OBJECTIVES

Clinical pathways (CPs) ensure adherence to heart failure (HF) management guidelines. To optimize quality care in a low resource setting, an evidence-based care pathway for the management of acute HF was implemented at the emergency department (ED) of the Philippine General Hospital (PGH), the designated national tertiary hospital and referral center. This study aimed to describe the characteristics of adults with acute HF admitted at the ED and evaluate the quality of care they received, measured using physician adherence to the hospital’s acute heart failure CP.

METHODS

This was a retrospective, descriptive cohort study. We reviewed the inpatient charts of all adult patients with acute HF admitted to the ED of the PGH and referred to the Division of Cardiovascular Medicine between December 1, 2022 and May 31, 2023. Quality of care was assessed based on adherence to quality indicators adapted from routine and conditional order sets detailed in the pathway. Descriptive statistics was utilized to describe patient characteristics, quality of care, and outcomes.

RESULTS

Two hundred thirty-six (236) patients were included, with a mean age of 51.8 years. Majority were male (53.4%); hypertension (61.4%) and ischemic heart disease (53.8%) were the most common comorbidities, and infection the most common precipitant of decompensation (60.6%). There were optimal adherence rates to routine orders, which included referrals to Internal Medicine and Cardiology, baseline vital signs monitoring, fluid intake and output monitoring, chest radiograph, complete blood count, blood urea nitrogen, sodium, potassium, prothrombin time, partial thromboplastin time, arterial blood gas, urinalysis, and N-terminal pro b-type natriuretic peptide. Conditional orders, such as oxygen support, focused echocardiography, thyroid - stimulating hormone, and the use of vasopressors, diuretics, and venous thromboembolism prophylactic agents, were optimally performed when warranted. However, we noted suboptimal adherence to certain resource-intensive conditional orders, such as hourly monitoring of urine output (61.4%), hooking to cardiac monitor (53.8%), and performance of 12-lead ECG within 10 minutes (56.8%). Further, only 43.9% of patients were referred to the intensive care unit. Troponin I, calcium, magnesium, and albumin were ordered in excess.

CONCLUSION

Overall adherence rate of physicians to the hospital’s Acute Heart Failure Pathway was satisfactory. Work is needed to improve adherence to hourly urine output monitoring, consistent hooking to cardiac monitor, and timely performance of 12-lead ECG – an effort that begins with expanding in-hospital diagnostic equipment and human resource supply. We recommend continuous pathway implementation with periodic evaluation and stakeholder feedback to further improve quality of care.

Human ; Male ; Female ; Middle Aged: 45-64 Yrs Old ; Adult ; Albumins ; Blood ; Blood Urea Nitrogen ; Calcium ; Cardiology ; Chart ; Charts ; Cohort Studies ; Critical Care ; Critical Pathways ; Diagnostic Equipment ; Disease ; Diuretics ; Echocardiography ; Electrocardiography ; Emergencies ; Emergency Service, Hospital ; Equipment And Supplies ; Evaluation Studies As Topic ; Feedback ; Heart ; Heart Diseases ; Heart Failure ; Hormones ; Hospitals ; Hospitals, General ; Humans ; Hypertension ; Indicators And Reagents ; Infection ; Infections ; Inpatients ; Intensive Care Units ; Internal Medicine ; Lead ; Magnesium ; Male ; Medicine ; Myocardial Ischemia ; Natriuretic Peptide, Brain ; Natriuretic Peptides ; Nitrogen ; Overall ; Oxygen ; Partial Thromboplastin Time ; Patients ; Peptides ; Philippines ; Physicians ; Potassium ; Prothrombin ; Prothrombin Time ; Quality Of Health Care ; Referral And Consultation ; Sodium ; Statistics ; Tertiary Care Centers ; Thorax ; Thromboembolism ; Thromboplastin ; Thyroid Gland ; Time ; Troponin ; Troponin I ; Universities ; Urea ; Urinalysis ; Urine ; Venous Thromboembolism ; Vital Signs ; Work ; Workforce

The paper summarizes the authorized invention patents, device registration and the relevant published articles of acupuncture medical devices of TCM in recent 5 years, and analyzes the current status and challenges in this field. It is discovered that the optimization and substitution in diagnosis and treatment of acupuncture are involved in the development of acupuncture medical devices. The technology application of these devices are composed of traditional and emerging engineering technologies; and the theoretical guidance for their development requires the integration of traditional acupuncture principles with modern medical theories. The development of acupuncture medical devices highlights the characteristics of multidimensional integration, treatment for specific ailments, portability and wearability, painlessness and non-invasion, precision and personalization, as well as intelligent automation. Upon analysis, it is shown that in the development and product transformation of acupuncture medical devices in recent years, the theoretical principles of acupuncture of TCM have not been fully utilized yet, the transformation of patented product is low, the clinical evidence of product is insufficient, and the market competitiveness needs improvement. In the future, The theoretic guidance of acupuncture of TCM should be enhanced in the development of acupuncture medical devices, a production-education- research model with the combination of medicine and engineering be constructed, clinical verification of product be emphasized, and product development paradigms be advanced, so as to meet the demands of the medical market.
Acupuncture Therapy/trends* ; Humans ; Medicine, Chinese Traditional/instrumentation* ; Equipment and Supplies

The objective of this study is to map the global scientific competitive landscape in the field of artificial intelligence (AI) medical devices using scientific data. A bibliometric analysis was conducted using the Web of Science Core Collection to examine global research trends in AI-based medical devices. As of the end of 2023, a total of 55 147 relevant publications were identified worldwide, with 76.6% published between 2018 and 2024. Research in this field has primarily focused on AI-assisted medical image and physiological signal analysis. At the national level, China (17 991 publications) and the United States (14 032 publications) lead in output. China has shown a rapid increase in publication volume, with its 2023 output exceeding twice that of the U.S.; however, the U.S. maintains a higher average citation per paper (China: 16.29; U.S.: 35.99). At the institutional level, seven Chinese institutions and three U.S. institutions rank among the global top ten in terms of publication volume. At the researcher level, prominent contributors include Acharya U Rajendra, Rueckert Daniel and Tian Jie, who have extensively explored AI-assisted medical imaging. Some researchers have specialized in specific imaging applications, such as Yang Xiaofeng (AI-assisted precision radiotherapy for tumors) and Shen Dinggang (brain imaging analysis). Others, including Gao Xiaorong and Ming Dong, focus on AI-assisted physiological signal analysis. The results confirm the rapid global development of AI in the medical device field, with "AI + imaging" emerging as the most mature direction. China and the U.S. maintain absolute leadership in this area-China slightly leads in publication volume, while the U.S., having started earlier, demonstrates higher research quality. Both countries host a large number of active research teams in this domain.
Artificial Intelligence ; Bibliometrics ; Humans ; China ; Equipment and Supplies ; United States ; Biomedical Research

The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine and intelligent care. However, the artificial intelligent medical device sector still faces significant challenges, such as data privacy protection and algorithm reliability. This study, based on invention patent analysis, revealed the technological innovation trends in the field of artificial intelligent medical devices from aspects such as patent application time trends, hot topics, regional distribution, and innovation players. The results showed that global invention patent applications had remained active, with technological innovations primarily focused on medical image processing, physiological signal processing, surgical robots, brain-computer interfaces, and intelligent physiological parameter monitoring technologies. The United States and China led the world in the number of invention patent applications. Major international medical device giants, such as Philips, Siemens, General Electric, and Medtronic, were at the forefront of global technological innovation, with significant advantages in patent application volumes and international market presence. Chinese universities and research institutes, such as Zhejiang University, Tianjin University, and the Shenzhen Institute of Advanced Technology, had demonstrated notable technological innovation, with a relatively high number of patent applications. However, their overseas market expansion remained limited. This study provides a comprehensive overview of the technological innovation trends in the artificial intelligent medical device field and offers valuable information support for industry development from an informatics perspective.
Artificial Intelligence ; Patents as Topic ; Humans ; Inventions ; China ; Brain-Computer Interfaces ; Telemedicine ; Equipment and Supplies ; Robotics ; Algorithms

The rapid development of artificial intelligence technology is driving profound changes in medical practice, particularly in the field of medical device application. Based on data from the U.S. clinical trials registry, this study analyzes the global registration landscape of clinical trials involving artificial intelligence-based medical devices, aiming to provide a reference for their clinical research and application. A total of 2 494 clinical trials related to artificial intelligence medical devices have been registered worldwide, with participation from 66 countries or regions. The United States leads with 908 trials, while for other countries or regions, including China, each has fewer than 300 trials. Germany, the United States, and Belgium serve as central hubs for international collaboration. Among the sponsors, 63.96% are universities or hospitals, 22.36% are enterprises, and the remainder includes individuals, government agencies and others. Of all trials, 79.99% are interventional studies, 94.67% place no restrictions on participant gender, and 69.69% exclude children. The targeted diseases are primarily neurological and mental disorders. This study systematically reveals the global distribution characteristics and research trends of artificial intelligence medical device clinical trials, offering valuable data support and practical insights for advancing international collaboration, resource allocation, and policy development in this field.
Artificial Intelligence ; Humans ; Clinical Trials as Topic/statistics & numerical data* ; Equipment and Supplies ; Registries ; United States

In recent years, the research on artificial intelligence medical devices has risen markedly along with the expanding application scenarios, exhibiting prominent interdisciplinary characteristics. From 2000 to 2024, the variety of research in artificial intelligence medical devices has significantly increased, while the balance of disciplines has slightly declined, and Simpson's diversity index has continuously increased. Medicine and biology are the main research themes and supportive disciplines in this field. Knowledge from computer science, engineering technology, and mathematics is widely involved and shows an upward trend, while content from the humanities and social sciences is less involved in the research. Compared to the United States and the United Kingdom, China has relatively less biological and chemical knowledge content in the research of this field, but more content related to computer science, engineering technology and material science is involved. This study analyzes the current state and trends of interdisciplinary on artificial intelligence medical devices from the perspective of macro-categories of disciplines, aiming to provide references for research planning, talent training and interdisciplinary cooperation in the field.
Artificial Intelligence ; Humans ; Equipment and Supplies ; Interdisciplinary Research

BACKGROUND AND OBJECTIVES

Mouth retractors are essential in ensuring efficient yet safe exposure of the oral cavity and oropharynx. However, when applied improperly or haphazardly, retractors can cause tissue injuries and compromise patient safety. In addition, there are gaps in the usability of existing designs. This study aimed to identify the issues encountered by otorhinolaryngology surgeons in the use of commercially available mouth retractors, design and fabricate an improved retractor, and explore the use of additive manufacturing (popularly known as 3D printing) for retractor prototyping.

METHODS

The study used the United States Food and Drug Administration (US FDA) Design Control as its framework. End-user requirements from otorhinolaryngologists were collected through key informant interviews. Results were organized into a Design Input template which was used to guide the design and development process. Prototype designs were iteratively created using computer-aided design software and 3D printing. Once design specifications were satisfied, a beta prototype was fabricated and given to another cohort of otorhinolaryngologists. The participants assessed the usability of the beta prototype. System Usability Scale (SUS) was used to quantify participant's feedback.

RESULTS

Five designs were created in the course of the study. The final prototype was fabricated using a Stereolithography (SLA) 3D printer. Several features were developed to address user requirements. The primary modification was to make the retractor modular to facilitate easier and shorter mounting and assembly. Gingival injury was addressed with the replacement of the maxillary alveolus hook with support bars. Five participants evaluated the beta prototype which received a mean SUS score of 75, well above the 50th percentile threshold.

CONCLUSION

This study demonstrates the applicability of the US FDA Design Control Process in the local setting to improve the mouth retractor design. Clinical and ergonomic issues were identified and design solutions were proposed and some have been implemented in a low-fidelity prototype. Results of the small-scale usability test suggest that the present form factor can be the basis for further iterations. Future studies can implement the proposed features to address other clinical and ergonomic needs.

Human ; 3d Printing ; Printing, Three-dimensional ; Devices, Medical ; Equipment And Supplies

The objective of inspection, testing and supervision of medical devices is to ensure the effectiveness and safety of medical devices in use. Leachables are substances that are leached from medical devices or materials during their clinical use. Leachables are important factors for the safety risks of medical devices. The analysis, detection, and safety evaluation of leachables are important parts of the safety evaluation of medical devices. The allowable limits for leachable substances which are established on the toxicological research provide a scientific basis for the judgment of qualitative and quantitative analysis results. Obtaining more detailed, rigorous and sufficient toxicological research data is of great significance to set highly enforceable product technical indicators. For the establishment of allowable limits for leachable substances, its role in the safety evaluation of medical devices is summarized, and the relevant standards and their implementation status in the testing of medical devices are introduced.
Equipment and Supplies/standards* ; Equipment Safety

Medical equipment management plays a crucial role in enhancing the quality and efficiency of healthcare services. However, traditional management approaches are increasingly inadequate to meet the growing demands of modern healthcare. As intelligent operation and maintenance (O&M) models based on big data, the Internet of Things (IoT), and artificial intelligence (AI) technologies develop, it is imperative to explore their application in medical equipment management. This paper reviews the technical overview of intelligent O&M and discusses the algorithms and challenges of intelligent O&M models based on different technologies. It also proposes issues that need improvement in intelligent O&M models, aiming to provide valuable references for the future development of medical equipment management.
Artificial Intelligence ; Algorithms ; Internet of Things ; Equipment and Supplies ; Big Data

The rapid development of nanomaterials has brought groundbreaking opportunities for high-quality innovation in medical devices, but it has also become a new challenge for regulatory authorities. How to scientifically and rationally evaluate the risks of medical device products with nanomaterials and establish appropriate regulatory classifications have become critical research priorities. To solve this problem, this study focuses on medical devices with nanomaterials, conducts a comparative analysis of domestic and international regulatory classification policies, reviews the current registration status of related products, and provides recommendations on key considerations for the classification and regulation of medical devices with nanomaterials, which aims at promoting high-quality advancement in China's medical device regulation.
Nanostructures/classification* ; Equipment and Supplies/classification*