Validity of the large language model ChatGPT (GPT4) as a patient information source in otolaryngology by a variety of doctors in a tertiary otorhinolaryngology department.

BACKGROUND: A high number of patients seek health information online, and large language models (LLMs) may produce a rising amount of it. AIM: This study evaluates the performance regarding health information provided by ChatGPT, a LLM developed by OpenAI, focusing on its utility as a source for otolaryngology-related patient information. MATERIAL AND METHOD: A variety of doctors from a tertiary otorhinolaryngology department used a Likert scale to assess the chatbot's responses in terms of accuracy, relevance, and depth. The responses were also evaluated by ChatGPT. RESULTS: The composite mean of the three categories was 3.41, with the highest performance noted in the relevance category (mean = 3.71) when evaluated by the respondents. The accuracy and depth categories yielded mean scores of 3.51 and 3.00, respectively. All the categories were rated as 5 when evaluated by ChatGPT. CONCLUSION AND SIGNIFICANCE: Despite its potential in providing relevant and accurate medical information, the chatbot's responses lacked depth and were found to potentially perpetuate biases due to its training on publicly available text. In conclusion, while LLMs show promise in healthcare, further refinement is necessary to enhance response depth and mitigate potential biases.

SARS-CoV-2 Surface Swabs in Locations With Public Access-Potential for Improved Source Control.

The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces at public locations has been minimally described. By swab testing, we investigated the presence of SARS-CoV-2 on surfaces in public locations during the pandemic in February 2022. The viability of SARS-CoV-2 was not tested. Almost 25% of surfaces were positive for SARS-CoV-2; this was most pronounced in supermarkets.

Anti-SARS-CoV-2 Seropositivity Among Medical Students in Copenhagen.

BACKGROUND: Health care workers are at a higher risk of getting infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than the general population. Knowledge about medical students' exposure to SARS-CoV-2 is lacking. Thus, we measured the prevalence of SARS-CoV-2 antibodies in a cohort of Danish medical students. METHODS: We invited all medical students at the University of Copenhagen (UCPH) to participate. Students underwent venous blood sampling and a questionnaire about work-life behaviors possibly associated with SARS-CoV-2 exposure and coronavirus disease 2019 (COVID-19) symptoms. Samples were analyzed for total immunoglobulin G (IgG) antibodies against SARS-CoV-2, and seropositive samples were screened for IgG, immunoglobulin M, and immunoglobulin A antibodies. We determined associations between seropositivity and clinical and social activities and self-reported symptoms. RESULTS: Between October 19 and 26, 1120 students participated in the questionnaire and 1096 were included. Of all included, 379 (34.58%) were seropositive. Seropositivity was associated with attendance at 2 parties at UCPH, on February 29 and March 6, 2020 (odds ratio [OR], 5.96; 95% CI, 4.34-8.24; P < .001). Four hundred sixty-one students (42.06%) worked with COVID-19 patients, which was significantly associated with seropositivity (OR, 1.38; 95% CI, 1.03-1.85; P = .033). The symptom most associated with seropositivity was loss of smell and/or taste (n = 183 of all, 31.35%; OR, 24.48; 95% CI, 15.49-40.60; P < .001). Bachelor's students were significantly more likely to be seropositive than Master's students (42.28% vs 16.87%; P < .001). CONCLUSIONS: Medical students have the highest reported seropositivity in the Danish health care system. In this cohort of students at UCPH, seropositivity was associated with social behavior markers and, to a lesser extent, with self-reported contact with SARS-CoV-2-infected patients.