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Background: Performing emergency surgery for bowel obstruction continues to place a significant strain on the healthcare system. Conventional assessment methods for outcomes in bowel obstruction cases often concentrate on isolated factors, and the evaluation of results for individuals with bowel obstruction remains poorly studied. This study aimed to examine the risk factors associated with major postoperative complications. Methods: We retrospectively analyzed 99 patients undergoing surgery from 2015 to 2022. We divided the patients into two groups: (1) benign-related obstruction (n = 68) and (2) cancer-related obstruction (n = 31). We used logistic regression, KNN, and XGBOOST. We calculated the receiver operating characteristic curve and accuracy of the model. Results: Colon obstructions were more frequent in the cancer group (p = 0.005). Operative time, intestinal resection, and stoma were significantly more frequent in the cancer group. Major complications were at 41% for the cancer group vs. 20% in the benign group (p = 0.03). Uni- and multivariate analysis showed that the significant risk factors for major complications were cancer-related obstruction and CRP. The best model was KNN, with an accuracy of 0.82. Conclusions: Colonic obstruction is associated with tumor-related blockage. Malignant cancer and an increase in C-reactive protein (CRP) are significant risk factors for patients who have undergone emergency surgery due to major complications. KNN could improve the process of counseling and the perioperative management of patients with intestinal obstruction in emergency settings. [ABSTRACT FROM AUTHOR]

The dawn of Artificial intelligence (AI) in healthcare stands as a milestone in medical innovation. Different medical fields are heavily involved, and pediatric emergency medicine is no exception. We conducted a narrative review structured in two parts. The first part explores the theoretical principles of AI, providing all the necessary background to feel confident with these new state-of-the-art tools. The second part presents an informative analysis of AI models in pediatric emergencies. We examined PubMed and Cochrane Library from inception up to April 2024. Key applications include triage optimization, predictive models for traumatic brain injury assessment, and computerized sepsis prediction systems. In each of these domains, AI models outperformed standard methods. The main barriers to a widespread adoption include technological challenges, but also ethical issues, age-related differences in data interpretation, and the paucity of comprehensive datasets in the pediatric context. Future feasible research directions should address the validation of models through prospective datasets with more numerous sample sizes of patients. Furthermore, our analysis shows that it is essential to tailor AI algorithms to specific medical needs. This requires a close partnership between clinicians and developers. Building a shared knowledge platform is therefore a key step. [ABSTRACT FROM AUTHOR]

In the transformative landscape of healthcare, personalized medicine emerges as a pivotal shift, harnessing genetic, environmental and lifestyle data to tailor medical treatments for enhanced outcomes and cost efficiency. Central to its success is public engagement and consent to share health data amidst rising data privacy concerns. To investigate European public opinion on this paradigm, we executed a comprehensive cross-sectional survey to capture the general public's views on personalized medicine and data-sharing modalities, including digital tools and electronic records. The survey was distributed in eight major European Union countries and the results aim at guiding future policymaking and trust-building measures for secure health data exchange. This article delineates our methodological approach, whereby survey findings will be expounded in subsequent publications. Executive summary A collaborative cross-sectional online survey was developed by researchers from Università Cattolica del Sacro Cuore and Amsterdam UMC to assess European Union (EU) citizens' attitudes toward personalized medicine and genomic data sharing. Structured into four thematic modules comprising 37 questions in total, the survey comprehensively addressed individuals' knowledge, attitudes towards data sharing, governance issues and perceived personal needs related to personalized medicine. Translations into eight European languages were undertaken to ensure broad accessibility, with distribution managed by a private company, ensuring high-quality research standards and privacy compliance. The survey aims to inform and shape policy on personalized medicine by capturing a snapshot of current EU views, with an outlook on enhancing healthcare through data-driven and patient-tailored approaches. While providing valuable insights for EU policymaking in healthcare, the survey acknowledges limitations such as potential online user bias, language restrictions and self-reported data accuracy. [ABSTRACT FROM AUTHOR]

Advancements in genomics have significant implications for public health, making citizens' education vital for informed decision-making. Based on two literature reviews' findings and a survey conducted with experts from the Italian Network of Genomics in Public Health, we conducted a pilot survey on Italian citizens' attitudes, knowledge and educational needs toward genetic testing and omics sciences. Our results demonstrate a widespread interest in genetic testing and uncertainties regarding associated risks, with 99% of participants acknowledging insufficient knowledge of genetic testing. There is an urgent need for educational tools to improve citizens' literacy and engagement in this rapidly evolving field. [ABSTRACT FROM AUTHOR]

Introduction: Over the last decade, the emergence and spread of personalized medicine (PM) have defined a substantial revolution in healthcare. In principle, healthcare system sustainability is challenged by the investments required for research and development, as well as the adoption of PM techniques in routine clinical care. The "Integrating China in the International Consortium for Personalized Medicine" (IC2PerMed) EU-funded project aims to integrate China into the "International Consortium for Personalized Medicine" (ICPerMed). IC2PerMed aims to align the EU and China's research agendas in this field to enable a swift development of approaches in the EU and China with strong leverage upon EU-Chinese collaborations. Methods: Within this project, we first mapped relevant policies on PM in both the EU and China, and then we involved European and Chinese experts in PM in workshops and Delphi surveys in order to identify relevant priorities for the implementation of PM in sustainable healthcare. Results: As a result of this process, we identified nine overarching priorities, each addressing specific aspects of the sustainability of healthcare systems and PM implementation, with the main goal of supporting policymakers in integrating PM approaches in the EU and China. Discussion/conclusion: The implementation of PM in health systems is appealing in terms of improved accuracy in diagnostics, treatment, and prevention of disease, as well as reduction of the side effects resulting from inefficient use of drugs. Research, development, and implementation of needed techniques require time and resources that can slow the adoption of PM in healthcare systems. The nine priorities we identified address some of the most critical points, trying to lay the foundations for a comprehensive approach. [ABSTRACT FROM AUTHOR]

Background: Personalised medicine (PM) has been fostered by technological and medical advances, but all stakeholders, including healthcare professionals, citizens and policy makers, should achieve adequate health literacy to promote PM implementation. The "Integrating China in the International Consortium for Personalised Medicine" (IC2PerMed) project, funded by the International Consortium for Personalised Medicine, focuses on this issue by highlighting the need to educate healthcare professionals and empower citizens. Within the aforementioned project, building on a mapping of European and Chinese policies in PM, experts in the field of PM participated in an online workshop and a following two-round Delphi survey, in order to identify the priority areas of intervention for healthcare professionals' education and curricula, engagement and empowerment of citizens and patients. Results: Nine experts completed the survey and reached a consensus on seventeen priorities: seven were related to health professionals' education and curricula, whereas ten on citizen and patients' awareness and empowerment. Conclusion: These priorities emphasized the importance of education and health literacy, multidisciplinary and international collaboration, public trust, and consideration of ethical, legal, and social issues. The present experience highlights the relevance of the involvement of stakeholders in informing decision-makers, developing appropriate national plans, strategies, and policies, and ensuring the adequate implementation of PM in health systems. [ABSTRACT FROM AUTHOR]

Aim: Research and innovation (R&I) actors are fundamental in shortening the translational gap of personalized medicine in health systems. In the context of the 'Integrating China in the International Consortium for Personalized Medicine' project, we aimed to map the current landscape of R&I actors in the field of personalized medicine in the EU and China. Methods: A two-phase desk research study was conducted. Results: We identified 78 R&I actors. Research and technology organizations were the most frequent in both the EU and China. The identified R&I actors were active in a wide range of fields. The EU and China have many different R&I actors addressing personalized medicine-related issues, with few characteristics in common. Conclusion: More efforts are needed to ensure these R&I actors are encouraged to work together to bridge each other's gaps. [ABSTRACT FROM AUTHOR]

The 12q14 microdeletion syndrome is a rare condition characterized by low birth weight, failure to thrive, short stature, learning disabilities, and osteopoikilosis. To date, 20 cases of 12q14 deletion have been reported in the literature, displaying both phenotypic than genetic variability. We report on three familial cases, a mother and two brothers, with severe short stature. The mother and elder brother presented with osteopoikilosis while the younger brother had severe short stature and developmental delay. SNP array analysis revealed a 1.9 Mb heterozygous 12q14.2q14.3 deletion in all three patients encompassing 14 genes and 3 miRNAs. In addition, the younger brother carried a paternal 11q13.4 duplication including the SHANK2 gene. This latter patient was investigated for developmental delay and did not show osteopoikilosis, confirming the role of age in the clinical presentation of this condition. To the best of our knowledge, this is the second family described with the syndrome. Comparing the clinical and molecular data of our patients with those previously reported we performed a detailed genotype-phenotype correlation confirming the association between growth retardation and osteopoikilosis when the rearrangement includes both LEMD3 and HMGA2 genes. In addition, we suggest the XPOT, TBK1, WIF1 genes as candidates for the clinical features observed in our patients and discuss for the first time the possible involvement of some microRNAs, when deleted, in the etiology of the phenotypes in 12q14 microdeletion syndrome patients. We expect the interpretation of our findings to be useful both from a molecular point of view and for genetic counseling. [ABSTRACT FROM AUTHOR]

Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. We aimed to evaluate whether population-level vaccine effectiveness is heralded by an increase in the relative proportion of deaths among non-elderly populations that were less covered by vaccination programs. We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021–5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave). We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in (1) countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies. Countries that prioritized vaccination among older people saw an increasing share of deaths among 0–69 year old people in the vaccination versus the two control periods (summary proportion ratio 1.32 [95 CI% 1.24–1.41] and 1.35 [95 CI% 1.26–1.44)]. No such change was seen on average in countries with age-independent vaccination policies (1.05 [95 CI% 0.78–1.41 and 0.97 [95 CI% 0.95–1.00], respectively) and limited vaccination (0.93 [95 CI% 0.85–1.01] and 0.95 [95 CI% 0.87–1.03], respectively). Proportion ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0–49 among all 0–69 deaths in the vaccination versus pre-vaccination periods. The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly provides evidence for the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths. • There was a shift towards younger age strata for COVID-19 deaths in many countries in the first 5 months of deployment of COVID-19 vaccines. • This age shift was not noticed in countries that had low vaccination coverage or did not prioritize vaccination in the elderly. • The age shift in COVID-19 deaths provides strong evidence for the effectiveness of vaccination and the evolution of the pandemic towards endemicity. [ABSTRACT FROM AUTHOR]

The first annual meeting of the Italian Society for Artificial Intelligence in Medicine (Società Italiana Intelligenza Artificiale in Medicina, SIIAM) on December 7, 2023, marked a significant milestone in integrating artificial intelligence (AI) into Italy's healthcare framework. This paper reports on the collaborative workshop conducted during this event, highlighting the collective efforts of 51 professionals from diverse fields including medicine, engineering, data science, and law. The interdisciplinary background of the participants played a crucial role in generating ideas for innovative AI solutions tailored to healthcare challenges. Central to the discussions were several AI applications aimed at improving patient care and streamlining healthcare processes. Notably, the use of Large Language Models (LLMs) in remote monitoring of chronic patients emerged as an area of focus. These models promise enhanced patient monitoring through detailed symptom checking and anomaly detection, thereby facilitating timely medical interventions. Another significant proposal involved employing LLMs to improve empathy in medical communication, addressing the challenges posed by cultural diversity and high-stress levels among healthcare professionals. Additionally, the development of Machine Learning algorithms for standardizing treatment in pediatric emergency departments was discussed, along with the need for educational initiatives to enhance AI adoption in rural healthcare settings. The workshop also explored using LLMs for efficient data extraction and analysis in scientific literature, interpreting healthcare norms, and streamlining hospital discharge records. This paper provides a comprehensive overview of the ideas and solutions proposed at the workshop, reflecting the participants' forward-thinking vision and the potential of AI to revolutionize healthcare., Competing Interests: The authors declare no conflict of interest., (©2024 Pacini Editore SRL, Pisa, Italy.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Background and Objective: The capacity to promote and disseminate the best evidence-based practices in terms of digital health innovations and technologies represents an important goal for countries and governments. To support the digital health maturity across countries the Global Digital Health Partnership (GDHP) was established in 2019. The mission of the GDHP is to facilitate global collaboration and knowledge-sharing in the design of digital health services, through the administration of surveys and white papers., Objective: The scope of this study is to critically analyze and discuss results from the Evidence and Evaluation GDHP Work Stream's survey, understand how governments and countries intend to address main obstacles to the digital health implementation, identify their strategies for a communication of effective digital health services, and promote the sharing of international based best practices on digital health., Methods: This survey followed a cross-sectional study approach. A multiple-choice questionnaire was designed to gather data. Choices were extracted from research publications retrieved through a rapid review., Results: Out of 29 countries receiving the survey, 10 returned it. On a scale from 1 to 5, eHealth systems/platforms (mean = 3.56) were indicated as the most important tool for centralized infrastructure to collect information on digital health, while primary care (mean = 4.0) represented the most voted item for healthcare services to collect information on digital health. Seven Countries out of 10 identified lack of organization, skepticism of clinicians, and accessibility of the population as a barriers to adopt digital health implementation, resulting to be the most voted items. Finally, the most endorsed priorities in digital health for Countries were the adoption of data-driven approaches (6 Countries), and telehealth (5 Countries)., Conclusion: This survey highlighted the main tools and obstacles for countries to promote the implementation of evidence-based digital health innovations. Identifying strategies that would communicate the value of health care information technology to healthcare professionals are particularly imperative. Effective communication programs for clinicians and the general population in addition to improved digital health literacy (both for clinicians and citizens) will be the key for the real implementation of future digital health technologies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cascini, Gentili, Causio, Altamura, Melnyk, Beccia, Pappalardo, Lontano and Ricciardi.)

Background: To promote shared digital health best practices in a global context, as agreed within the Global Digital Health Partnership (GDHP), one of the most important topics to evaluate is the ability to detect what participating countries believe to be priorities suitable to improve their healthcare systems. No previously published scientific papers investigated these aspects as a cross-country comparison., Objective: The aim of this paper is to present results concerning the priorities identification section of the Evidence and Evaluation survey addressed to GDHP members in 2021, comparing countries' initiatives and perspectives for the future of digital health based on internationally agreed developments., Methods: This survey followed a cross-sectional study approach. An online survey was addressed to the stakeholders of 29 major countries., Results: Ten out of 29 countries answered the survey. The mean global score of 3.54 out of 5, calculated on the whole data set, demonstrates how the global attention to a digital evolution in health is shared by most of the evaluated countries., Conclusion: The resulting insights on the differences between digital health priority identification among different GDHP countries serves as a starting point to coordinate further progress on digital health worldwide and foster evidence-based collaboration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Cascini, Altamura, Failla, Gentili, Puleo, Melnyk, Causio and Ricciardi.)

Background: Clinical trials are essential for bringing new drugs, technologies and procedures to the market and clinical practice. Considering the design and the four-phase development, only 10% of them complete the entire process, partly due to the increasing costs and complexity of clinical trials. This low completion rate has a huge negative impact in terms of population health, quality of care and health economics and sustainability. Automating some of the process' tasks with artificial intelligence (AI) tools could optimize some of the most burdensome ones, like patient selection, matching and enrollment; better patient selection could also reduce harmful treatment side effects. Although the pharmaceutical industry is embracing artificial AI tools, there is little evidence in the literature of their application in clinical trials., Methods: To address this issue, we performed a scoping review. Following the PRISMA-ScR guidelines, we performed a search on PubMed for articles on the implementation of AI in the development of clinical trials., Results: The search yielded 772 articles, of which 15 were included. The articles were published between 2019 and 2022 and the results were presented descriptively. About half of the studies addressed the topic of patient recruitment; 12 articles reported specific examples of AI applications; five studies presented a quantitative estimate of the effectiveness of these tools., Conclusion: All studies present encouraging results on the implementation of AI-based applications to the development of clinical trials. AI-based applications have a lot of potential, but more studies are needed to validate these tools and facilitate their adoption., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cascini, Beccia, Causio, Melnyk, Zaino and Ricciardi.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.