Health Care Science最新文献

{"title":"A Chinese Expert Consensus on the Artificial Intelligence Proficiency of Medical Students: Competencies and the Multi-Modal Assessment","authors":"Mengchun Gong, Jiao Li, Yonghui Ma, Bo Jin, Wei Chen, Yan Hou, Li Hong, Tianwen Lai, Bohan Zhang, Ge Wu, Zhirong Zeng","doi":"10.1002/hcs2.70049","DOIUrl":"10.1002/hcs2.70049","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Artificial intelligence (AI) is transforming healthcare, demanding reevaluation of medical education. China's “New Medical Education” initiative urgently requires a standardized AI literacy framework for medical students to address fragmented standards, rapid technological evolution, and insufficient localized ethical norms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To establish a Chinese expert consensus defining core AI competencies and a multi-modal assessment framework for medical students.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A multidisciplinary (including medical education, clinical medicine, medical AI, public health, and medical ethics) expert group (<i>n</i> = 32) developed an initial competency list based on the “Knowledge-Skills-Attitude” Medical Competency Model. Two Delphi rounds (100% response rate; consensus threshold: mean ≥ 4.0, CV ≤ 0.25) refined the framework. Core competencies were prioritized via Analytic Hierarchy Process (AHP). The final consensus document was established after multiple expert group meetings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The consensus defines AI literacy for medical students as a comprehensive attribute for integrating AI into professional knowledge, clinical practice, research, and health management. It comprises a 21-item Competencies of AI Proficiency (CAIP) list across knowledge (eight indicators), skills (seven indicators), and attitude (six indicators) dimensions. Key competencies prioritized include understanding AI's role in multidisciplinary knowledge integration (CAIP3), identifying AI output biases (CAIP4), understanding health data governance (CAIP2), maintaining physician-led AI-assisted diagnosis (CAIP16), and identifying AI diagnostic biases (CAIP12). A multi-modal assessment framework is recommended, including paper-based/computerized tests for knowledge, situational judgment tests (SJTs) for attitudes, and objective structured clinical examinations (OSCEs) with a specific “AI Clinical Decision Conflict Scoring Scale” for skills. A multi-stage dynamic assessment system (“Pre-enrollment–Pre-clinical–Post-clinical”) is proposed for longitudinal tracking. Educational integration pathways emphasize embedding AI literacy modularly from early undergraduate years, constructing an integrated curriculum covering fundamental principles, advanced large model applications (e.g., prompt engineering, agent development), and ethical considerations, supported by a “digital twin hospital platform.”</p>\u0000 </section>\u0000 ","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 1","pages":"49-57"},"PeriodicalIF":3.3,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12946706/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electroacupuncture for Managing Chemotherapy-Induced Gastrointestinal Symptom Clusters in Patients With Breast Cancer: Study Protocol for a Randomized Controlled Trial","authors":"Xinlong Tao,&nbsp;Zhen Liu,&nbsp;Miaozhou Wang,&nbsp;Dengfeng Ren,&nbsp;Fuxing Zhao,&nbsp;Hongbin Wang,&nbsp;Guowang Yang,&nbsp;Ganlin Zhang,&nbsp;Zitao Li,&nbsp;Zhilin Liu,&nbsp;Shifen Huang,&nbsp;Yongzhi Chen,&nbsp;Mengting Da,&nbsp;Xiaoyan Ma,&nbsp;Hongxia Liang,&nbsp;Yongxin Li,&nbsp;Yinyin Ye,&nbsp;Yonghui Zheng,&nbsp;Xiao Liang,&nbsp;Guoshuang Shen,&nbsp;Xiaorong Bai,&nbsp;Jiuda Zhao","doi":"10.1002/hcs2.70056","DOIUrl":"10.1002/hcs2.70056","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Chemotherapy-induced gastrointestinal symptom clusters in breast cancer impair quality of life and treatment adherence, yet lack effective interventions. While acupuncture mitigates isolated chemotherapy-induced symptoms, its mechanisms for multi-symptom clusters remain unclear. This study evaluates electroacupuncture's efficacy and explores its biological mechanisms in managing these clusters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This prospective, multicenter, block-randomized, double-blind, sham-controlled trial will enroll 388 patients with breast cancer undergoing neoadjuvant/adjuvant chemotherapy, to be randomly assigned (1:1) to electroacupuncture or sham electroacupuncture groups. Both groups will receive the standard quadruple antiemetic regimen combined with electroacupuncture or sham intervention. The primary endpoint is the incidence of chemotherapy-induced gastrointestinal symptom clusters within 120 h after chemotherapy. Secondary endpoints include improvement in gastrointestinal symptom clusters post-first chemotherapy cycle, nausea-free rates during acute and delayed phases, vomiting-free rates during overall, acute, and delayed phases, complete response rate, complete protection rate, and quality of life. Adverse events will be documented throughout the study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This study will assess the efficacy and safety of electroacupuncture in alleviating chemotherapy-induced gastrointestinal symptom clusters in patients with breast cancer. By integrating multi-omics analyses, we aim to elucidate the biological mechanisms underlying its therapeutic effects. The findings may offer a robust clinical foundation for optimizing symptom cluster management in cancer care.</p>\u0000 \u0000 <p><b>Trial Registration:</b> Clinical Trials ID: NCT06952920. Date of registration: April 16, 2025. Prospectively registered. URL of Trial Registry Record: https://clinicaltrials.gov/study/NCT06952920cond=NCT06952920&amp;rank=1.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 1","pages":"85-94"},"PeriodicalIF":3.3,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12946714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147329054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey on Medical Competence Evaluation Benchmarks for Large Language Models","authors":"Qiting Wang,&nbsp;Huiru Zou,&nbsp;Haobin Zhang,&nbsp;Yongshun Huang,&nbsp;Junzhang Tian,&nbsp;Weibin Cheng","doi":"10.1002/hcs2.70050","DOIUrl":"10.1002/hcs2.70050","url":null,"abstract":"<p>Large language models (LLMs) show considerable potential to revolutionize healthcare through their performance across diverse clinical applications. Given the inherent constraints of LLMs and the critical nature of medical practice, a rigorous and systematic evaluation of their medical competence is imperative. This study presents a comprehensive review of the established methodologies and benchmarks for evaluating the medical competence of LLMs, encompassing a thorough analysis of current assessment practices across medical knowledge, clinical practice competence, and ethical–safety considerations. By integrating clinician competency assessment frameworks into LLMs evaluation, we propose a structured tri-dimensional framework that systematically organizes existing evaluation approaches according to medical theoretical knowledge, clinical practice ability, and ethical–safety considerations. Furthermore, this research provides critical insights into future developmental trajectories while establishing foundational frameworks and standardization protocols for the integration of LLMs into medical practice.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 1","pages":"4-18"},"PeriodicalIF":3.3,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12946712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three Shifts That Will Redefine Health Systems","authors":"You Wu,&nbsp;Haibo Wang,&nbsp;Zongjiu Zhang","doi":"10.1002/hcs2.70051","DOIUrl":"10.1002/hcs2.70051","url":null,"abstract":"&lt;p&gt;Academic journals, consulting firms, and mainstream media have often published “predictions” about the future development of medical and health care. These publications often emphasize the potential of cutting-edge scientific or technical breakthroughs. &lt;i&gt;Health Care Science&lt;/i&gt; looks at the problem from another perspective. We focus on how these changes enter the health system, how they operate in the real world, and how they reshape the organization and governance of medical services. At the beginning of 2026, we envision the following three major shifts that will reshape healthcare.&lt;/p&gt;&lt;p&gt;Although the concept of shifting “from sick care to health care” has been discussed for more than a decade [&lt;span&gt;1&lt;/span&gt;], healthcare systems are still largely organized around treating disease after it appears. Patients develop symptom, seek care, and health providers respond. This approach is gradually changing, as advances in data collection, monitoring, and risk modeling allow earlier identification of health risks and diseases, sometimes even before clinical symptoms emerge.&lt;/p&gt;&lt;p&gt;Effective prevention also depends on the built healthy environment of the population. Our living conditions, nutritional status, and physical capacity are the foundations, based on which disease prevention can be translated into health benefits. This change will also require adjustments in health financing models, and shift the window of performance evaluation to cover health benefits such as DALY or QALY saved.&lt;/p&gt;&lt;p&gt;For health services research, we propose the following research priority: when should predicted risks lead to intervention; how to avoid overdiagnosis and unnecessary anxiety among patients; how to coordinate across hospitals, public health sectors, community and society; and how to ensure that preventive strategies benefit all populations rather than widening inequalities [&lt;span&gt;2&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Patients today expect timely, seamless, and accessible healthcare services across everyday settings—at home, in workplace, even during travels. Medical services should strive to meet the needs of patients and rethink how care is organized and delivered. Wearable devices and sensors have expanded the scope of health-related data, making it possible to gather information that was previously difficult to obtain outside traditional healthcare settings [&lt;span&gt;3&lt;/span&gt;]. Meanwhile, AI is no longer limited to completing single task; it is streamlining daily clinical operations. Technology could be the solution, but its impact will depend on how well it is integrated into the existing health systems. That is why we see digital health platforms becoming critical infrastructures to connect hospitals, providers, and patients across different stages of care.&lt;/p&gt;&lt;p&gt;As these technologies move from development into deployment, governance frameworks became a central challenge [&lt;span&gt;4&lt;/span&gt;]. Unintended consequences have been reported from early AI uses in academic and clinical se","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 1","pages":"1-3"},"PeriodicalIF":3.3,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12946704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Large Language Models for Early Article Identification in Otolaryngology—Head and Neck Surgery Systematic Reviews","authors":"Ajibola B. Bakare,&nbsp;Young Lee,&nbsp;Jhuree Hong,&nbsp;Claus-Peter Richter,&nbsp;Jonathan P. Kuriakose","doi":"10.1002/hcs2.70048","DOIUrl":"10.1002/hcs2.70048","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Assess ChatGPT and Bard's effectiveness in the initial identification of articles for Otolaryngology—Head and Neck Surgery systematic literature reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Three PRISMA-based systematic reviews (Jabbour et al. 2017, Wong et al. 2018, and Wu et al. 2021) were replicated using ChatGPTv3.5 and Bard. Outputs (author, title, publication year, and journal) were compared to the original references and cross-referenced with medical databases for authenticity and recall.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Several themes emerged when comparing Bard and ChatGPT across the three reviews. Bard generated more outputs and had greater recall in Wong et al.'s review, with a broader date range in Jabbour et al.'s review. In Wu et al.'s review, ChatGPT-2 had higher recall and identified more authentic outputs than Bard-2.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Large language models (LLMs) failed to fully replicate peer-reviewed methodologies, producing outputs with inaccuracies but identifying relevant, especially recent, articles missed by the references. While human-led PRISMA-based reviews remain the gold standard, refining LLMs for literature reviews shows potential.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 1","pages":"19-28"},"PeriodicalIF":3.3,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12946713/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of Skeletal Muscle, Body Fat and Frailty With Prolonged Length of Hospital Stay Following Colectomy for Adenocarcinoma: A Pilot Case-Control Study.","authors":"Annmarie Butare, Justin Drake, Michael D Honaker","doi":"10.1002/hcs2.70058","DOIUrl":"https://doi.org/10.1002/hcs2.70058","url":null,"abstract":"<p><p>Physical fitness is well-known to be associated with health outcomes. This pilot study examined the impact of different measures of fitness on length of stay following colectomy. A case-control study was designed to evaluate the effect of skeletal muscle mass, body fat, and frailty measures on post-operative length of stay (LOS). A simple random sample of 50 patients in each arm was selected based on prolonged LOS. Binary logistic regression analysis was performed to determine associations between each covariate and LOS. After exclusions, 40 cases and 36 controls were included in the analysis. Frailty, as determined by weight loss and the Modified Frailty Index was not associated with prolonged LOS (<i>p</i> = 0.060 and <i>p</i> = 0.469). Cross-sectional muscle area (OR: 0.994, 95% CI: 0.989-0.999, <i>p</i> = 0.029) and skeletal muscle index (OR: 0.981, 95% CI: 0.965-0.996, <i>p</i> = 0.015) were associated with decreased LOS. Measures of body fat, as well as muscle-to-body fat ratios were not associated with LOS. These results suggest that body fat may be less influential than skeletal muscle when predicting post-operative outcomes. This pilot study warrants further investigation with a larger number of patients to identify cut-off values with which to provide targeted prehabilitation.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"5 2","pages":"95-97"},"PeriodicalIF":3.3,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13109836/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147793891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insulin-Related Consumables Should not be Ignored While Pooling Insulin Purchases: Experience From China","authors":"Jingya Zhang,&nbsp;Haoran Li,&nbsp;Ning Zhang,&nbsp;Ying Mao,&nbsp;Bin Zhu","doi":"10.1002/hcs2.70046","DOIUrl":"10.1002/hcs2.70046","url":null,"abstract":"<p>A series of measures to implement national volume-based procurement (NVBP) and follow-on NVBP in China have significantly reduced insulin prices and increased patient affordability. However, NVBP may lead to a higher burden of insulin-related consumables (such as injection pens and needles), which might discourage patients from using insulin in the pooled list and increase the risk of needle reuse. This article emphasizes that it is essential NVBP be implemented for both drugs and consumables, which will contribute to the achievement of universal insulin access.</p>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 6","pages":"410-413"},"PeriodicalIF":3.3,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development on the Proficiency of Diagnosis and Clinical Care for Rare Diseases in Young Physicians in China","authors":"Ge Wu,&nbsp;Yongzhang Miao,&nbsp;Siyuan Fan,&nbsp;Wanru Duan,&nbsp;Junyan Qian,&nbsp;Dawei Wu,&nbsp;Eray Yihui Zhou,&nbsp;Zhongli Xu,&nbsp;Jing Xie,&nbsp;Mengchun Gong,&nbsp;Shuyang Zhang","doi":"10.1002/hcs2.70042","DOIUrl":"10.1002/hcs2.70042","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>As medical advancements continue and public health levels rise, increasing attention is being paid to the diagnosis and treatment of rare diseases. Given its large population, China's efforts in enhancing overall clinical abilities for rare disease diagnosis and treatment are crucial. However, young physicians still face significant challenges in their professional capabilities in this field.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Based on interviews with young physicians and medical education experts from rare disease diagnosis and research institutions, this study explored systematic approaches to cultivating and enhancing the expertise of young Chinese physicians in rare disease diagnosis and treatment, along with the necessary support systems.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>By thematic analysis, we identified six effective training models: (1) mentorship teaching, (2) specialized training systems, (3) integration of rare disease knowledge into standard curricula, (4) continuous education and career path planning, (5) application of information technology, and (6) institution-supported international collaboration. We also discussed critical implementation challenges such as resource intensity and interdisciplinary friction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Based on these findings, we proposed a series of targeted strategies and recommendations. This study provided valuable experiences for young physicians in clinical and research institutions nationwide, thereby improving the overall level of rare disease diagnosis and treatment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 6","pages":"414-423"},"PeriodicalIF":3.3,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Language Barriers in the Federal Republic of Somalia's Healthcare: Addressing Inclusivity for Minority Dialects","authors":"Najib Isse Dirie,&nbsp;Mohamed Mustaf Ahmed","doi":"10.1002/hcs2.70043","DOIUrl":"10.1002/hcs2.70043","url":null,"abstract":"&lt;p&gt;The Federal Republic of Somalia, often perceived as linguistically homogeneous, is home to a rich tapestry of dialects and minority languages that reflect its diverse cultural heritage. While Somali is the official medium of communication, it is divided into two major dialects: Maxaa Tiri (spoken by approximately 60% of the population) and Maay (spoken by approximately 20% of the population) [&lt;span&gt;1&lt;/span&gt;]. Minority languages such as Bravanese (also known as Chimwiini or Chimbalazi), Mushunguli, Benadiri Somali, and Kibajuni are spoken by smaller communities, particularly in the southern and coastal regions [&lt;span&gt;1&lt;/span&gt;]. Despite the demographic linguistic diversity shown in Table 1, Maxaa Tiri holds institutional dominance, functioning as the primary dialect in healthcare delivery, official communication, and in documentation [&lt;span&gt;2&lt;/span&gt;]. This dominance marginalizes Maay speakers and other minority languages, limiting their access to healthcare information and services [&lt;span&gt;2&lt;/span&gt;]. Effective communication between healthcare providers and patients is essential for informed consent, accurate diagnosis, appropriate treatment, and patient safety [&lt;span&gt;3&lt;/span&gt;]. However, language barriers prevent many minority‑language speakers from accessing these critical aspects of care.&lt;/p&gt;&lt;p&gt;Health campaigns and medical documentation are predominantly conducted in Maxaa Tiri, leaving minority language speakers unable to fully understand vital health information [&lt;span&gt;2, 4&lt;/span&gt;]. Rural areas in the Federal Republic of Somalia are particularly vulnerable to the consequences of this linguistic exclusion. These regions often lack sufficient healthcare infrastructure and are home to many speakers of Maay and other minority dialects [&lt;span&gt;2, 4&lt;/span&gt;]. In such areas, healthcare workers may not speak local dialects, leading to frequent miscommunication. Moreover, health information, whether disseminated via campaigns, posters, or mobile platforms, is almost exclusively provided in Maxaa Tiri. This renders it inaccessible to large rural populations in developing countries. Consequently, residents of these regions are less likely to engage with health services, contributing to lower vaccination rates, delays in seeking care and poorer health outcomes.&lt;/p&gt;&lt;p&gt;This disconnection likely contributes to poorer health outcomes in minority communities. Although specific statistical data quantifying these outcomes are currently unavailable for the Federal Republic of Somalia, studies from similar low-resource settings have consistently demonstrated that language barriers lead to decreased healthcare utilization, reduced adherence to medical instructions, and increased patient safety risk [&lt;span&gt;5, 6&lt;/span&gt;]. This commentary analyzes the linguistic barriers faced by minority language speakers in accessing healthcare in the Federal Republic of Somalia. It explores solutions through inclusive policies, digital health platforms and global best practices. By ad","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 6","pages":"427-431"},"PeriodicalIF":3.3,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The First Clinical Renal Xenotransplantation Study (EXPAND): Evaluating Safety, Function, and Zoonotic Risks","authors":"Björn Nashan","doi":"10.1002/hcs2.70044","DOIUrl":"10.1002/hcs2.70044","url":null,"abstract":"&lt;p&gt;On November 3, 2025, United Therapeutics Corporation (Nasdaq: UTHR) announced the first clinical xenotransplantation within its EXPAND study, involving transplantation of the UKidney into a patient with end-stage renal disease (ESRD) at New York University (NYU) Langone Health. The UKidney is a genetically engineered porcine kidney incorporating 10 gene modifications—6 human gene insertions to enhance immunologic compatibility and 4 porcine gene knockouts to minimize rejection risk and control graft growth [&lt;span&gt;1&lt;/span&gt;]. In the context of the first xenotransplantation studies, “EXPAND” refers to the US Food and Drug Administration (FDA) “expanded access” program, often colloquially known as compassionate use. This program provides a pathway for seriously ill patients who have no other treatment options to receive an investigational medical device, in this case, a genetically modified pig heart, outside of a traditional clinical trial.&lt;/p&gt;&lt;p&gt;This announcement arrived just in time, since the last recipient, a 67-year-old male recipient at Massachusetts General Hospital, underwent removal of a genetically modified porcine kidney 9 months post-transplant due to progressive graft dysfunction in October 2025. The patient survived 271 days, representing the longest reported survival following a pig-to-human kidney xenotransplantation. Previous recipients experienced early graft loss or rejection. The case demonstrates extended graft viability and provides valuable clinical insight into the long-term outcomes of renal xenotransplantation [&lt;span&gt;2&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;The EXPAND study (NCT06878560) is a multicenter, open-label, interventional clinical trial sponsored by United Therapeutics Corporation. The study represents the first regulated clinical xenotransplantation program evaluating the &lt;i&gt;UKidney&lt;/i&gt;, a 10-gene–edited porcine kidney in patients with ESRD who are ineligible for or unlikely to receive a human donor kidney within 5 years. The first xenotransplantation under this protocol was successfully performed at NYU Langone Health on November 3, 2025 [&lt;span&gt;3, 4&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;The &lt;i&gt;UKidney&lt;/i&gt; is derived from a genetically engineered pig designed to enhance immunological compatibility and control organ growth. The genome modification includes six human gene insertions (knock-ins) that promote immune tolerance, regulate coagulation, and protect against complement-mediated injury, as well as four porcine gene deletions (knockouts) that remove carbohydrate epitopes responsible for hyperacute rejection and prevent excessive graft growth (Table 1) [&lt;span&gt;5&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;The primary objective of EXPAND is to evaluate the safety, tolerability, and functional performance of the xenograft at 24 weeks post-transplantation. Primary endpoints include patient and graft survival, while secondary endpoints assess glomerular filtration rate, proteinuria, and the incidence of xenograft rejection, infection, or other adverse events. Long-term follow-up will mo","PeriodicalId":100601,"journal":{"name":"Health Care Science","volume":"4 6","pages":"377-380"},"PeriodicalIF":3.3,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12728669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145835903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}