The incidence of kinesiophobia in patients with chronic neck pain is increasing annually, severely impacting their recovery, psychological well-being, and quality of life, and even leading to functional impairment. Traditional rehabilitation training methods are plagued by low patient compliance, tedious treatment processes, and a lack of personalization. Virtual reality technology, as an emerging digital rehabilitation tool, is gaining increasing attention for the management of kinesiophobia in patients with chronic neck pain. This article systematically reviews the core devices and intervention design for this technology in the management of kinesiophobia in patients with chronic neck pain. The article analyzes its effectiveness in reducing fear of movement, alleviating pain symptoms, and improving cervical range of motion and function. It also explores its value in personalized training and improving treatment compliance, as well as its limitations, such as uncertain long-term efficacy and high equipment costs. By integrating existing research evidence, this article aims to support the development of standardized virtual reality rehabilitation programs and the implementation of this technology in Chinese clinical practice. This approach, in turn, aims to help break the cycle of functional deterioration, improve quality of life, reduce the consumption of medical resources, and promote the standardized application of digital rehabilitation technology in chronic disease management, aligning with the needs of chronic disease prevention and treatment and the development of digital healthcare under the Healthy China strategy.

Objective Based on real-world data, this article examines the changes in surgical patient costs and usage of blood flow-oriented dense mesh stents in the treatment of intracranial aneurysms under different surface technology designs, and discusses the economic impact of this consumable in clinical use. Methods This article establishes a list of consumables for blood flow guided dense mesh stents in our hospital, which can be divided into two groups based on whether the stent uses surface treatment technology (yes, no); The bracket can be divided into three groups based on the surface treatment techniques used (no surface treatment, coating treatment, surface modification treatment). By calculating parameters such as the average quantity (amount) of consumables per case, the average number of dense mesh supports per case, the proportion of dense mesh support per case, and the proportion of dense mesh support per case, the rank sum test was used to statistically analyze the consumables usage data of our hospital from January 2020 to March 2025. Results From 2020 to 2024, the total amount of consumables used per case in our hospital has been decreasing year by year, and the difference is statistically significant (H=260.87, P<0.001); The total amount of consumables per case decreased, and the difference was statistically significant (H=412.30, P<0.001); The unit price of scaffolds with different surface treatment techniques is statistically significant (P<0.001). The number of scaffolds used with surface polishing treatment significantly increases, while the unit price significantly decreases; There is no significant difference in the total amount of consumables used under different surface treatment techniques, but the total amount of consumables used for coating technology supports significantly increases (H=65.11，P＜0.001). Conclusion The use of dense mesh stents with different surface treatment techniques for the treatment of intracranial aneurysms results in significant differences in the total quantity, total amount, and stent unit price of consumables used by patients. Studying their impact on treatment costs can provide a data basis for standardizing and refining consumables management, as well as hospital cost control.

Objective To address the pain points in equipment maintenance management at medical colleges and universities, a digital platform should be built to standardize, refine, and inform maintenance management. This will enhance the efficiency and quality of management, support teaching and scientific research, and provide a reference for the digital transformation of medical equipment management. Methods With the campus network as the core support, this solution deeply integrates AI technology and the full-lifecycle management concept to build a full-process intelligent digital system. In terms of technical architecture, the B/S (Browser/Server) mode is adopted, with Java as the development language and SpringMVC as the core framework. Relying on the Qwen3 model, a local maintenance knowledge base is built, and a five-layer system consisting of the "Data Layer - Acquisition Layer - Edge Layer - Platform Layer - Presentation Layer" is simultaneously onstructed.Results After the adoption of the digital system, maintenance efficiency and warehouse management effectiveness have been significantly improved:On the maintenance side: The time required for fault confirmation and solution formulation (1.29±0.22 days), waiting for spare parts (0.63±0.18 days), and completion of maintenance (4.24±0.33 days) is all shorter than that of the traditional method (2.04±0.46 days, 1.56±0.40 days, 4.80±0.37 days), with statistically significant differences (t=3.871、5.659、2.971，p<0.05).On the warehouse side: The time for procurement response (0.81±0.15 hours) and processing (0.21±0.09 minutes) is shorter than that of the traditional method (1.02±0.26 hours, 0.45±0.18 minutes), with statistically significant differences (t=11.615、11.051，P＜0.05).This system effectively optimizes the allocation of equipment maintenance resources and improves maintenance efficiency. Conclusion The digital platform enables full-process standardization and informatization. It significantly improves maintenance efficiency and inventory management standards, and innovatively incorporates large AI models and a maintenance knowledge base. This provides a replicable model for the digital transformation of medical equipment management, with both practical and theoretical value.

Objective Using CiteSpace, visualize and analyze the current research status, hotspots, and trends in digital health technologies for patients with chronic obstructive pulmonary disease (COPD). Methods Relevant literature on the use of digital health technology for COPD patients from the database's inception to June 2025 was searched in the core databases of China Knowledge and Web of Science. CiteSpace 6.3.R1 was used to view and analyze the authors, publishing institutions, and keywords in the retrieved Chinese and English literature. Results There were 412 Chinese-language publications and 282 English-language publications included, demonstrating that the volume of publications in this sector has been steadily increasing. Domestically, Tianjin Medical University's School of Nursing (4 publications) was the most prolific, with Wang Lan, Ma Lijun, and Zhao Yue ranking as the top three authors. Internationally, the U.S. Department of Veterans Affairs (12 publications) was the most prolific institution, with Fame, Tarassenko, and Chavannes ranking as top three writers. Domestic keywords were organized into nine clusters, whereas overseas keywords created ten clusters. Pulmonary rehabilitation, self-management, telemedicine, quality of life, and artificial intelligence have emerged as popular study topics in both domestic and international digital health technology for COPD.Conclusion The field of COPD digital health technology is still developing at home and abroad, and tele-rehabilitation and machine learning based on digital health technology will be the focus of future research in this field. We need to strengthen international communication and collaboration in order to bring more accurate and effective treatment and management programs for COPD patients.

To address the inefficiency and insufficient real-time performance of multi-source heterogeneous data fusion in hybrid operating rooms, this study proposes an adaptive data fusion method based on a multimodal neural network (MMNN). The CNN was utilized to extract image features, the LSTM network to process time-series data, and the embedding layer to encode discrete events. An attention mechanism was integrated to optimize feature fusion weights, and a dynamic learning rate adjustment strategy was adopted to enhance model training. Experimental results demonstrated that the proposed method achieved a fusion accuracy of 92.1% on the hybrid operating room dataset, significantly outperforming traditional methods (weighted sum: 85.3%; feature concatenation: 88.7%) (P<0.01). Precision, recall, and F1-score improved to 90.4%, 88.5%, and 89.3%, respectively (P<0.05), with a ROC-AUC of 0.93. Clinical validation revealed that the average operation time was reduced from 32.4±5.1 minutes to 25.1±3.8 minutes (P=0.003), and the decision response latency decreased from 1.8±0.4 seconds to 0.3±0.1 seconds (P<0.001). By dynamically fusing multimodal data, this method significantly enhances surgical efficiency and real-time decision-making, providing a reliable technical foundation for the intelligent development of hybrid operating rooms.

Objective To investigate the construction and implementation efficacy of a homogeneous management system for medical equipment in multi-campus public hospitals, aiming to enhance resource allocation efficiency and ensure consistent clinical service quality. Methods Grounded in the multi-campus practices of Sichuan Cancer Hospital, this study identified management challenges through literature analysis, field research, and brainstorming methods. A standardized framework spanning five dimensions—equipment configuration, operational protocols, maintenance consistency, personnel training, and quality control—was established under the principle of "holistic standardization and homogenization." Results The homogeneous multi-hospital management system covers five dimensions: configuration, usage, maintenance, personnel, and quality control. It includes overall planning for configuration, intensive procurement methods, compilation of the operation manual for medical equipment in multi campuses hospitals, smoothing cross-hospital equipment allocation, and strengthening internal quality control management. After practical operation, the utilization rate of equipment resources has been significantly improved. For example, the average utilization rate of life-support equipment in the allocation center increased by 22%, the maintenance rate of a certain brand of large-scale equipment decreased by 8.9%, and the procurement budget for ventilators was reduced by 40%. Meanwhile, the operation and maintenance quality was enhanced, with the average maintenance duration of medical equipment across the hospital shortened by 33%. The clinical response has been favorable, and the department satisfaction rate rose from 84.5% to 95.5%. Conclusion The homogeneous management system, integrating standardized protocols and digital solutions, effectively addresses resource fragmentation and operational inefficiencies in multi-campus settings. This model offers a replicable strategy for optimizing medical equipment management in public hospitals, demonstrating substantial clinical and operational value for large-scale healthcare systems.

Objective To explore the effect of the reflective mode of the problem menu in the refined management of medical consumables in our hospital based on the difference-in-differences (DID) model. Methods The period from June 2023 to December 2023, during which the refined management of medical consumables was carried out without using the reflective mode of the problem menu, was set as the control group. The period from January 2024 to June 2024, when the refined management of medical consumables was implemented with the application of the reflective mode of the problem menu, was designated as the observation group. The difference-in-differences (DID) model was used to analyze indicators including the rational utilization rate of medical consumables, the proportion of high-value medical consumables, the proportion of medical consumables per 100 yuan of medical income, the time spent on weekly inventory checking, application, collection, and billing, as well as the rates of missing barcodes, mislabeled barcodes, and billing errors. Results The rational utilization rate of medical consumables in the observation group was higher than that in the control group (P<0.05), while the proportion of high-value medical consumables and the proportion of medical consumables per 100 yuan in the observation group were lower than those in the control group (P<0.05). Compared with the control group, the weekly inventory checking time, consumable application time, collection time, and billing time in the observation group were shortened by 13.96±3.44 minutes, 13.26±2.34 minutes, 17.00±3.82 minutes, and 29.36±8.52 minutes, respectively. The missing labeling rate, wrong labeling rate, and billing error rate of medical consumable barcodes in the observation group were 8.30%, 7.10%, and 5.00% lower than those in the control group, respectively. The Difference-in-Differences (DID) regression model showed that after the implementation of the reflective model of the problem menu, the significant effects on the rational utilization rate of medical consumables, the proportion of high-value medical consumables, and the proportion of medical consumables per 100 yuan were 6.531, -4.163, and -9.106, respectively (P<0.05). Conclusion The reflective model based on the question menu increased the rational utilization rate of medical consumables and the work efficiency of staff, while reducing the proportion of high-value medical consumables, the proportion of medical consumables per 100 yuan (of medical service revenue), as well as the rates of missing barcodes, incorrect barcodes, and billing errors for medical consumables. Consequently, it improved the quality of refined management of medical consumables.

Objective Aiming at long-standing practical issues in the medical device field, such as the disconnection between clinical needs and industrial R&D, and insufficient efficiency in technology translation, this study intends to construct a collaborative innovation model and implementation path covering the full life cycle of "Clinical Needs Identification – R&D Verification – Clinical Translation – Market Application", and explore optimization methods for building an innovation ecosystem in this field. Methods By establishing a structured cooperation mechanism, a targeted needs demonstration system, a standardized R&D process, and a full-chain risk prevention and control framework, the implementation path of collaborative innovation between medical institutions and enterprises was systematically advanced. Typical collaborative projects between medical institutions and enterprises were selected as research objects, and a comparative analysis method was adopted to conduct quantitative evaluation on indicators such as technology translation cycle and cooperation satisfaction before and after the model implementation. Results After the application of this collaborative innovation model, the matching degree between clinical needs and industrial R&D has significantly improved, obstacles in the technology translation process have been reduced, and cooperation satisfaction has increased from 74% (before implementation) to 92%, forming an innovative ecosystem with positive interaction. Conclusion This collaborative innovation model between medical institutions and enterprises has effectively promoted the formation of a value-oriented innovative ecosystem supported by industry chain collaboration. It can effectively improve the translation efficiency and innovation quality in the medical device field, and provide a referenceable implementation path and social demonstration value for collaborative innovation practices in related fields.

Objective To analyze recall reports for active medical devices issued in China from 2017 to 2024, examine the current status and characteristics of recalls for such devices, and provide guidance for recall management in China. Methods A retrospective statistical analysis was conducted to comprehensively review recall reports for active medical devices published by the National Medical Products Administration Website from 2017 to 2024. The study focused on key information in the recall reports, including product categories, management levels, recall levels, and recall reasons, and performed a descriptive analysis. Results A total of 1,050 recall reports for active medical devices in China were identified from 2017 to 2024. Among these, 69 were Class I recalls, 347 were Class II recalls, and 634 were Class III recalls. 50.48% of recalled products were Class II medical devices. 70.10% of recalled products were imported medical devices; recalls involved 18 product categories, with medical imaging devices (24.38%), clinical examination devices (17.81%), respiratory/anesthesia and emergency devices (12.86%), and medical diagnostic and monitoring devices (11.62%) accounting for the highest proportions; Analysis of recall causes revealed that hazards related to performance accounted for 31.05% of medical device recalls, while energy hazards accounted for 16.86%. In the analysis of hazard sources and recall levels, operational hazards led to the highest number of Class I recalls (33.33%) and Class II recalls (46.97%); other hazards caused the most Class III recalls, accounting for 66.56%. Conclusion This paper comprehensively outlines the characteristics of active medical device recalls in China, aiding manufacturers in strengthening targeted quality control and regulatory authorities in optimizing oversight strategies.

Objective To establish an intraocular lens (IOL) adverse event risk analysis model based on Dempster-Shafer (D-S) theory of evidence, so as to solve the uncertainty and conflict problems under multi-source heterogeneous data. Methods Risk information from multiple sources was integrated, including the National Medical Device Adverse Event Monitoring System (124 items), MAUDE database (4942 items), Meta-analysis of clinical literature (8 studies, 1543 patients), and Delphi method expert opinions (6 experts). The identification framework Θ = {L1, L2, L3, L4, L5} represents the risk level. The basic probability assignment (BPA) function was assigned to each information source, and the confidence degree (C) was introduced to correct its reliability. Finally, the multi-source evidence was fused by Dempster's rule of combination, and the comprehensive risk level and uncertainty measure (U) were output. Results The fusion results showed that the risk level of aspheric IOL dislocation was L4 (very likely), BPA= 0.572, followed by L3 (possible), BPA=0.405, and the overall uncertainty was very low (U=0.008). It is suggested that there is a definite risk of dislocation of this type of IOL, which should be paid more attention to. Conclusion The risk analysis model based on D-S evidence theory can effectively integrate multi-source heterogeneous data, deal with information conflict and uncertainty, and output risk level assessment results with high credibility. This study uses this method to confirm that the risk of aspherical IOL dislocation is ' very likely ' ( L4 level ), which needs to be highly valued by clinical and regulatory authorities. This method is suitable for the post-marketing risk monitoring of Iols and other high-risk medical devices. It has strong methodological significance and practical application value, and can provide scientific decision support for regulatory authorities, medical institutions and manufacturers.

Objective To compare the dosimetric differences among four treatment modalities, including fixed-jaw versus jaw-tracking techniques combined with flattening filter (FF) or flattening filter-free (FFF) beams, in intensity-modulated radiotherapy (IMRT) for nasal NK/T-cell lymphoma. Methods A total of 30 patients with nasal NK/T-cell lymphoma treated in Jiangsu Cancer Hospital between 2018 and 2025 (age range: 33~75 years old; median age: 52 years old) were retrospectively analyzed. Treatment plans were generated using the Varian planning system, including four modalities: SJ-FF, SJ-FFF, JT-FF, and JT-FFF. All plans were optimized under identical conditions and weighting to ensure comparability. Dosimetric parameters of the planning target volume (PTV) (D2%, D50%, D98%, Dmean, HI, CI) and organs at risk (OARs) (brainstem, parotid glands, eyeballs, and lenses) were compared. Results No statistically significant differences were observed in PTV dosimetric parameters (D2%, D50%, D98%, Dmean, HI, CI) among the four treatment modalities (P> 0.05). For OARs, the jaw-tracking technique significantly reduced the mean doses to the brainstem, parotid glands, eyeballs, and lenses (P < 0.05), as well as the maximum doses to the brainstem, eyeballs, and lenses (P < 0.05). Similarly, the FFF mode reduced the mean doses to the brainstem, parotid glands, and lenses (P < 0.05). The combination of jaw-tracking and FFF beams provided the most pronounced protective effect on the lenses.Conclusion Both the jaw-tracking technique and FFF beams can maintain PTV dose homogeneity and conformity while significantly reducing radiation exposure to surrounding OARs. Their combination offers additional protective benefits, particularly for the lenses. These findings suggest that jaw-tracking combined with FFF beams may represent an optimal radiotherapy option for patients with nasal NK/T-cell lymphoma, with potential clinical application value.

Based on the practical experience of medical device standard review, common issues in standard drafting were systematically sorted out. By analyzing specific cases, in-depth study were conducted on the factors those may affect the quality of standards. Considering current industry development and the capabilities of standard drafters, targeted recommendations are proposed to improve the quality of medical device standards, these methods include optimizing the technical organization mechanism for medical device standardization, strengthening the capacity building of drafting personnel, enhancing pre-review control of medical device standards, and empowering standard drafting with technical tools. To further improve the quality of China's medical device standards and provide guidance for the high-quality development of the industry.

Objective This study aimed to evaluate the feasibility of using the Normal Tissue Objective (NTO) as an alternative to the conventional dose restriction Ring structure in optimizing intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans for Graves' ophthalmopathy, thereby providing insights for selecting efficient optimization strategies in clinical practice.Methods A total of 35 patients with Graves' ophthalmopathy were enrolled. Using the Eclipse treatment planning system, four distinct plan types were designed for each patient: IMRT(Ring), VMAT(Ring), IMRT(NTO), and VMAT(NTO). Dosimetric parameters for the target volume and organs at risk (OARs) were compared between the Ring and NTO groups within each radiotherapy technique (IMRT or VMAT). The response characteristics of the two techniques were also analyzed.Results For IMRT, plans optimized with the Ring demonstrated a significantly superior target conformity index (CI) (0.82 ± 0.02) compared to the NTO plans (0.72 ± 0.05) (P< 0.01). The Ring plans also showed higher homogeneity index (HI), Dmax, and Dmean values. Notably, the mean brain dose was significantly reduced from 253.70 ± 32.18 cGy in the NTO group to 231.07 ± 27.95 cGy in the Ring group (P < 0.01), although this improvement was accompanied by a significant increase in monitor units (MUs). In VMAT, the Ring group achieved a slightly better CI (0.80 ± 0.02) than the NTO group (0.77 ± 0.04) (P < 0.01). The mean brain dose also decreased significantly from 211.09 ± 29.42 cGy (NTO) to 206.80 ± 25.67 cGy (Ring) (P < 0.01), and the mean lens dose was notably lower in the Ring group. Overall, the use of the Ring resulted in a more pronounced improvement in dose distribution for both techniques.Conclusion The Ring was more effective than the NTO in enhancing target conformity and reducing the radiation dose to normal brain tissue, applicable to both IMRT and VMAT techniques. While the NTO cannot fully substitute for the Ring, further investigation is warranted to determine whether a combination of both could lead to additional improvements in treatment plan quality.

Magnetic resonance imaging (MRI) is an essential tool for diagnosing neck diseases, but its relatively long scanning time is prone to motion artifacts, which can affect diagnostic accuracy and patient comfort. Accelerating MRI scanning techniques is key to addressing this issue. Currently, clinically common accelerated MRI scanning techniques include simultaneous multi-slice, compressed sensing and deep learning. However, there is still a lack of systematic review regarding their principles, advantages and disadvantages, and progress in neck MRI. This paper aims to provide a literature review that systematically elaborates on the imaging principles of three accelerated scanning techniques and analyzes their progress in clinical research on neck MRI.

Objective To address issues such as irrational configuration, low utilization efficiency, and insufficient economic benefits of hospital ultrasound diagnostic equipment after medical insurance reform, and to construct a full-lifecycle multi-dimensional evaluation system based on real-world evidence, so as to improve the refined management level of equipment.Methods Taking the 2023 data of 13 outpatient ultrasound equipment of the same grade (covering 4 production regions) in a hospital as samples, based on Health Technology Assessment (HTA) and combined with the Delphi method, 4 first-level indicators (technical characteristics, clinical application, economic management, and usage behavior) and 16 second-level indicators were established for data analysis.Results There were significant differences in the performance of equipment from different regions. Austrian equipment had a fast technological iteration rate (time difference from registration certificate to purchase: 18.0±6.2 months), Japanese equipment bore a high load of routine examinations (utilization rate ratio: 1.29±0.01), and American equipment had prominent advantages in high-end examinations (proportion of difficult and complicated cases examinations: 14.6±3.2%). The economic benefits of equipment were significantly differentiated: the annual revenue of high-efficiency equipment exceeded the average by 134.85%, while that of low-efficiency equipment was only 43.44%; differences in accessory universality led to a 30% cost fluctuation. The positive rate of routine examinations of domestic equipment was 0.75, showing no statistical difference from imported equipment (P=0.73).Conclusion This multi-dimensional evaluation system can provide a basis for the scientific configuration of hospital ultrasound diagnostic equipment, help optimize the utilization efficiency of medical resources, promote the technological improvement of domestic equipment, and has important practical significance for hospitals to control costs and improve diagnosis and treatment quality.

Medical robots are increasingly widely used in medical fields and gradually becoming common diagnostic and therapeutic equipment in current and future medical fields. In recent years, the integration of artificial intelligence (AI) and medical robots has made a breakthrough. Notably, deep learning (DL)-based AI has significantly improved the performance of equipment in multiple aspects: optimizing intraoperative visual clarity, enabling real-time support force feedback, facilitating intraoperative real-time data analysis, as well as advancing medical imaging, auxiliary disease diagnosis and treatment, and therapeutic decision-making support. These advancements afford clinicians more intuitive and precise support in diagnosis and treatment. Currently, DL-based AI technology has become an essential feature for future medical robots. Therefore, this paper reviews the application process, future development directions, and the existing difficulties and challenges of the integration of DL-based AI and medical robots，aiming to provide theoretical support and practical guidance for the future development and regulation of medical robots deeply integrated with AI technology.

Objective To address the limitations of existing human skeleton-based action recognition models, which often suffer from complex network designs and insufficient utilization of spatiotemporal motion information, this study proposes an efficient model for skeleton spatiotemporal feature representation. Methods A Spatio-Temporal Attention Graph Convolutional Network (STA-GCN) is constructed. The model introduces a spatial attention module to emphasize key joints and their motion trajectories, and a temporal attention module to enhance the modeling of critical frames and velocity-related information. The two attention mechanisms are jointly integrated into the graph convolutional framework to form the STA-GCN. Furthermore, a series of ablation experiments are conducted to validate the effectiveness of each module. Results Experiments on the UTD-MHAD and Florence 3D Actions datasets achieve accuracies of 99.42% and 85.51%, respectively. Ablation results demonstrate that STA-GCN significantly improves recognition performance on both datasets, yielding 35.26% and 15.49% accuracy improvements over the baseline ST-GCN. Conclusion The experimental results indicate that the proposed STA-GCN effectively captures the spatiotemporal motion characteristics of skeleton data and substantially enhances action recognition performance, making it a highly effective method for human skeleton-based behavior recognition tasks.

Objective This paper aims to address the thermal failure issue of tungsten alloy X-ray targets in the X-ray generation process of medical linear accelerators. The study employs methods such as thermal load modeling, finite element simulation, and structural comparison analysis to examine the temperature and thermal stress fields of the X-ray target under typical VMAT and sIMRT conditions. Methods A transient thermal load model is established based on pulse parameters. Finite element simulations are performed for both steady-state and transient thermo-mechanical coupling on the target surface. The evaluation indicators—peak temperature, maximum principal stress, and fatigue damage—are used to compare the heat dissipation performance of the end-face, radial, and composite cooling structures. Results Under the VMAT condition, the target temperature continuously increases, but after optimizing the structure, the peak temperature is reduced by more than 15%. For the sIMRT condition, the maximum stress amplitude caused by thermal cycling is reduced by approximately 18%. Among the three structures, the composite cooling design demonstrates the best performance. Conclusion Optimizing the cooling structure can significantly reduce the thermal load on the X-ray target, enhancing its stability and lifespan, and provides a foundation for the design of high-dose-rate accelerating tubes.

This article presents a detailed analysis of three typical cases in the GE Innova 4100-IQ angiography system, including intermittent shutdown of the water chiller, failure of gantry and table movement, and unavailability of X-ray. Through systematic diagnosis and repair practices, the paper summarizes the troubleshooting principle of “from easy to difficult, from simple to complex,”and emphasizes the importance of integrated hardware and software diagnosis.Furthermore, it constructs a methodological maintenance framework derived from case-based practice, and discusses future directions for medical equipment maintenance by integrating current industry trends such as remote diagnosis and predictive maintenance.The study provides practical methodological references for the maintenance of high-end medical equipment.

As a non-invasive ventilator, the V60 was widely adopted early on in the treatment of respiratory diseases. With its simple operation, intuitive interface, and stable performance, it has received consistent clinical acclaim. This paper provides detailed observations of common fault cases encountered during the daily use and maintenance of this model, along with corresponding maintenance standards, operational principle analyses of faulty components, and research testing of multiple new repair solutions for critical malfunctions. The goal is to promote the application of safe and reliable new conclusions, restoring the device to normal operation. Ultimately, this approach has significantly reduced maintenance costs in clinical settings while also enhancing the troubleshooting skills of medical engineers, holding substantial practical significance across multiple dimensions.

Objective To investigate the development trends and research hotspots in the field of postoperative high-flow nasal cannula (HFNC) therapy by employing bibliometric methods, so as to provide a reference for future research in this field. Methods Using the Web of Science Core Collection database as the data source, CiteSpace and VOSviewer software were employed to perform visual analysis on the annual publications, authors, countries, institutions, journals, co-cited references, and keywords of literature related to postoperative HFNC published between 2012 and 2024. Results A total of 153 articles were included in the analysis. The annual publication volume in this field showed a year-by-year increasing trend, with rapid growth in the past 6 years, accounting for 83.01% of the total publications. The scholar with the highest number of publications was Cheng, Ya-jung from China. The country with the highest number of publications was China, followed by the United States. The institution with the highest number of publications was Assistance Publique–Hôpitaux de Paris (AP-HP) in France. The most frequently cited journal was the British Journal of Anaesthesia. Keyword analysis revealed that the use of HFNC for preventing acute respiratory distress syndrome (ARDS) after cardiac surgery is a current research hotspot. Conclusion By conducting a systematic analysis of the postoperative HFNC literature (2012-2024), this study delineates the field's current state and trends. The findings offer an evidence-based reference to steer future research, clinical protocols, and international partnerships, facilitating the standardization and progression of postoperative HFNC therapy.

Objective In order to carry out safe and scientific exercise, the article develops an Android-based target heart rate visualization and monitoring system for real-time monitoring, recording and analyzing heart rate data, and presenting it to the user in an intuitive and easy-to-read way. Methods In this study, blender modeling is used to render the flower pictures, the heart rate acquisition device adopts XOSS heart rate belt to collect real-time heart rate data from the user, and BLE Bluetooth transmission technology is used to transmit the heart rate data detected by the heart rate belt, the analysis and display module is written by Android studio to display flowers on the cell phone side according to the preset range of the target heart rate for the heart rate, and the color displayed by the flowers is recognized to maintain the target heart rate in real time. By recognizing the color displayed by the flower, real-time adjustment of the exercise strategy so as to maintain the target heart rate in real time. Results Experimental results show that the heart rate measurement error of this system is ≤ ±3 beats per minute; the K-S test for normality of heart rate measurement differences shows P = 0.42 > 0.05, indicating a normal distribution; the paired t-test shows P = 0.21 > 0.05, confirming that the system's measurements have no significant systematic bias compared to the control device. The system’s mean coefficient of variation for heart rate data across different scenarios is 1.13%, the Bluetooth packet loss rate is 0.7%, and the connection retention rate reaches 98.0%, verifying the system's connection stability and data transmission reliability. The study confirms that the flower color-based visual heart rate feedback mechanism can intuitively represent real-time fluctuations in the user's heart rate during exercise. Conclusion The experimental results show that this study successfully realizes a visual heart rate feedback mechanism based on flower color changes, which can intuitively reflect the real-time heart rate interval changes of users during exercise. Conclusion This study provides scientific and effective exercise guidance by accurately collecting and analyzing the daily exercise data of the testers, aiming to optimize the exercise program and enhance the exercise effect.

Respiratory failure is a clinical syndrome characterized by impaired pulmonary ventilation or gas exchange caused by various underlying conditions, leading to disrupted gas exchange and physiological imbalance. While conventional treatments can offer some improvement, mechanical ventilation plays a pivotal role in restoring ventilation and gas exchange functions. Invasive mechanical ventilation is highly effective but associated with significant tissue injury and a higher risk of complications. Noninvasive mechanical ventilation, on the other hand, causes less harm but offers relatively lower ventilation efficiency. In recent years, the sequential invasive–noninvasive mechanical ventilation strategy has been shown to effectively stabilize patient conditions, alleviate discomfort, reduce the risk of complications, and improve clinical outcomes. This review summarizes the clinical implementation of this strategy and the optimal timing for transitioning between modes, aiming to provide insights for the treatment of respiratory failure.

Objective Based the backdrop of current advancements in medical imaging and endoscopic intervention technologies within healthcare institutions, this study analyzes and investigates the multidimensional safety risks associated with the clinical application of covered stents for palliative treatment of intestinal obstruction caused by malignant diseases. It aims to provide healthcare institutions, registrants, and regulatory authorities with scientific evidence for risk identification, assessment, and prevention.. Methods Based on four reported cases of serious adverse events involving intestinal covered stents from a tertiary hospital in Zhejiang Province, combined with information from the National Medical Products Administration (NMPA) and the U.S. FDA MAUDE database, this study systematically reviews the product structure evolution, domestic and international regulatory history, and current status of intestinal covered stents. Risk analysis was conducted across multiple dimensions—including product design, material processes, clinical use, and patient factors—to systematically identify and evaluate key risk points. Results Intestinal coated stents are mainly subject to the risk of stent fracture and migration due to registrant product design and workmanship, the risk of poor operator decision-making and handling due to clinical use in healthcare organizations, the risk due to progression of malignant disease and changes in the dietary conditions of the patient, as well as the serious outcomes of Aortoenteric Fistula, gastrointestinal perforation, and stent migratory failure caused by the above three types of risks.Conclusion Based on the main risks identified in this type of product, targeted risk control recommendations are proposed from the perspectives of technical improvement, clinical standardization, regulatory policy and patient management, aiming to provide reference for safe clinical use and regulatory decision-making.

Objective To address the issues of process gaps, information silos, and high billing error rates (>8%) in traditional SPD (Supply, Processing, Distribution) models, this study explores the application effects of full-process barcode scanning informatization transformation in the transition to the SPD mode within large public hospitals, providing practical evidence for the refined management of medical consumables. Methods A closed-loop scanning system was constructed based on tricolor QR codes: "Red Code" (quantified management), "Yellow Code" (billing linkage), and "Green Code" (high-value consumables traceability). Fixed-quantity package thresholds were set using a dynamic safety stock algorithm (weekly average usage × fluctuation coefficient). Data on logistics efficiency and costs from six months before and after the transition were compared using paired t-tests with SPSS 26.0. Results The hospital-wide procurement expenditure for non-chargeable medical consumables decreased by 3.04% year-on-year (P=0.02), cumulatively saving over 3 million RMB. Consumable withdrawal amounts in pilot wards decreased by 5.86% to 19.18%. The billing discrepancy rate based on scanning was reduced to 2.28%-5.97% (P=0.05). Conclusion The full-process scanning transformation significantly reduces management error rates and operational costs through informatization means, providing replicable experience for the standardized promotion of the SPD mode in large public hospitals and medical insurance settlement risk control.

Objective This study aims to construct a scientific and systematic evaluation system for the maturity level of medical consumables supply chain management informatization, providing a scientific basis for high-quality development. Methods Evaluation indicators were preliminarily screened through literature review. Key indicators were optimized using the Delphi method, and indicator weights were determined via the Analytic Hierarchy Process (AHP). Results After three rounds of Delphi expert consultation, an· evaluation system for medical consumables supply chain management informatization maturity was established, comprising 6 primary indicators and 29 secondary indicators. The primary indicators and their respective weights are: Data Management (0.222), Infrastructure (0.195), Platform System (0.193), Human Resources (0.163), Management Security (0.148), and Innovation Application (0.080). Conclusion The evaluation system developed in this study features scientifically selected indicators and weightings aligned with practical needs. It provides a systematic assessment tool for the informatization management of medical consumables supply chains and highlights core focus areas for hospitals' related informatization initiatives.

Objective To develop an intelligent Internet of Things (AIoT) and improved support vector machine (SVM) state recognition model that meets the new requirements of medical imaging equipment state recognition and operation management. Methods With the help of the Intelligent Internet of Things (AIoT), an AIoT system architecture is established based on the operational characteristics of medical imaging equipment and the requirements of smart hospital scenarios, forming a three-layer collaborative framework of "perception transmission analysis". Through the real-time collection of multi-dimensional data and multi-stage preprocessing of IoT sensor networks, the non-linear SVM algorithm relies on the values of kernel function (g) and penalty parameter (C), and an improved differential evolution algorithm (IDE) is introduced to optimize the kernel function parameters of SVM, quickly and accurately completing the recognition of medical imaging equipment. Compare the state recognition performance of IDE-SVM model, traditional Gaussian kernel, LSTM neural network, and Random Forest (RF), and compare the clinical benefits before and after this model. Results Compared with other models, the improved IDE-SVM model showed higher accuracy, F1 Score, lower inference latency, and cloud data synchronization period (P<0.05); The IDE-SVM model maintains a stable CPU usage rate of 18% -22% and occupies approximately 450MB of memory;After the application of this model, there were different improvements in unplanned downtime, equipment related misdiagnosis rate, maintenance cost, and average fault response time, which were 52.9%, 61.2%, 50%, and 81.5%, respectively. Conclusion After adopting AIoT and improving SVM state recognition model, the accuracy and speed of medical imaging equipment state recognition have been significantly improved, and the efficiency of equipment operation and maintenance management has also been effectively enhanced.

Objective To address the problems existing in the current hospital network security protection system, such as vulnerability to network attacks and difficulty in adapting to the special scenarios of hospitals, a security protection system is proposed, aiming to enhance the security protection capabilities of hospital networks. Methods This system takes the zero-trust architecture as the core framework, integrates K-means clustering, random forest and deep Q-network, and quantifies the special scenario constraints of the hospital into security policy parameters. And through the closed loop of K-means data perception, random forest risk identification, deep Q-network dynamic decision-making, and system adaptive response, the refined control of hospital network security protection has been achieved. Results This system has a network threat recognition rate of 96.41% and a permission update accuracy rate of 96.95%. The response time for identifying network threats is 130.5ms, and the memory usage is 154.8MB. The average false alarm rate for detecting network attacks is 0.37%, the missed alarm rate is 1.42%, the interception rate is as high as 98.87%, the business interference rate ranges from 0.27% to 1.42%, and the compliance rate for access application control is 99.52%. Conclusion By integrating the quantification of hospital scenario constraints with intelligent algorithm optimization, the research system has significantly enhanced the protection performance of hospital network security and its adaptability to hospital business, providing a new approach for the research on network security protection in the medical industry.

ObjectiveTo comply with the regulatory requirements of national pharmaceutical authorities for real-time temperature and humidity monitoring of pharmaceuticals and medical consumables during usage, we developed a hospital cold chain monitoring system suitable for clinical operation.MethodsThe system architecture incorporates:Hardware: Huawei Hi3861 chip (RISC-V architecture) running HarmonyOS LiteOS-M;Sensors: SHT30 high-precision modules (±0.1°C for temperature, ±1.5%RH for humidity);Cloud platform: Huawei Cloud IoT for data storage and analytics;Applications: Multi-terminal software solutions;This HarmonyOS-based intelligent monitoring system achieves real-time precision surveillance and early warning for medical environments..Results Performance metrics demonstrated:Monitoring accuracy:Temperature error: 0.3±0.2°C (t=6.352, P<0.001),Humidity error: 2.1±0.9%RH (t=4.781, P<0.01),Response performance:Alarm latency: 4.2±0.8s (Z=12.463, P<0.001),Compatibility:Supports 6 terminal types (mobile/tablet/PC etc.),Data transmission success rate: 99.2±0.5% (Z=5.217, P<0.05). ConclusionThe system is not only able to monitor the refrigerator, cold storage and other cold chain equipment in each department of the hospital, but also can monitor the temperature and humidity environment of the large equipment room, which can meet the various needs of the hospital for temperature and humidity monitoring. The system comprehensively monitors various hospital environments including:Refrigerators and cold storage units,Large equipment rooms;While fulfilling all clinical monitoring requirements, it achieves:100% localization of critical components;52.3% cost reduction compared to imported systems;Scalability potential for blood bank and logistics applications

Uric acid test reagent is a rapid diagnostic reagent used for quantitative detection of uric acid concentration in human whole blood samples in vitro. In clinical practice, they are mainly used to monitor uric acid levels . The article focuses on the technical evaluation points of uric acid detection reagent product registration, and provides suggestions and references for product registration applicants and regulatory reviewers.

Based on the working principle of ultrasound equipment, this study systematically analyzes the troubleshooting and maintenance processes for three typical malfunctions of the Philips EPIQ Cvx ultrasound system (intermittent image quality degradation of multiple probes, stripe interference of single probe, and occasional error reporting). By employing a "hierarchical troubleshooting + modularized approach" combined with the equipment architecture, the study accurately identifies the source of the malfunctions and proposes solutions. Additionally, targeted preventive maintenance strategies are proposed, including regular performance testing of channel boards, increased monitoring of power supply environmental conducted noise, standardized software configuration backup management, and enhanced probe sensitivity calibration and electrical safety testing. This study provides a comprehensive solution for ultrasound equipment maintenance, encompassing "fault localization, module repair, and preventive maintenance," offering practical guidance for maintenance engineers. This helps to improve maintenance efficiency and ensure the stable operation of ultrasound equipment.

Objective Through investigating the configuration and application effect of domestic in-use medical magnetic resonance (MR) cold water machines, constructing an application effect evaluation method, and forming relevant conclusions, this study aims to assist in improving the management level of medical equipment in medical institutions and enhancing the quality of medical imaging examinations, thereby promoting the better development of domestic MR and its supporting equipment industries. Methods Through expert interviews, questionnaire surveys, and a large-sample sampling survey of MR cold water machine equipment in 123 medical institutions in seven major regions of China for the first time, the configuration of MR cold water machine equipment was comprehensively sorted out, and the application effect was analyzed. Results In terms of equipment configuration in domestic in-use MR cold water machines: The brands of MR cold water machine equipment manufacturers are concentrated in three companies, and the parameter differences of different equipment mainly lie in cooling efficiency and working mode, etc.; In terms of equipment usage effect: The maintenance cost of MR cold water machine equipment is relatively reasonable, the main maintenance mode is original factory warranty, the average annual number of faults is concentrated in 0-2 times, the maintenance response time is concentrated within 24 hours, and the overall satisfaction with equipment usage is good. ConclusionBased on the large-sample data survey, the constructed evaluation method for the application effect of MR cold water machine equipment can comprehensively and scientifically evaluate the application effect of the equipment, and has important guiding significance for medical equipment management and the application of MR equipment.

ObjectiveIn response to the prevalent clinical demand for managing upper-extremity hypertonia, this study presents a device designed to alleviate elevated muscle tone. Grounded in the principle of continuous passive motion (CPM) and developed in strict accordance with clinical guidelines, the apparatus enables controlled, repetitive mobilization of the upper limb to safely reduce spasticity. MethodsThrough the extraction and analysis of rehabilitation training movements for patients with clinically presented upper limb muscle hypertonia, the requirements for the device to achieve multi-joint coordinated functions involving the shoulder, elbow, wrist, and fingers have been clarified. Based on these requirements, the mechanical component adopts an exoskeleton-type wearable design to ensure motion trajectory accuracy and overall stability; joint motors employ the Controller Area Network (CAN) protocol for multi-degree-of-freedom coordinated control, precisely simulating shoulder and elbow rehabilitation movements; and a pneumatic glove enables finger flexion and extension training through air pressure actuation. Results Tests indicate that the device exhibits a motion cycle error of less than ±0.13 s, joint movement angle deviation within ±1°, and noise levels below 57 dB. Its electrical safety complies with the GB 9706.1–2020 standard, with both touch current and patient leakage current under normal conditions remaining below 100 μA. The structural design and functional parameters of the device strictly adhere to relevant laws and regulations. ConclusionThe device developed in this study is grounded in the CPM principle. By means of parameter-based design, it replicates therapeutic motion patterns to deliver continuous passive rehabilitation, thereby preserving joint range of motion and addressing abnormally elevated upper-limb muscle tone secondary to stroke and related conditions.

ObjectiveAddressing issues such as data silos, lack of transparency in processes, and difficulties in traceability in traditional medical device management models, this study aims to develop a blockchain-based comprehensive medical device management system to achieve end-to-end trustworthy management from departmental procurement to clinical use. Methods A consortium blockchain architecture was adopted to integrate nodes from various hospital departments. An improved PBFT consensus algorithm (transaction confirmation time <500ms) and a hybrid storage solution combining ‘on-chain hashing + off-chain IPFS’ were designed; a smart contract system encompassing five core modules, including equipment lifecycle and approval decision-making, is developed; and an innovative dynamic permission management mechanism based on attribute encryption is implemented. Results Following system implementation, key performance indicators for equipment management demonstrated significant improvement compared to pre-implementation levels: equipment turnover rate increased by 31.5%, while deployment response time decreased by 73.3%. Regarding data quality and security management, maintenance record completeness reached 100%, with 56 instances of unauthorised access successfully intercepted. In terms of system processing capacity, it consistently handled an average of 230,000 management transactions daily. All improvements in key metrics were statistically significant (P<0.05).Conclusion This study demonstrates that blockchain technology can significantly enhance the efficiency and security of medical device management. The proposed lightweight on-chain solution and dynamic permission model provide innovative solutions for medical blockchain applications, holding significant practical value for advancing hospital digital transformation.

ObjectiveTo address issues related to inaccurate monitoring, low maintenance efficiency, and poorly managed spare parts caused by multifactorial coupling faults under high pressure and frequency conditions in the expiratory flow sensor of the Hamilton G5 invasive ventilator, thereby enhancing the operational safety and cost-effectiveness of ICU critical care equipment.MethodsThis study proposes an integrated method combining multi-source signal fusion diagnosis and hierarchical collaborative maintenance. By integrating real-time high-pressure waveform features, airtightness parameters, and historical trends, a dynamic threshold adaptive diagnostic model was constructed. A three-level maintenance mechanism—"rapid calibration – component replacement – system maintenance"—was designed, and a Weibull-based life prediction model was used to optimize spare part inventory for high-pressure ventilation circuits.Results The model achieved a fault identification accuracy of 92.8% and reduced the false alarm rate to 6.2%. Maintenance efficiency increased by 57.1%, spare part turnover improved by 133.3%, and the stock-out risk was controlled within 1.5%.ConclusionThe study develops an end-to-end intelligent operation and maintenance solution for invasive ventilator sensors. Through interdisciplinary integration and engineering validation, it provides theoretical and practical support for data-driven management of critical medical equipment and promotes a shift in clinical operation and maintenance towards proactive prevention.

ObjectiveTo conduct electromagnetic compatibility design for an intelligent cardiopulmonary resuscitation machine to improve its pass rate in electromagnetic compatibility tests and shorten the registration time. MethodsKey components required for the intelligent cardiopulmonary resuscitation machine were studied and analyzed. Based on electromagnetic compatibility standards such as YY 9706.102-2021 and GB 4824-2019, conducted emission tests were performed for different installation positions of the power filter; radiation emission tests were conducted for the presence or absence of shielding in the switching power supply, whether cables were separately bundled, grounding of the servo motor and PCB board, etc. The data before and after the tests were compared and analyzed to explore their impact on conducted disturbance and radiated disturbance.Results Installing the power filter near the power inlet can effectively reduce conducted disturbance quasi-peak by more than 25dB (μV) and conducted disturbance average by more than 21dB (μV); selecting a switching power supply with transformer shielding can effectively reduce radiated disturbance quasi-peak by more than 6dB (μV/m); grounding the servo motor housing can effectively reduce radiated disturbance quasi-peak by more than 7dB (μV/m); separating and bundling cables during wiring can effectively reduce radiated disturbance quasi-peak by more than 15dB (μV/m); grounding the PCB board and grounding near external connectors can effectively reduce radiated disturbance quasi-peak by more than 15dB (μV/m).ConclusionThe intelligent cardiopulmonary resuscitation machine, through designs such as shielding, filtering, and grounding, can effectively enhance its electromagnetic compatibility, providing reference value for subsequent research on electromagnetic compatibility of intelligent cardiopulmonary resuscitation machines.

Objective To establish a clinical application evaluation framework for medical equipment, guiding procurement planning and project approval of medical equipment in hospital.Methods Issues across the full lifecycle of medical equipment were systematically analyzed. An initial clinical application evaluation framework was constructed. The clinical application evaluation framework was improved through expert consultation. The weights of each level of indicators were acquired by Analytic Hierarchy Process and Entropy Weight Method. Clinical evaluations of infusion pumps from three mainstream brands were conducted using institutional data. Results A comprehensive evaluation framework was developed, comprising 4 first-level, 4 second-level, and 24 third-level indicators. The Analytic Hierarchy Process determined that clinical usage evaluation carried the highest weight among first-level indicators, while safety held the highest weight among second-level indicators, indicating that clinical application and safety performance were the most valued factors by experts. Through the application of this clinical evaluation framework to three brands of infusion pumps in the hospital, Brand C's infusion pump exhibited optimal performance in practical applications.Conclusion This lifecycle-oriented evaluation system, characterized by structural integrity and high reliability, provides critical reference value for clinical evaluation, selection, and deployment of medical equipment.

ObjectiveBased on the HM-J-16-I accelerator, ultra-high dose rate electron FLASH (with a dose rate exceeding 40 Gy/s) was achieved through modification and precise dose control was realized. The electron beam energy and dose distribution under the electron FLASH state were verified to meet the requirements of GB15213 for conventional electron beams.MethodsBased on the 6MeV and 10MeV states, the dose rate was increased by significantly boosting the injected beam current, removing the ionization chamber, reducing the thickness of the primary and secondary scattering foils to minimize dose rate attenuation, and lowering the SSD to increase the dose rate to reach the electron FLASH threshold. The dose was precisely controlled by the pulse control unit through the control of the number of pulses.Results The highest dose rate of the 6MeV electron FLASH reached 240 Gy/s, and that of the 10MeV electron FLASH reached 415 Gy/s. The dose output stability was better than ±2%. The determination coefficients R²for 10MeV FLASH dose linearity were 0.99997 (SSD705 mm) and 0.99997 (SSD1000mm), both exceeding 0.999. The dose rate output stability was better than ±2%, with penetration index R50 at 41.4mm(SSD705mm)41.1mm (SSD1000mm).The energy variation was less than ±0.5 MeV, The flatness of the 10MeV electron FLASH at the standard depth was 5.5 mm, and the symmetry was 101.5%, and central offset CAX.Dev=0.55mm. ConclusionThe tests and analyses of the dose rate, dose, percentage depth dose curve, and off-axis ratio curve of the electron FLASH of the HM-J-16-I accelerator demonstrated that the dose rate fully met the requirements of electron FLASH and far exceeded the threshold of 40 Gy/s. Moreover, the stability of the output dose, energy, symmetry, and homogeneity all met the requirements of GB15213 for conventional electron beams. This provides important dosimetric parameters and beam characteristics for the further research and application of FLASH-RT, accelerating the development of electron FLASH in medical applications.

Acute altitude sickness is a frequent and common disease in the plateau population, and in severe cases, it will rapidly develop into high-altitude pulmonary edema and high-altitude cerebral edema, which is an important factor threatening the life safety of people. A large number of studies have confirmed the effectiveness of various objective physiological indicators such as blood pressure, blood oxygen saturation, heart rate and sleep in predicting acute altitude sickness. At present, the development of portable devices is becoming more and more mature, with the characteristics of real-time, dynamic and continuous monitoring of physiological indicators, and plays an increasingly important role in the fields of physiological monitoring and disease prevention. The application of portable devices to physiological monitoring of the plateau population has certain advantages in the prevention of acute altitude sickness. This paper aims to systematically review the application of portable monitoring devices in acute altitude sickness and highlight their application value. This paper reviews the current research status of portable devices at home and abroad from the monitoring of physiological parameters such as blood pressure, blood oxygen saturation, heart rate, and sleep, analyzes the characteristics and application effects of different types of portable devices, and discusses the intelligent prediction methods of acute altitude sickness based on data mining and artificial intelligence, as well as the challenges and countermeasures faced by system integration.

Objective To evaluate the effectiveness and correlation of corneal wavefront aberrations and double-pass optical quality analysis (OQAS) in the assessment of visual quality after small-incision lenticule extraction (SMILE). Methods This prospective study included 47 patients (93 eyes) who underwent SMILE surgery at the Affiliated Hospital of Yunnan University. Visual acuity, refraction, corneal wavefront aberrations, and OQAS-based visual quality assessments were conducted preoperatively and at 6 months postoperatively. Corneal wavefront aberrations were measured using Pentacam, with parameters including trefoil 0° [Z(3,3)], coma 0° [Z(3,1)], coma 90° [Z(3,-1)], trefoil 30° [Z(3,-3)], tetrafoil 0° [Z(4,4)], fourth-order astigmatism 0° [Z(4,2)], spherical aberration [Z(4,0)], fourth-order astigmatism 45° [Z(4,-2)], and tetrafoil 22.5° [Z(4,-4)]. OQAS parameters included modulation transfer function cutoff frequency (MTF cutoff), objective scatter index (OSI), and Strehl ratio (SR). Statistical analysis was performed using SPSS 19.0 to compare pre- and postoperative indices and analyze correlations. Results At 6 months postoperatively, uncorrected visual acuity (UCVA) improved to 1.11±0.15, and refractive error was -0.12±0.05 D, indicating satisfactory correction. Root mean square (RMS) of higher-order aberrations increased significantly from 0.333±0.081 to 0.702±0.207 (p < 0.05), with notable increases in Z(3,-1) and Z(4,0) by 0.368±0.211 and 0.165±0.114, respectively. No significant differences were observed in OSI, MTF cutoff, or SR between pre- and postoperative measurements (p > 0.05). Correlation analysis showed only weak (R<0.3) or statistically insignificant associations between corneal wavefront aberrations and OQAS parameters, both pre- and postoperatively as well as in their changes. ConclusionCorneal wavefront aberrations and the double-pass optical quality analysis system each have distinct advantages in evaluating visual quality after SMILE. The combined application of both methods contributes to a more comprehensive assessment of postoperative visual quality, providing valuable reference for the design of personalized surgical plans and postoperative management.