of 84 procedures were performed. In 54% of the subjects, the artificial cough procedure was successful on > 70% of occasions, with 56% of all procedures considered successful. Ninety percent of all the procedures were performed in subjects who were spontaneously breathing and on pressure-support ventilation with peak inspiratory pressures of 20 cm H2O. Rates of adverse events were similar to those seen in the application of endotracheal suctioning.CONCLUSIONS:This study solely evaluated the efficacy of an automated artificial cough procedure, which illustrated the potential for reducing the need for endotracheal suctioning when applied by attending nurses in routine care.
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Summary Purpose The purpose of this study was to investigate the adoption and actual use of a digital dietary monitoring system (DDMS) and its impact on patient satisfaction with the provided hospital care, body weight changes and health-related quality of life (HRQoL) in patients with potentially curable esophageal cancer planned for surgery. The DDMS enables patients and dietitians to monitor patients' nutritional intake and body weight during the preoperative period. Methods In this prospective observational study, the first 47 included patients received usual nutritional care, and were followed from diagnosis until surgery. After implementation of the DDMS 37 patients were followed, again from diagnosis until surgery. Main outcomes were actual use of the DDMS, by means of adoption and usage measures, overall patient satisfaction (EORTC-INPATSAT32), weight change and HRQoL (EORTC QLQ-C30 and EORTC-OG25). Outcomes were assessed immediately after diagnosis, and 6 and 12 weeks later. Results The system had an adoption rate of 64% and a usage rate of 78%. No significant effects on patient satisfaction were found at 12 weeks after diagnosis between the intervention and the usual care group. The implementation of the DDMS also had no significant effect on body weight and HRQoL over time. Conclusions Patients with potentially curable esophageal cancer planned for surgery were able to use the DDMS. However, no significant effects on patient satisfaction, body weight changes and HRQoL were observed. Further research should focus on the specific needs of patients regarding information and support to preoperatively optimize nutritional intake and nutritional status.
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