[ChatGPT for use in technology-enhanced learning in anesthesiology and emergency medicine and potential clinical application of AI language models : Between hype and reality around artificial intelligence in medical use]. / ChatGPT im Einsatz für "technology-enhanced learning" in Anästhesiologie und Notfallmedizin und potenzielle klinische Anwendung von KI­Sprachmodellen : Zwischen Hype und Wirklichkeit um künstliche Intelligenz im medizinischen Einsatz.

BACKGROUND: The utilization of AI language models in education and academia is currently a subject of research, and applications in clinical settings are also being tested. Studies conducted by various research groups have demonstrated that language models can answer questions related to medical board examinations, and there are potential applications of these models in medical education as well. RESEARCH QUESTION: This study aims to investigate the extent to which current version language models prove effective for addressing medical inquiries, their potential utility in medical education, and the challenges that still exist in the functioning of AI language models. METHOD: The program ChatGPT, based on GPT 3.5, had to answer 1025 questions from the second part (M2) of the medical board examination. The study examined whether any errors and what types of errors occurred. Additionally, the language model was asked to generate essays on the learning objectives outlined in the standard curriculum for specialist training in anesthesiology and the supplementary qualification in emergency medicine. These essays were analyzed afterwards and checked for errors and anomalies. RESULTS: The findings indicated that ChatGPT was able to correctly answer the questions with an accuracy rate exceeding 69%, even when the questions included references to visual aids. This represented an improvement in the accuracy of answering board examination questions compared to a study conducted in March; however, when it came to generating essays a high error rate was observed. DISCUSSION: Considering the current pace of ongoing improvements in AI language models, widespread clinical implementation, especially in emergency departments as well as emergency and intensive care medicine with the assistance of medical trainees, is a plausible scenario. These models can provide insights to support medical professionals in their work, without relying solely on the language model. Although the use of these models in education holds promise, it currently requires a significant amount of supervision. Due to hallucinations caused by inadequate training environments for the language model, the generated texts might deviate from the current state of scientific knowledge. Direct deployment in patient care settings without permanent physician supervision does not yet appear to be achievable at present.

An adaptation strategy to urban heat: hospital rooms with radiant cooling accelerate patient recovery.

BACKGROUND: Patients with respiratory diseases are vulnerable to the effects of heat. Therefore, it is important to develop adaptation strategies for heat exposure. One option is to optimise the indoor environment. To this end, we equipped hospital patient rooms with radiant cooling. We performed a prospective randomised clinical trial to investigate potentially beneficial effects of the hospitalisation in rooms with radiant cooling on patients with a respiratory disease exacerbation. METHODS: Recruitment took place in June, July and August 2014 to 2016 in the Charité - Universitätsmedizin Berlin, Germany. We included patients with COPD, asthma, pulmonary hypertension, interstitial lung disease and pneumonia. 62 patients were allocated to either a standard patient room without air conditioning or a room with radiant cooling set to 23°C (73°F). We analysed the patients' length of stay with a Poisson regression. Physiological parameters, fluid intake and daily step counts were tested with mixed regression models. RESULTS: Patients hospitalised in a room with radiant cooling were discharged earlier than patients in standard rooms (p=0.003). The study participants in chambers with radiant cooling had a lower body temperature (p=0.002), lower daily fluid intake (p<0.001), higher systolic blood pressure (p<0.001) and an increased daily step count (p<0.001). CONCLUSION: The results indicate that a radiant cooling system in hospital patient rooms provides clinical benefits for patients with respiratory disease exacerbations during the warm summer months, which may contribute to an earlier mobilisation. Radiant cooling is commended as a suitable adaptation strategy to reduce the clinical impact of climate warming.