Today, the medical tourism industry has a projected growth rate of up to 25% year-over-year for the next 10 years and it is estimated that 3–4% of the world’s population will travel internationally for healthcare. The purpose of this article is to give a brief insight into relevant topics of medical tourism that remain undefined, unsolved or unregulated. The expected impacts of medical tourism include possible ethical, legal, and medical risks arising as a result of differences in particular countries in the standards applied in medical tourism institutions/facilities. Different standards of medical care, differences in legal systems and regulations, and taken procedures could result in unethical situations mainly due to the absence of internationally prescribed laws and accreditations related to medical tourism.

Introduction: Over the past two years, the use of Large Language Models (LLMs) in clinical medicine has expanded significantly, particularly in cardiology, where they are applied to ECG interpretation, data analysis, and risk prediction. This study evaluates the performance of five advanced LLMs—Google Bard, GPT-3.5 Turbo, GPT-4.0, GPT-4o, and GPT-o1-mini—in responding to cardiology-specific questions of varying complexity. Methods: A comparative analysis was conducted using four test sets of increasing difficulty, encompassing a range of cardiovascular topics, from prevention strategies to acute management and diverse pathologies. The models’ responses were assessed for accuracy, understanding of medical terminology, clinical relevance, and adherence to guidelines by a panel of experienced cardiologists. Results: All models demonstrated a foundational understanding of medical terminology but varied in clinical application and accuracy. GPT-4.0 exhibited superior performance, with accuracy rates of 92% (Set A), 88% (Set B), 80% (Set C), and 84% (Set D). GPT-4o and GPT-o1-mini closely followed, surpassing GPT-3.5 Turbo, which scored 83%, 64%, 67%, and 57%, and Google Bard, which achieved 79%, 60%, 50%, and 55%, respectively. Statistical analyses confirmed significant differences in performance across the models, particularly in the more complex test sets. While all models demonstrated potential for clinical application, their inability to reference ongoing clinical trials and some inconsistencies in guideline adherence highlight areas for improvement. Conclusion: LLMs demonstrate considerable potential in interpreting and applying clinical guidelines to vignette-based cardiology queries, with GPT-4.0 leading in accuracy and guideline alignment. These tools offer promising avenues for augmenting clinical decision-making but should be used as complementary aids under professional supervision.

Today, medical tourism is underrated and mostly perceived as a beauty tourism. However, except dermatological and dental services also organ transplantation, IVF and many other therapies are well present in medical tourism travel arrangements. Medical tourism without any doubt impacts access to healthcare. Healthcare system in many countries allows access to some of these services but all-around world approaches differ. We believe that healthcare access could greatly benefit by opening this kind of services to wider population while at the same time not endangering patient’ safety. Harmonized propositions, accreditations and certificates for medical tourism industry access covered by both, private and public health insurances, would contribute to service transparency and patient’ safety while taking care of moral aspects of such services. Therefore, if consciously incorporated, medical tourism, as a part of global healthcare could easily become an efficient and effective additional access to healthcare.

In early 2026 in Croatia, a male heterosexual patient of Croatian origin was diagnosed with extensively drug-resistant (XDR) gonorrhoea after unprotected vaginal intercourse with a Croatian female. The Neisseria gonorrhoeae HR027 isolate (genomic lineage B, MLST sequence type (ST)9903) exhibited high-level azithromycin, ceftriaxone, cefixime, benzylpenicillin, ciprofloxacin and tetracycline resistance. It had the mosaic penA -60.001 allele, and A2045G mutations in 23S rRNA. A single dose of ceftriaxone 2 g administered intravenously cured the infection. HR027 showed zoliflodacin and gepotidacin wild-type minimum inhibitory concentrations.