Prediction of visceral adipose tissue magnitude using a new model based on simple clinical measurements.

Aims: Waist circumference (WC) is a reliable obesity surrogate but may not distinguish between visceral and subcutaneous adipose tissue. Our aim was to develop a novel sex-specific model to estimate the magnitude of visceral adipose tissue measured by computed tomography (CT-VAT). Methods: The model was initially formulated through the integration of anthropometric measurements, laboratory data, and CT-VAT within a study group (n=185), utilizing the Multivariate Adaptive Regression Splines (MARS) methodology. Subsequently, its correlation with CT-VAT was examined in an external validation group (n=50). The accuracy of the new model in estimating increased CT-VAT (>130 cm2) was compared with WC, body mass index (BMI), waist-hip ratio (WHR), visceral adiposity index (VAI), a body shape index (ABSI), lipid accumulation product (LAP), body roundness index (BRI), and metabolic score for visceral fat (METS-VF) in the study group. Additionally, the new model's accuracy in identifying metabolic syndrome was evaluated in our Metabolic Healthiness Discovery Cohort (n=430). Results: The new model comprised WC, gender, BMI, and hip circumference, providing the highest predictive accuracy in estimating increased CT-VAT in men (AUC of 0.96 ± 0.02), outperforming other indices. In women, the AUC was 0.94 ± 0.03, which was significantly higher than that of VAI, WHR, and ABSI but similar to WC, BMI, LAP, BRI, and METS-VF. It's demonstrated high ability for identifying metabolic syndrome with an AUC of 0.76 ± 0.03 (p<0.001). Conclusion: The new model is a valuable indicator of CT-VAT, especially in men, and it exhibits a strong predictive capability for identifying metabolic syndrome.

Parvovirus B19 Infection in Adults: A Case Series.

Parvovirus B19 infection, typically associated with erythema infectiosum in children, presents variably in adults, often leading to misdiagnosis. This case series describes three adult patients diagnosed with parvovirus B19 infection in an internal medicine outpatient clinic in March 2024. Symptoms included fatigue, joint pain, swelling, and skin rash, with misdiagnoses including early rheumatoid arthritis. The diagnosis was confirmed via positive parvovirus antibodies and polymerase chain reaction (PCR). All patients received supportive care, and symptoms resolved within an average of 18 days. This series underscores the need for heightened clinical suspicion and timely serological testing for parvovirus B19 in adults presenting with flu-like symptoms, joint pain, and rash, especially during mini-outbreaks and following contact with infected children.

Is ChatGPT an Accurate and Reliable Source of Information for Patients with Vaccine and Statin Hesitancy?

Objective: Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence (AI) language model that is trained to respond to questions across a wide range of topics. Our aim is to elucidate whether it would be beneficial for patients who are hesitant about vaccines and statins to use ChatGPT. Methods: This cross-sectional and observational study was conducted from March 2 to March 30, 2023, using OpenAI ChatGPT-3.5. ChatGPT provided responses to 7 questions related to vaccine and statin hesitancy. The same questions were also directed at physicians. Both the answers from ChatGPT and the physicians were assessed for accuracy, clarity, and conciseness by experts in cardiology, internal medicine, and microbiology, who possessed a minimum of 30 years of professional experience. Responses were rated on a scale of 0-4, and the ChatGPT's average score was compared with that of physicians using the Mann-Whitney U test. Results: The mean scores of ChatGPT (3.78±0.36) and physicians (3.65±0.57) were similar (Mann-Whitney U test p=0.33). The mean scores of ChatGPT were 3.85±0.34 for vaccination and 3.68±0.35 for statin use. The mean scores of physicians were 3.73±0.51 for vaccination and 3.58±0.61 for statin use. There was no statistically significant difference between the mean scores of ChatGPT and physicians for both vaccine and statin use (p=0.403 for vaccination, p=0.678 for statin). ChatGPT did not consider sources of conspiratorial information on vaccines and statins. Conclusions: This study suggests that ChatGPT can be a valuable source of information for guiding patients with vaccine and statin hesitancy.