The Hospital Facility Maintenance Installation (IPSRS) at Petala Bumi Regional General Hospital, Pekanbaru, functions under the direct supervision of the Hospital Director and is responsible for maintaining hospital facilities, infrastructure, and medical equipment to ensure safety and service quality. This descriptive-analytic qualitative study (2023) aimed to analyze the medical equipment maintenance system at IPSRS, involving four informants from hospital management and technical staff. Data were obtained through interviews, observations, and document reviews, analyzed using content analysis with triangulation techniques. The findings show that IPSRS faces human resource shortages, with limited staff qualifications and multitasking duties affecting performance. The maintenance budget is available but requires better allocation. Materials and spare parts are mostly sufficient but partly depend on third-party suppliers. SOPs exist but are not fully implemented due to HR constraints and lack of evaluation. The organizational structure functions adequately but needs better HR placement. It is recommended that hospital management add skilled technical staff, update SOPs, and enhance staff competence through training and certification. Strengthening HR, budget management, and maintenance procedures will improve IPSRS efficiency and support high-quality, sustainable hospital services.

Assessment of the medical equipment supply chain in the Democratic Republic of Congo: a qualitative methods study.

Medical imaging has developed from an auxiliary means of clinical examination into a significant method and intuitive basis for clinical diagnosis of diseases, providing all-around and full-cycle health protection for the people. The Internet of Medical Things (IoMT) allows medical equipment, intelligent terminals, medical infrastructure, and other elements of medical production to be interconnected, eliminating information silos and data fragmentation. Medical images disseminated in IoMT contain a wide diversity of sensitive patient information, which means protecting the patient's personal information is vital. In this work, an Adversarial-improved reversible steganography network (Airs-Net) for computed tomography (CT) images in the IoMT is presented. Specifically, the Airs-Net adopting the prediction-embedding strategy mainly consists of an image restoration network, an embedded pixel location network, and a discriminator. The image restoration network is effective in restoring the pixel prediction error of the restoration set in integer and non-integer scaled images of arbitrary size when information is concealed. The embedded information location network can automatically select pixel locations for information embedding based on the interpolated image features of the degraded image. The restored image, embedding location map, and embedding information are fed into the embedder for information embedding, and the subsequent secret-carrying image is continuously optimized for the quality of the information-embedded image by the discriminator. Quantitative results show that Airs-Net outperforms state-of-the-art methods in both PSNR and SSIM. Further, the qualitative and quantitative results and analyses under specific clinical application scenarios and in coping with multiple types of medical image information hiding demonstrate the excellent generalization performance and practical application capability of the Airs-Net.

Microenvironmental niches dictate divergent fibroblast fates in reversible versus progressive lung fibrosis.

The study highlighted the key dimensions of social responsibility adopted by SONATRACH as one of the leading companies in the Algerian petroleum industry. It is characterized by economic and environmental responsibility through building a crisis and emergency management system, reducing greenhouse gas emissions, reducing gas flaring to less than 19%, and decreasing the number of fuel leaks by 21%. In terms of cooperative social responsibility towards the external environment, SONATRACH has contributed in various areas: in the health sector, by providing donations in the form of financial assistance and medical equipment to health institutions; in the sports sector by sponsoring sports clubs; and in the educational sector, by rehabilitating primary schools and installing solar panels. Additionally, SONATRACH has financed significant projects in remote areas and connected neighborhoods to electricity.

ABSTRACT The Internet of Things (IoT) and cloud computing (CC) concepts are commonly incorporated in healthcare applications. In the healthcare industry, a huge quantity of patient data is generated by IoT devices. The integral storage of mobile devices and processing power is used to analyze the stored data in the cloud. The Internet of Medical Things (IoMT) combines health monitoring mechanisms with medical equipment and sensors to monitor patient records and offer extra smart and experienced healthcare services. This paper proposes an effective and walrus-optimized deep learning (DL) technique for chronic kidney disease (CKD) prediction in IoT. To begin, the data are collected from the CKD dataset, and the preprocessing procedures, such as missing value imputation, numerical conversion, and normalization, are performed to improve the quality of the dataset. Then, dataset balancing is done using the k-means (KM) clustering algorithm to prevent the model from making inaccurate predictions. After that, enhanced residual network 50 (EResNet50) is utilized to extract more discriminative features from the dataset. From that, the optimal features are selected via elite opposition and the Cauchy distribution-based walrus optimization algorithm (ECWOA). Finally, the classification uses the walrus-optimized bidirectional long short-term memory (WOBLSTM). The simulation outcomes demonstrated the effectiveness of our method over existing techniques, with a higher sensitivity of 99.89% for CKD prediction.

Durable medical equipment (DME)-wheelchairs, non-invasive ventilation, gastrostomy tubes, and communication devices-provides vital support for individuals with amyotrophic lateral sclerosis (ALS). Here, we describe DME use in COURAGE-ALS evaluating reldesemtiv's efficacy and safety in ALS, to evaluate if DME use can be considered an endpoint of interest in ALS trials. COURAGE-ALS, a multicentre, double-blind, randomized, placebo-controlled clinical trial was conducted at 83 sites in the United States, Canada, Europe, and Australia. Participants were randomized 2:1 to receive reldesemtiv or placebo for 24 weeks, followed by 24 weeks of active drug treatment. Exploratory outcomes included reasons for prescribing, extent of use, DME types, and regional differences. Among 482 participants, 166 (34.4%) were using at least one DME item at baseline. Among 276 participants completing study visits through Week 24, 130 (47.1%) initiated use of a total of 188 new DME items post-baseline through 24 weeks. Manual wheelchairs were most used at baseline (89 items) and initiated (47 items) during the trial. Both baseline DME use and initiating a new item were associated with lower ALS Functional Rating Scale-Revised scores and worse quality of life. The trial was terminated early due to futility. Treatment assignment did not impact DME use. Regional disparities were noted. This study shows that DME is commonly prescribed to ALS trial participants. Further understanding of geographic differences in DME access and their impact on clinical outcomes is warranted prior to including DME use as an endpoint in ALS trials. ClinicalTrials.gov identifier: (NCT04944784).

Biofilms are surface-attached bacterial consortia, which account for 80% of the world's microbial biomass, and are responsible for 75% of human infections. These surface bacterial communities have enhanced their ability to withstand unfavourable conditions and resist antimicrobial treatments due to the presence of outer membrane proteins (OMPs). Outer membrane proteins (OMPs) play a central role in biofilm formation by mediating adhesion, matrix assembly, and intercellular interactions, and they are increasingly being targeted for novel antibacterial therapies to disrupt biofilm-related infections. OMPs play a crucial role in biofilm formation, as these proteins contribute to the assembly and architecture of the biofilm matrix, interact with other matrix proteins, and influence surface hydrophobicity and cell aggregation. Notably, genetic modifications or deletions of OMPs can increase or decrease biofilm formation, indicating their regulatory influence on matrix composition and biofilm morphology. Incidentally, biofilm poses significant challenges in industry and abiotic medical equipment. OMPs offer excellent targets to mitigate biofilm-forming infections, since blocking their function can reduce bacterial adhesion and disrupt biofilm integrity. Furthermore, antimicrobial peptides as well as nanotechnology-based therapeutics are under development to target OMPs, allowing for innovative approaches that circumvent traditional resistance mechanisms seen in biofilms. This review underscores the significance of key OMPs in devising strategies to combat biofilm-associated infections and offers a concise overview of their structure, function, and immunoprotective role. By targeting outer membrane proteins, emerging therapies seek to address the persistence and antibiotic resistance of biofilm-forming bacteria, representing a promising direction in the treatment of chronic and multidrug-resistant infections.

Introduction. A two-dimensional hydrodynamic problem is numerically solved in the “stream function-vorticity” formulation for an open rectangular cavity simulating blood flow and its coagulation within a vascular aneurysm. The model accounts for a simplified nonlinear mathematical description of the first phase of blood coagulation (30 seconds). Materials and Methods. To accelerate the numerical solution of the unsteady problem with an explicit finite-difference scheme for the vorticity dynamics equation, an n-fold splitting method of the explicit scheme (n = 100, 200) was employed, along with the use of a symmetry plane in the rectangular aneurysm domain. The splitting method was also applied to solve the dynamic system of advection-diffusion equations with nonlinear source terms for the activator and inhibitor blood factors (N = 70). The maximum time step τ0 was synchronized across both splitting cycles. The computation was performed on half of the rectangular aneurysm using a uniform 100×50 grid with equal spacing h 1 = h 2 = 0.01. The inverse matrix required for solving the Poisson equation in the “stream function-vorticity” formulation with a finite number of elementary operations was computed using the Msimsl library. Results. The numerical solution demonstrated that, in arterioles (Re = 3.6), advection and diffusion of fibrin occur according to the nonlinear dynamics of activator and inhibitor factors, as if fibrin were moving counter to the blood flow. The maximum fibrin density forms in the central region of the vessel in the shape of a “fibrin horseshoe”. For higher Reynolds numbers (Re = 3000) corresponding to arteries, fibrin motion occurs along the main flow, and the central part of the vessel is separated from the aneurysm by a “fibrin foot” along its geometric boundary. In arterioles, a layered fibrin growth effect was also observed, with periodic variations in fibrin density near the aneurysm wall, consistent with other authors’ findings. In arteries, the fibrin film within the aneurysm forms in approximately one second — significantly shorter than the first coagulation phase (30 seconds). Discussion. The finite-difference approximation achieves sixth-order accuracy at interior nodes and fourth-order accuracy at boundary nodes. The model was applied to simulate blood flow in arterial aneurysms at high Reynolds numbers (Re = 3000) and in arteriole aneurysms (Re = 3.6). The dimensionless range of fibrin density variation is consistent with data reported by other researchers. Conclusions. The study proposes a system of equations representing a simplified unsteady model of blood motion and fibrin (thrombus) formation in vascular aneurysms. The proposed model provides a qualitative understanding of thrombus formation mechanisms in aneurysms of arteries and arterioles, as well as in elements of medical equipment.

Introduction: Compliance with medical equipment calibration is essential to ensure service quality and patient safety. However, not all medical devices in community health centers (Puskesmas) in Palu City have been calibrated according to standards. Objective: This study aimed to analyze differences in calibration compliance between Paripurna-accredited and Utama-accredited Puskesmas. Methods: A comparative quasi-experimental study with a posttest-only design was conducted at Kamonji and Lere Health Centers from August to September 2025. Total sampling was applied to all employees, yielding 127 respondents. Data were analyzed using the Independent Sample t-test. Results and Discussion: Kamonji Health Center showed higher instrumental compliance, while Lere Health Center demonstrated slightly higher normative compliance. Statistical analysis indicated a significant difference in calibration compliance between the two health centers (t = 2.726; p = 0.007). Conclusion: Calibration compliance was significantly higher at the Paripurna-accredited health center, suggesting that higher accreditation status is associated with better calibration practices. Strengthening supervision and documentation is recommended, particularly for Utama-accredited health centers.

This retrospective cohort study evaluated the relationship between patient falls, Morse Fall Scale (MFS) items, patient demographics, length of stay and hospital site. Data were acquired from 72 hospitals in a health system. Logistic regression models were conducted including MFS items, demographics, length of stay, and interaction terms. The final mixed effects logistic regression model included significant patient-level covariates as fixed effects and hospital site as a random effect. 6531 of 978,920 total admissions included a patient fall. Four MFS items (fall history, secondary diagnosis, gait weak/impaired, mental status-overestimates/forgets limitations) and three demographic items (male gender, increased age, longer length of stay) were associated with increased likelihood of falling. Two MFS items (ambulatory aids, intravenous therapy/lock) and Hispanic ethnicity were associated with decreased risk of falling. An interaction effect was present between male gender and mental status. Males who overestimate/forget limitations had 3.16 times higher odds of falling than females oriented to their own ability. The proportion of variance in falls between hospitals was 0.23 and the median odds ratio (MOR) 1.57. This study uniquely assessed fall risk at the level of the patient and hospital, using data from nearly 1 million admissions at 72 hospitals. Controlling for patient characteristics, results demonstrate variability in fall risk among hospitals. Research informing hospital differences as well as gender and racial/ethnic differences in falls is needed to identify appropriate interventions. As hospitals increasingly adopt risk-directed fall prevention, assessment tools should be re-evaluated for clinical utility and corresponding prevention practices. The MFS may be enhanced by removing intravenous lock as a risk and screening for additional risks such as medications and medical equipment. Quality improvement efforts must also consider the hospital's environment and processes that may further contribute to fall risk. Authors adhered to STROBE guidelines for reporting. No Patient or Public Contribution.

Healthcare-associated infections (HCAIs) remain a significant global challenge, as pathogenic microorganisms can persist on hospital surfaces and medical equipment, contributing to severe infections and epidemic outbreaks. Conventional preventive measures, including disinfection procedures and personal protective equipment, are often insufficient to ensure complete microbial control, prompting interest in innovative antimicrobial surface technologies. This study reports the design, preparation, and comprehensive characterization of chitosan- and poly(ε-caprolactone)-based antibacterial coatings incorporating chlorhexidine-loaded zirconium phosphate (ZrPCHX) nanoparticles. Coatings were deposited by optimized spray and brush techniques to obtain uniform, adherent, and well-defined films. Their morphological, physicochemical, mechanical, and cytocompatibility properties were systematically evaluated, and antibacterial efficacy was assessed against clinically relevant pathogens following ISO 22196:2011 and additional protocols simulating realistic hospital conditions. Both coating systems demonstrated pronounced antibacterial activity, with the PCL-based formulation exhibiting a faster and broader bactericidal effect while maintaining good cytocompatibility. These findings support the potential of the developed nanostructured coatings as sustainable and scalable materials for the active decontamination of high-touch hospital surfaces, offering continuous antimicrobial protection and contributing to a reduction in HCAI incidence.

The monitoring, diagnosis, and treatment of patients has been completely transformed by the Internet of Things (IoT) in healthcare, especially in underprivileged and distant locations. IoT-enabled remote patient monitoring (RPM) makes it possible to gather and transmit health data like heart rate, glucose levels, and blood pressure in real-time, facilitating proactive and individualized care. IoT-enabled smart wearable devices like smartwatches, ECG patches, and fitness bands track physical activity and health parameters provide real-time data to clinicians via mobile apps or cloud servers and empower patients with self-monitoring tools. IoT-enabled RFID tags to locate critical medical equipment (e.g. ventilators, infusion pumps) enhances operational efficiency and reduces loss or theft and assists in hospital inventory and supply chain management. IoT devices facilitate real-time consultation with physicians using health data from patients and bridges the healthcare gap in rural and underserved areas. With a focus on RPM systems, Smart Wearables and RFID tags this chapter examines the architecture, technology, uses, and advantages of IoT in healthcare. The difficulties with interoperability, system integration, security, and data privacy are also covered. IoT has the revolutionary potential to improve healthcare outcomes, lower readmission rates to hospitals, and improve the quality of life for patients with chronic illnesses, as demonstrated by case studies and recent advances.

Patient service has an influence on sales turnover of drugs and medical devices because of the emergence of a good sense of service will feel happy and comfortable using the services of a pharmacy or hospital so that the quality provided and the sense of service provided by the patient will affect sales turnover, especially in the installation section. pharmacy. -The purpose of writing this final report is to find out whether there is an effect of patient care on sales turnover of drugs and medical devices in the pharmacy installation section of the TK III Hospital 04.06.03 Dr. Soetarto The writing method uses a sample of 45. By using the IMB SPSS Statistics 22 tool. The results of this paper indicate that there is a significant effect between patient care on sales turnover of drugs and medical devices carried out in the t test. From the results of table 4.9 above, t count is 4.889 and t table is 1.6810, so 4.889 > 1.6810. or t count is greater than t table so that it is concluded that ho is rejected and ha is accepted. The magnitude of the effect of patient care on sales of drugs and medical equipment is 35.7%. From the results of data processing the value of R Square (coefficient of determination) is 0.357 or 35.7%. While the remaining 64.3% is influenced by other variables.

ObjectivesThis study aims to evaluate the actual energy consumption of two generations of 1.5-T magnetic resonance imaging (MRI) scanners, quantify the benefits in terms of primary energy savings resulting from technological replacement, and compare field estimates of primary energy consumption with those reported in environmental product declarations (EPDs).Materials and methodsTwo 1.5-T MRI scanner models, the old model version and its new model replacement, were monitored using a power quality analyzer connected to the electrical cabinet. Electrical power consumption data were collected over 2-week periods, both before and after the scanner replacement. Primary energy consumption was projected over 10 years, and the resulting values were compared with those reported in the EPDs for the two scanners.ResultsOver 10 years, cumulative energy consumption is estimated to be 1,010.4 MWh for the new unit versus 1,206.7 MWh for the old unit, corresponding to a 16.3% reduction. Considering the range of European primary energy factors (PEFs), energy savings varied from 235.6 to 687.1 MWh. Comparison with EPDs revealed significant discrepancies (± 40%) depending on the national PEF used, demonstrating that EPDs can both overestimate and underestimate actual energy consumption.ConclusionReplacement of an old MRI model resulted in measurable energy savings, particularly in non-productive phases. However, EPDs do not always reflect clinical operation or the impact of national energy mixes. While energy efficiency is central to sustainable radiology, it should not be the sole driver for equipment replacement, which must remain primarily guided by clinical and diagnostic criteria.Relevance statementFor a radiology department focused on more sustainable practices, it is essential to have accurate data on the environmental performance of medical imaging equipment, which should not be based solely on EPDs, but on real data based on usage patterns and national energy mixes.Key PointsReplacing the old MRI scanner reduced energy consumption by 16.3%, mainly due to lower use in non-productive modes.Over a 10-year operational period, the primary energy consumption savings varied from 235.6 to 687.1 MWh.A discrepancy emerged between EPD-reported and real-world measurements, highlighting the importance of on-site validation for sustainability assessments.Graphical

Optimising medical equipment utilisation and serviceability: A data-driven approach through insights from five healthcare institutions.

Non-contact identification of opportunistic pathogens in mixed biofilm contaminations by hyperspectral imaging.

The goal of creating cutting-edge medical devices is deeply based on technological advances and innovative design principles. People increasingly want to improve their quality of life, ensure their safety, health, and take full advantage of technological developments. Diagnostic and restorative directions of medicine are among those fields that are constantly evolving. Patients with various health issues, including both physical and mental challenges, are at the center of these developments, requiring ongoing care to manage their conditions effectively. This study focuses on integrating advanced technologies, particularly Artificial Intelligence (AI), into the medical field to enhance diagnostic device functionality, accuracy, and connectivity. The primary objective is to develop medical equipment that simplifies the diagnostic process, improves efficiency, and enhances the accuracy of clinical assessments. The methodology is based on the systematic design and optimization of diagnostic tools incorporating AI-driven data analysis, which enables more accurate and personalized patient assessments. As a result of the study, four therapeutic medical devices integrating infrared radiation and Artificial Intelligence (AI) have been designed. These devices are developed to enhance patient care and improve overall quality of life by providing advanced noninvasive diagnostic and therapeutic solutions. Experimental evaluations confirm that all four devices operate exclusively through non-invasive methods, thereby minimizing patient discomfort, pain, and the risk of infection or post-procedural complications. The application of infrared radiation technology demonstrates high precision and reliability in medical diagnostics, while AI-driven analysis contributes to enhanced efficiency and the personalization of therapeutic interventions.

International sanctions against countries, by restricting access to medicines and medical equipment, violate public health and fundamental human rights. Using a descriptive–analytical method and relying on international legal instruments (such as the International Covenant on Economic, Social and Cultural Rights) and Islamic sources (the Qur'an, hadiths, and jurisprudence), this study examines the comparative impact of pharmaceutical sanctions on health systems and their conflict with legal and ethical principles. The findings indicate that sanctions not only contradict the right to health under international law but also oppose Islamic norms such as preserving human dignity and the obligation of treatment in emergencies. Empirical cases in Iran, Iraq, and Syria confirm the increase in mortality among patients with specific conditions, shortages of essential medicines, and price inflation. This study, by offering solutions such as humanitarian exemptions and strengthening regional cooperation, emphasizes the necessity of revising sanction mechanisms to reduce human harm.

Fragility curves for unanchored medical equipment accounting for building and content interaction