This study examines research on the impact of climate change (CC) on non-communicable diseases (NCDs) using bibliometric analysis, topic modeling, and content analysis. Articles published in the Web of Science database between 2000 and 2024 were analyzed. VOSviewer and Biblioshiny were used for bibliometric analysis and Python for topic modeling. In addition, the 50 most cited articles were content analyzed. The results show that there has been an increasing number of publications over time and that the research originates predominantly from high/very high Human Development Index (HDI) countries, especially China and the United States, rather than from low HDI countries. These countries also have strong international cooperation networks. Topic modeling shows that high/very high HDI countries work on a balanced range of topics, while low HDI countries focus primarily on environmental impacts. Thematic analysis shows that research topics are evolving, diversifying, and deepening. As a result, the literature on CC-NCDs is expanding and deepening, thus providing evidence-based information for global public health interventions. However, in countries with low HDI and the most vulnerability to the impacts of climate change, the volume of publications, thematic diversity, and international cooperation are significantly low. Unfortunately, from a public health policy perspective, global climate change is far from being a problem that any country can solve alone. Global cooperation is, therefore, essential.

Viral hepatitis are infections that can cause liver damage, become chronic, lead to cirrhosis, hepatocellular carcinoma and ultimately result in death due to their ability to spread in the community through blood and infected body fluids. The aim of this study was to determine the seroprevalence of hepatitis B (HBV), hepatitis C (HCV), and hepatitis D (HDV) transmitted through blood among individuals living in Trabzon province and to examine the factors potentially associated with seroprevalence. This cross-sectional study was conducted in Trabzon province, located in the northeast of T & uuml;rkiye, including a total of 10 districts, including the central district. Since seroprevalence was calculated for HBV, HCV, and HDV in the study, the sample size was separately calculated for each, and the calculated maximum sample size of 1116 was accepted as the minimum sample size for the study. The study was completed with 1502 participants. Serological tests for HBV included HBsAg, anti-HBs, and anti-HBc IgG; for HCV, anti-HCV; and for HDV, anti-HDV were analysed. Data were evaluated for HBV risk factors using univariate analyses with Chi-square test and for multiple analyses using enter model logistic regression analysis. The mean age of the participants was 45.7 +/- 16.6 years, with 767 (51.1%) being female. The prevalence of HBV seropositivity, indicating vaccination, was 23.0%, while the seroprevalence of HBV among unvaccinated adults was 27.4%. HBsAg positivity was 5.1%, and isolated anti-HBc IgG positivity was 4.2%. The proportion of individuals with HBsAg in the gray zone was 0.5%, while the positivity rates for anti-HBs and anti-HBc IgG (indicating past infection) were 17.6%. The prevalence of anti-HCV was six per thousand, while anti-HDV was not detected in the analyses. HBsAg positivity and co-infection with HCV were found in one person, and among the nine individuals positive for anti-HCV, isolated anti-HBc IgG positivity was detected in three. Increasing age, presence of a person with jaundice in the family, presence of diabetes mellitus, alcohol use and cupping therapy were identified as risk factors for HBV in the logistic regression analysis. Risk factors for HCV in univariate analyses were being over 40 years old, presence of hepatic steatosis and receiving dialysis treatment. The results of the study indicate that despite being included in our vaccination schedule and the administration of vaccines to high-risk adults, HBV still requires intensive attention as a public health problem. HCV, lacking a vaccine has been evaluated as an infectious agent that needs to be taken into consideration due to its potential risks and requires the complete implementation of individual and social precautions.

Background and Aim: Metabolic-associated fatty liver disease (MAFLD) is a condition that frequently goes unnoticed as it typically remains asymptom-atic until progressing to an advanced stage. As a result, it is essential to imple-ment opportunistic screening initiatives within family medicine practices to accurately identify and refer selected at-risk patients to specialized care. This study aims to investigate the prevalence of MAFLD and advanced hepatic fi-brosis among primary care patients in Turkiye by utilizing non-invasive tests. Materials and Methods: We performed a retrospective analysis of pro-spectively collected data from February 1, 2022, to April 14, 2023, at a Family Medicine Outpatient Clinic. The Hepatic Steatosis Index (HSI) was used to identify fatty liver cases, followed by established MAFLD criteria for diagnosis. Patients were then categorized based on advanced fibrosis risk using the fibrosis-4 (FIB-4) index. Results: Among the 450 patients who sought primary care during the study period (286 women and 164 men; mean age: 48.2±13.7 years), 295 (65.6%) were diagnosed with MAFLD using HSI values and established criteria. Di-abetes mellitus emerged as the sole independent predictor of MAFLD. FIB-4 values classified 242 (82%) and 53 (18%) patients with MAFLD at low and intermediate risk of advanced fibrosis, respectively, with none at high risk. Conclusion: MAFLD exhibits a notable prevalence among Turkish patients who presented at a Family Medicine Outpatient Clinic. Given the growing impact of metabolic diseases, primary care providers and non-liver special-ists should actively participate in MAFLD screening programs.

The objective of this study was to examine the effects of orlistat use on metabolic control and weight loss in diabetic and nondiabetic patients.

Background: Timely decision‐making is critical for managing toxicological exposures; however, many physicians lack toxicology‐specific experience and resources.Objectives: This study aimed to assess whether GPT‐4o, an artificial intelligence (AI)‐based decision support system, could provide emergency medicine residents with information for managing toxicology cases and to analyze its potential effectiveness in guiding treatment decisions compared to toxicologists.Methods: We conducted a prospective observational study with 30 emergency medicine residents (16 junior residents [JRs] and 14 senior residents [SRs]) using GPT‐4o. Each resident was assigned 30 clinical scenarios derived from real‐life toxicological exposure cases. GPT‐4o responded to the same 30 scenarios assigned to each resident. The responses from the residents and GPT‐4o were compared to gold standard (GS) responses determined by a medical toxicologist. Cohen's kappa coefficient was used to evaluate the agreement between each group's responses and the GS.Results: GPT‐4o and SRs showed a similar and good agreement with the GS for recommending antidotal treatment (GPT‐4o: κ = 0.710, p < 0.001; SR: κ = 0.704, p < 0.001). This agreement was lower among JRs (κ = 0.451, p < 0.001). Regarding the recommendation for enhancing elimination treatment, GPT‐4o demonstrated greater agreement with the GS (κ = 0.632, p < 0.001) than SRs (κ = 0.551, p < 0.001) and JRs (κ = 0.293, p < 0.001).Conclusions: Although ChatGPT‐4o demonstrated good agreement with the medical toxicologist, the observed risk of incorrect recommendations suggests that AI‐based systems should currently be considered as supportive tools rather than stand‐alone decision makers. Expert toxicological oversight remains important, particularly for high‐stakes clinical decisions.