Medical equipment, as an important indicator of smart hospital evaluation, plays a vital role in hospital operations. To ensure the safe and efficient operation of medical equipment, a reasonable performance evaluation system is indispensable. This study introduces a platform based on Internet of Things (IoT) technology that connects medical devices and collects data, achieving standardized and structured data processing, and supporting online operational supervision. Through the Delphi method, a performance evaluation system for large medical equipment is constructed, including 4 primary indicators and 22 secondary indicators. DICOM data acquisition devices are used to achieve functions such as efficiency analysis, benefit analysis, usage evaluation, and decision-making support for medical equipment. The study is still in its early stages, and in the future, it is expected to integrate more types of equipment, achieve rational resource allocation, and significantly impact decision-making for the development of public hospitals.
Internet of Things ; Delphi Technique

Astragali Radix (AR), a traditional Chinese medicine (TCM), has demonstrated therapeutic efficacy against various diseases, including cardiovascular conditions, over centuries of use. While doxorubicin serves as an effective chemotherapeutic agent against multiple cancers, its clinical application remains constrained by significant cardiotoxicity. Research has indicated that AR exhibits protective properties against doxorubicin-induced cardiomyopathy (DIC); however, the specific bioactive components and underlying mechanisms responsible for this therapeutic effect remain incompletely understood. This investigation seeks to identify the protective bioactive components in AR against DIC and elucidate their mechanisms of action. Through network medicine analysis, astragaloside IV (AsIV) and formononetin (FMT) were identified as potential cardioprotective agents from 129 AR components. In vitro experiments using H9c2 rat cardiomyocytes revealed that the AsIV-FMT combination (AFC) effectively reduced doxorubicin-induced cell death in a dose-dependent manner, with optimal efficacy at a 1∶2 ratio. In vivo, AFC enhanced survival rates and improved cardiac function in both acute and chronic DIC mouse models. Additionally, AFC demonstrated cardiac protection while maintaining doxorubicin's anti-cancer efficacy in a breast cancer mouse model. Lipidomic and metabolomics analyses revealed that AFC normalized doxorubicin-induced lipid profile alterations, particularly by reducing fatty acid accumulation. Gene knockdown studies and inhibitor experiments in H9c2 cells demonstrated that AsIV and FMT upregulated peroxisome proliferator activated receptor γ coactivator 1α (PGC-1α) and PPARα, respectively, two key proteins involved in fatty acid metabolism. This research establishes AFC as a promising therapeutic approach for DIC, highlighting the significance of multi-target therapies derived from natural herbals in contemporary medicine.
Animals ; Doxorubicin/adverse effects* ; Saponins/administration & dosage* ; Isoflavones/pharmacology* ; Rats ; Cardiomyopathies/prevention & control* ; Mice ; Fatty Acids/metabolism* ; Myocytes, Cardiac/metabolism* ; Triterpenes/administration & dosage* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Cardiotonic Agents/administration & dosage* ; Mice, Inbred C57BL ; Cell Line ; Astragalus Plant/chemistry* ; Astragalus propinquus

Objective To select high-quality and cost-effective dural(spinal)membrane repair materials,in order to reduce the cost of consumables procurement,save medical insurance funds,and optimize hospital operation and management.Methods Taking the BS06B disease group(spinal cord and spinal canal surgery without extremely severe or severe complications and comorbidities,mainly diagnosed as congenital tethered cord syndrome)as an example,a retrospective analysis was conducted on the relevant data of surgical treatment for congenital tethered cord syndrome conducted in our hospital from January 2021 to June 2023.Safety and efficacy indicators in clinical application(incidence of postoperative epidural hemorrhage,incidence of postoperative purulent cerebrospinal meningitis,incidence of cerebrospinal fluid leakage,surgical duration,and postoperative hospital stay)were compared.Results There was no difference in safety and effectiveness between different brands of dura mater repair materials.Conclusion For the repair of small incisions in dura mater surgery,high-quality and cost-effective dura mater repair materials can be selected to reduce hospital costs and control expenses for the disease group.

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.

Purpose To investigate the fusion model based on MRI radiomics and deep learning to predict the telomerase reverse transcriptase promoter(TERTp)mutation status in isocitrate dehydrogenase-wildtype diffuse astrocytoma.Materials and Methods A retrospective analysis of 175 patients with isocitrate dehydrogenase-wildtype diffuse astrocytoma(122 in the training group and 53 in the test group)from January 2019 to June 2021 in the First Affiliated Hospital of Chongqing Medical University.The Cancer Genome Atlas and The Cancer Imaging Archive were performed to assess TERTp mutation status.The edema and tumor regions were outlined on T1c and T2f images,deep learning model were constructed using the SE-Net model,radiomics features of different regions(edema region,tumor region and overall lesion)were extracted,and 11 features were screened by the least absolute shrinkage and selection operator to build radiomics model.Finally,the radiomics model,deep learning model and clinical model containing Visually Accessible Rembrandt Images features were combined as fusion model,and the model was evaluated using calibration curves and decision curves.Results Six predictive models were eventually built,with an area under curve(AUC)of 0.815(95%CI 0.738-0.892)and 0.645(95%CI 0.494-0.796)for the training and test groups of the clinical model;the AUC for the training and test groups of the deep learning model was 0.860(95%CI 0.798-0.922)and 0.735(95%CI 0.614-0.856);the fusion radiomics model had better predictive performance than the edema or tumor region radiomics models alone,with AUC of 0.906(95%CI 0.856-0.955)and 0.867(95%CI 0.769-0.964)in the training and test groups;the fusion model showed the best performance,with AUC of 0.964(95%CI 0.929-1.000)and 0.905(95%CI 0.818-0.991)in the training and test groups.Conclusion The clinical fusion model of radiomics combined with deep learning performed well in predicting TERTp mutation status in isocitrate dehydrogenase-wildtype diffuse astrocytoma.

Objective:To explore the effect of staged rehabilitation nursing in patients undergoing arthroscopic rotator cuff repair.Methods:From January 2021 to December 2022, convenience sampling was used to select 73 patients who underwent arthroscopic rotator cuff repair in the Department of Hand Surgery at Affiliated Hospital of Nantong University as participants. According to the random number table method, patients were divided into a control group ( n=36) and an observation group ( n=37). Control group received routine rehabilitation nursing, while observation group received staged rehabilitation nursing. The University of California, Los Angeles (UCLA) Shoulder Rating Scale score, American Shoulder and Elbow Surgeons (ASES) Rating Scale score, Constant-Murley Shoulder Scale score, and complications during rehabilitation were compared between two groups of patients before and six months after intervention. Results:Six months after surgery, both groups showed an increase in UCLA scores and ASES scores compared to before the intervention ( P<0.05), and the scores of observation group were higher than those of control group, with statistical differences ( P<0.05). Six months after surgery, the Constant-Murley Shoulder Scale scores for daily life and shoulder range of motion in observation group were higher than those in control group, and the differences were statistically significant ( P<0.05). During the rehabilitation period, the incidence of complications in observation group was lower than that in control group with a statistical difference ( P<0.05) . Conclusions:Staged rehabilitation nursing in patients undergoing arthroscopic rotator cuff repair shows significant effects and can effectively promote patient recovery.

Objective To construct a MRI-based radiomics nomogram for predicting the Cyelin-Dependent Kinase Inhibitor 2A/B(CDKN 2A/B)homozygous deletion status in patients with isocitrate dehydrogenase(IDH)-mutant astrocytoma.Methods A total of 200 patients with IDH-mutant astrocytoma(103 CDKN 2A/B homozygous deletion and 97 CDKN 2A/B non-homozygous dele-tion)were enrolled in a training cohort(n=140)and a test cohort(n=60).A total of 1 946 features were respectively extracted in tumor edema area and tumor parenchyma area,and 3 892 features were extracted in overall tumor area.All features were extracted from T2 fluid attenuated inversion recovery(T2 FLAIR)and T1 WI contrast enhancement sequences.The t test and the least absolute shrinkage and selection operator(LASSO)model were used to select radiomics features,and a radiomics nomogram was constructed by using age,gen-der and the above radiomics features.Results The t test concluded that the overall tumor radiomics signature had the best perform-ance[area under the curve(AUC):training cohort=0.951,test cohort=0.779]and the radiomics nomogram had a good ability to pre-dict the CDKN 2A/B homozygous deletion in IDH-mutant astrocytoma.The clinical usefulness of the nomogram in predicting the CDKN 2A/B homozygous deletion was further confirmed by decision curve analysis(DCA).Conclusion The nomogram combined with age,gender,and the radiomics features provides a clinically useful approach to predict the CDKN 2A/B homozygous deletion and facilitated MRI-based clinical decision-making in patients with IDH-mutant astrocytoma.

BACKGROUND:Nanocomposite hydrogel has great research prospects and application potential in the treatment of osteoarthritis. OBJECTIVE:To review the research progress of nanocomposite hydrogel in osteoarthritis and cartilage repair. METHODS:Databases such as CNKI and PubMed were searched.The English key words were"nanocomposite hydrogel,nanogel,osteoarthritis,cartage,physical encapsulation,electrostatic interaction,covalent crosslinking",and the Chinese key words were"nanocomposite hydrogel,nanogel,osteoarthritis,cartage,physical encapsulation,physical encapsulation,electrostatic effect,covalent cross-linking".After an initial screening of all articles based on inclusion and exclusion criteria,71 articles with high correlation were retained for review. RESULTS AND CONCLUSION:In cell or animal experiments,nanocomposite hydrogel has the effect of improving osteoarthritis.Nanocomposite hydrogel can promote cartilage repair,improve the internal environment of osteoarthritis,and achieve the therapeutic purpose of osteoarthritis by improving the mechanical environment between joints,carrying targeted drugs,and promoting the chondrogenesis of seed cells.At present,the research of nanocomposite hydrogel in osteoarthritis disease still has a huge space to play.It is expected to open up a new way for the clinical treatment of osteoarthritis by continuing to deepen the research of material preparation and actively carrying out cell and animal experiments.

Objective:To evaluate direct and indirect costs for schizophrenia,major depressive disorder(MDD)and bipolar disorder,and to compare their differences of cost composition,and to explore the drivers of the total costs.Methods:A total of 3 175 inpatients with schizophrenia,MDD,and bipolar disorder were recruited.In-patient's self-report total direct of medical costs outpatient and inpatient,out-of-pocket costs,and direct non-medical costs were regarded as direct costs.Productivity loss and other loss caused by damaging properties were defined as indirect costs.The perspectives of this study included individual and societal levels.Multivariate regression analysis was applied for detecting the factors influencing disease costs.Results:The total cost of schizophrenia was higher than those of MDD and bipolar disorder at individual and societal levels.The indirect costs of three mental disorders were higher than the direct costs,and the indirect cost ratio of bipolar disorder was higher than those of schizophre-nia and MDD.Age,gender,working condition and marital status(P＜0.05)were the important drivers of total costs.Conclusion:The economic burden of the three mental disorders is relatively heavy.Schizophrenia has heaviest disease burden,and the productivity loss due to mental disorders is the driving force of the soaring disease cost