OBJECTIVES<p>Timely access to appropriate levels of care is essential for improving maternal, newborn,
and child health outcomes. To address persistent service delivery fragmentation and strengthen referral systems, the Philippine Department of Health issued Administrative Order 2020-0019 to guide the design of Health Care Provider Networks (HCPNs) under the Universal Health Care Act of 2019. This study assessed the extent to which sixteen municipalities across four provinces in Eastern Visayas comply with the HCPN service delivery guidelines in the context of maternal and newborn care.p>METHODS<p>The study employed a descriptive cross-sectional mixed-methods design, utilizing structured facility checklists to assess compliance with HCPN standards. Qualitative data were gathered through key informant interviews and focus group discussions with purposively selected stakeholders—decision makers, health personnel, and mothers—to contextualize findings. A three-lever framework for integrated care (policy, operational, and cross- cutting) guided the analysisp>RESULTS<p>The findings revealed significant gaps between the current capacities of study health facilities and the requirements outlined in the HCPN guidelines. Major gaps included (1) weak cooperative governance mechanisms to support network-wide coordination; (2) limited systematic linkages between facilities, including fragmented referral protocols and non-interoperable health information systems; (3) inadequate investments in infrastructure, health human resources, and medical commodities; and (4) absence of performance monitoring systems across HCPNs.p>CONCLUSION<p> 
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Human ; Information Systems ; Occupational Groups ; Referral And Consultation ; Universal Health Care ; Delivery Of Health Care

Objective To investigate the current status of work readiness and its influencing factors among patients returning to work after lung cancer surgery. Methods A retrospective study was conducted on young and middle-aged postoperative lung cancer patients who were treated at the Department of Thoracic Surgery, West China Hospital, Sichuan University from March to September 2023 and returned to their jobs. Data were collected through a general information questionnaire, readiness for return-to-work scale (RRTW), general self-efficacy scale (GSES), and simplified coping style questionnaire (SCSQ). Univariate and multivariate logistic regression analyses were used to explore the factors affecting the work readiness of patients returning to work. Results A total of 219 patients were included, with 59 males and 160 females aged 18-60 years. Among the postoperative lung cancer patients returning to work, 73.1% were in the active maintenance stage of return-to-work readiness with a RRTW score of (17.59±1.48) points, and 26.9% were in the uncertain maintenance stage with a RRTW score of (16.22±1.50) points. Multivariate logistic regression analysis showed that patients aged≤30 years (OR=52.381), employees of enterprises and institutions (OR=7.682), agricultural, pastoral, fishery, forestry laborers (OR=15.665), positive coping (OR=5.043), those with higher self-efficacy (OR=1.157) and engaged in physically demanding work (OR=2.449) had higher return-to-work readiness, while patients with≥2 children (OR=0.055), self-payment (OR=0.044), and those working more than 40 hours per week (OR=0.122) had lower return-to-work readiness. Conclusion The return-to-work readiness of young and middle-aged postoperative lung cancer patients needs to be improved, and occupation, job nature, main coping styles, general self-efficacy and other factors are associated with return-to-work readiness.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

Pulmonary endometriosis (PEM) is a rare disease with diverse clinical manifestations, most commonly presenting as hemoptysis, while patients presenting solely with pulmonary nodules are less common. Here, we report three female patients (aged 32, 19, and 46 years, respectively). One patient sought medical attention due to hemoptysis during menstruation, while the other two had no obvious symptoms and were found to have pulmonary nodules during routine physical examinations. Two patients had a history of cesarean section, and one had a history of miscarriage. Pathologically, one patient of PEM showed extensive hemorrhage in the alveolar spaces, with fragmented endometrial glandular epithelium observed within the hemorrhagic foci. The other two patients exhibited proliferative endometrial glands and stroma, surrounded by old hemorrhage. Immunohistochemistry revealed that the endometrial glands and stroma in all three patients were positive for estrogen receptor, progesterone receptor, and vimentin, with CD10 positivity in the endometrial stroma. All three patients were definitively diagnosed as PEM by pathology and underwent thoracoscopic pulmonary wedge resection. Follow-up periods were 18, 31, and 49 months, respectively, with no recurrence observed in any of the patients.

Left ventricular assist device (LVAD) serves as a critical therapeutic option for patients with end-stage heart failure, significantly enhancing survival rates and quality of life. However, LVAD implantation exerts complex and profound effects on right ventricular (RV) function, with RV dysfunction emerging as a key factor influencing the prognosis of LVAD patients. This article systematically reviews the relationship between LVAD and RV function, exploring the importance of RV function in LVAD patients, assessment methods, underlying mechanisms of impact, and strategies for prevention and management. Comprehensive evidence suggests that preoperative evaluation of RV function is crucial for predicting the risk of RV dysfunction, while effective prevention and management rely on preoperative optimization, meticulous intraoperative techniques, rigorous postoperative monitoring, and multidisciplinary collaboration. Furthermore, this review discusses the potential and future directions of emerging technologies, such as improved LVAD designs, biventricular assist devices, gene therapy, and personalized medicine, in ameliorating RV dysfunction. In conclusion, RV function is one of the key determinants of successful LVAD therapy. Through comprehensive assessment, prevention, and management of RV function, coupled with the application of novel technologies, the clinical outcomes of LVAD patients can be further improved.

This paper realized a portable brain-computer interface (BCI) system tailored for smart healthcare. Through the decoding of steady-state visual evoked potential (SSVEP), this system can rapidly and accurately identify the intentions of subjects, thereby meeting the practical demands of daily medical scenarios. Firstly, an SSVEP stimulation interface and an electroencephalogram (EEG) signal acquisition software were designed, which enable the system to execute multi-target and multi-task operations while also incorporating data visualization functionality. Secondly, the EEG signals recorded from the occipital region were decomposed into eight sub-frequency bands using filter bank canonical correlation analysis (FBCCA). Subsequently, the similarity between each sub-band signal and the reference signals was computed to achieve efficient SSVEP decoding. Finally, 15 subjects were recruited to participate in the online evaluation of the system. The experimental results indicated that in real-world scenarios, the system achieved an average accuracy of 85.19% in identifying the intentions of the subjects, and an information transfer rate (ITR) of 37.52 bit/min. This system was awarded third prize in the Visual BCI Innovation Application Development competition at the 2024 World Robot Contest, validating its effectiveness. In conclusion, this study has developed a portable, multifunctional SSVEP online decoding system, providing an effective approach for human-computer interaction in smart healthcare.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Electroencephalography ; Signal Processing, Computer-Assisted ; Software ; Adult ; Male

This study aims to develop a fully automated method for tooth segmentation and root canal measurement based on cone beam computed tomography (CBCT) images, providing objective, efficient, and accurate measurement results to guide and assist clinicians in root canal diagnosis grading, instrument selection, and preoperative planning. The method utilized Attention U-Net to recognize tooth descriptors, cropped regions of interest (ROIs) based on the center of mass of these descriptors, and applied an integrated deep learning method for segmentation. The segmentation results were mapped back to the original coordinates and position-corrected, followed by automatic measurement and visualization of root canal lengths and angles. The results indicated that the Dice coefficient for segmentation was 96.42%, the Jaccard coefficient was 93.11%, the Hausdorff Distance was 2.07 mm, and the average surface distance was 0.23 mm, all of which surpassed existing methods. The relative error of the root canal working length measurement was 3.15% (< 5%), the curvature angle error was 2.85 °, and the correct classification rate of the treatment difficulty coefficient was 90.48%. The proposed methods all achieved favorable results, which can provide an important reference for clinical application.
Cone-Beam Computed Tomography/methods* ; Deep Learning ; Humans ; Dental Pulp Cavity/diagnostic imaging* ; Image Processing, Computer-Assisted/methods*

In order to meet the need of autonomous control of patients with severe limb disorders, this paper designs a nursing bed control system based on motor imagery-brain computer interface (MI-BCI). In view of the low decoding performance of cross-subjects and the dynamic fluctuation of cognitive state in the existing MI-BCI technology, the neural network structure optimization and user interaction feedback enhancement are improved. Firstly, the optimized dual-branch graph convolution multi-scale neural network integrates dynamic graph convolution and multi-scale convolution. The average classification accuracy is higher than that of multi-scale attention temporal convolution network, Gram angle field combined with convolution long short term memory hybrid network, Transformer-based graph convolution network and other existing methods. Secondly, a dual visual feedback mechanism is constructed, in which electroencephalogram (EEG) topographic map feedback can improve the discrimination of spatial patterns, and attention state feedback can enhance the temporal stability of signals. Compared with the single EEG topographic map feedback and non-feedback system, the average classification accuracy of the proposed method is also greatly improved. Finally, in the four classification control task of nursing bed, the average control accuracy of the system is 90.84%, and the information transmission rate is 84.78 bits/min. In summary, this paper provides a reliable technical solution for improving the autonomous interaction ability of patients with severe limb disorders, which has important theoretical significance and application value.
Humans ; Brain-Computer Interfaces ; Deep Learning ; Electroencephalography ; Feedback, Sensory ; Neural Networks, Computer ; Beds

OBJECTIVE: To evaluate the early effectiveness of navigation-free robot-assisted total knee arthroplasty (TKA) compared to traditional TKA in the treatment of knee osteoarthritis combined with extra-articular deformities. METHODS: The clinical data of 30 patients with knee osteoarthritis combined with extra-articular deformities who met the selection criteria between June 2019 and January 2024 were retrospectively analyzed. Fifteen patients underwent CORI navigation-free robot-assisted TKA and intra-articular osteotomy (robot group) and 15 patients underwent traditional TKA and intra-articular osteotomy (traditional group). There was no significant difference in age, gender, body mass index, affected knee side, extra-articular deformity angle, deformity position, deformity type, and preoperative knee range of motion, American Knee Society (KSS) knee score and KSS function score, and lower limb alignment deviation between the two groups ( P>0.05). The operation time, intraoperative blood loss, and complications of the two groups were recorded and compared. The knee range of motion and lower limb alignment deviation were recorded before operation and at 6 months after operation, and the knee joint function was evaluated by KSS knee score and function score. RESULTS: There was no significant difference in operation time between the two groups ( P>0.05); the intraoperative blood loss in the robot group was significantly less than that in the traditional group ( P<0.05). Patients in both groups were followed up 6-12 months, with an average of 8.7 months. The incisions of all patients healed well, and there was no postoperative complication such as thrombosis or infection. At 6 months after operation, X-ray examination showed that the position of the prosthesis was good in both groups, and there was no loosening or dislocation of the prosthesis. The knee joint range of motion, the lower limb alignment deviation, and the KSS knee score and KSS function score significantly improved in both groups ( P<0.05) compared to preoperative ones. The changes of lower limb alignment deviation and KSS function score between pre- and post-operation in the robot group were significantly better than those in the traditional group ( P<0.05), while the changes of other indicators between pre- and post-operation in the two groups were not significant ( P>0.05). CONCLUSION Compared to traditional TKA, navigation-free robot-assisted TKA for knee osteoarthritis with extra-articular deformities results in less intraoperative blood loss, more precise reconstruction of lower limb alignment, and better early effectiveness. However, long-term effectiveness require further investigation.
Humans ; Arthroplasty, Replacement, Knee/methods* ; Osteoarthritis, Knee/surgery* ; Robotic Surgical Procedures/methods* ; Male ; Female ; Retrospective Studies ; Range of Motion, Articular ; Middle Aged ; Aged ; Treatment Outcome ; Osteotomy/methods* ; Knee Joint/physiopathology* ; Operative Time

OBJECTIVE: To explore the differences in the implantation safety and stability of a S ₁ alar-iliac screw (S1AIS) or S2AIS for sacroiliac joint fixation, providing reference for selecting appropriate internal fixation in clinical practice. METHODS: Patients who underwent pelvic CT examination between January 2024 and December 2024 were selected. CT data from 80 patients with normal pelvic structure who met the selection criteria were included in a 1∶1 male to female ratio. CT digital reconstruction technology was used to measure the transverse and longitudinal diameters of the S1AIS and S2AIS insertable ranges, as well as the length, width, and sacral side length of the screw trajectory. The pelvic CT data from 30 patients were randomly selected based on a 1∶1 male to female ratio for three-dimensional (3D) printing of pelvic samples. The S1AIS/S2AIS with a diameter of 6.5 mm and 8.0 mm were implanted at the optimal entry/exit points on the left and right sides, respectively, to observe the perforation of the screw trajectory. The pelvic CT data from 1 patient was randomly selected for 3D printing of 10 pelvic samples to simulate Tile C2 fracture. They were divided into S1AIS group ( n=5) and S2AIS group ( n=5), with one S1AIS and one S2AIS fixation used for posterior sacroiliac joint separation, and the specimen stiffness and maximum load were measured by using an electric tension torsion dual axis universal mechanical tester. RESULTS: The anatomical parameter measurement showed that there was no significant difference in the length and width of the screw trajectory between S1AIS and S2AIS ( P>0.05), but the transverse and longitudinal diameters of the insertable ranges, as well as the sacral side length of the screw trajectory, were all greater than those of S2AIS, with significant differences ( P<0.05). After simulating the implantation of S1AIS and S2AIS with a diameter of 6.5 mm in pelvic specimens, no screw penetration was observed. Both S1AIS and S2AIS with a diameter of 8.0 mm showed screw penetration, with S2AIS having a higher incidence of posterior lateral sacral cortical penetration (46.7%) than S1AIS (3.3%) ( P<0.05). The biomechanical test showed that the stiffness and maximum load of S2AIS were significantly lower than those of S1AIS ( P<0.05). CONCLUSION As a method to fix the sacroiliac joint, the S1AIS has a larger insertable range, a longer sacral side length of the screw trajectory, a lower incidence of posterior lateral cortical rupture of the sacrum, and a greater fixation strength than S2AIS. Therefore, the implantation safety and fixation stability of the S1AIS are superior to S2AIS, and a diameter less than 8.0 mm screws should be selected as S2AIS for Chinese people.
Humans ; Bone Screws ; Sacroiliac Joint/diagnostic imaging* ; Male ; Female ; Sacrum/diagnostic imaging* ; Fracture Fixation, Internal/instrumentation* ; Ilium/diagnostic imaging* ; Tomography, X-Ray Computed ; Middle Aged ; Adult ; Printing, Three-Dimensional ; Aged