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

Traumatic brain injury (TBI) is intricately linked to the most severe clinical manifestations of brain damage. It encompasses dynamic pathological mechanisms, including hemodynamic disorders, excitotoxic injury, oxidative stress, mitochondrial dysfunction, inflammation, and neuronal death. This review provides a comprehensive analysis and summary of biomaterial-based tissue engineering scaffolds and nano-drug delivery systems. As an example of functionalized biomaterials, nano-drug delivery systems alter the pharmacokinetic properties of drugs. They provide multiple targeting strategies relying on factors such as morphology and scale, magnetic fields, pH, photosensitivity, and enzymes to facilitate the transport of therapeutics across the blood-brain barrier and to promote selective accumulation at the injury site. Furthermore, therapeutic agents can be incorporated into bioscaffolds to interact with the biochemical and biophysical environment of the brain. Bioscaffolds can mimic the extracellular matrix environment, regulate cellular interactions, and increase the effectiveness of local treatments following surgical interventions. Additionally, stem cell-based and exosome-dominated extracellular vesicle carriers exhibit high bioreactivity and low immunogenicity and can be used to design therapeutic agents with high bioactivity. This review also examines the utilization of endogenous bioactive materials in the treatment of TBI.

Objective To investigate the effect of triglyceride-glucose index(TyG)on the short-term prognosis of patients with initial acute ischemic stroke.Methods A total of 391 patients with initial acute ischemic stroke who were hospitalized in Kunshan Second People's Hospital and The Affiliated Suzhou Hospital of Nanjing Medical University from Jun.2020 to Jun.2023 were retrospectively included.According to the modified Rankin scale(mRS)scores at 90 d follow-up,they were assigned to good prognosis group(286 cases)or poor prognosis group(105 cases).Logistic regression and receiver operating characteristic(ROC)curve were used to evaluate the effect of TyG on the short-term prognosis of patients with initial acute ischemic stroke.Results Compared with the good prognosis group,the patients of poor prognosis group had older age,higher proportion of atrial fibrillation,higher levels of homocysteine,triglyceride,total cholesterol,low-density lipoprotein,and TyG,and higher National Institutes of Health stroke scale(NIHSS)score(all P＜0.05).Multivariate logistic regression analysis showed that age,homocysteine,TyG and NIHSS score were independent risk factors for poor prognosis in patients with initial acute ischemic stroke(all P＜0.05).ROC curve analysis showed that TyG combined with NIHSS score had good predictive value for poor prognosis of patients with initial acute ischemic stroke,and the area under curve value was 0.795.Conclusion The combination of TyG and NIHSS score is an independent influencing factor for poor short-term prognosis in patients with initial acute ischemic stroke.

Objective:To investigate the prevalence and influencing factors of depression,anxiety and comorbid depression-anxiety symptoms among college freshmen,providing a theoretical basis for promoting their mental health.Methods:From Jan to Feb 2022,an online questionnaire survey was conducted,involving 483 online questionnaires from college freshmen(184 males,299 females).The depression-anxiety-stress self-rating scale,smartphone dependence self-rating scale for adolescents,and Pittsburgh sleep quality index(PSQI)were used for online surveys.The influencing factors of depression,anxiety,and their comorbidity among college freshmen were analyzed by multivariable logistic regression analysis.Results:The detection rates of smartphone dependence,sleep disorders,depression,anxiety and comorbid depression-anxiety symptoms among college freshmen were 26.1%,12.8%,26.3%,32.1%,and 23.6%,respectively.The detection rates of depression,anxiety and comorbid depression-anxiety symptoms in male students were significantly higher than those in female students(P＜0.05).Multivariable logistic regression analysis showed that self-perceived poor mental health,smartphone dependence and sleep disorders were risk factors for depression,anxiety and comorbid depression-anxiety symptoms.Low satisfaction with college life was a risk factor for depression.Medical specialty was a risk factor for anxiety and comorbid depression-anxiety symptoms(P＜0.05).Conclusions:Male college freshmen show higher rates of depression,anxiety,and their comorbidity.Low satisfaction with college life,self-perceived poor mental health,high academic pressure,smartphone dependence,medical specialty,and sleep disorders may be risk factors for depression,anxiety and comorbid depression-anxiety symptoms among college freshmen.

Objective To investigate the relationship between the atherogenic index of plasma(AIP),carotid intima-media thick-ness(CIMT),and brachial-ankle pulse wave velocity(baPWV)with the 10-year risk of atherosclerotic cardiovascular disease(AS-CVD)in patients with type 2diabetes mellitus(T2DM).Methods This study retrospectively analyzed the clinical data of 131 T2DM pa-tients managed through the National Metabolism Management Center(MMC)at the Affiliated Central Hospital of Shandong First Medical University from January 2020 to December 2022,all of whom had undergone AIP,CIMT and baPWV assessments.The 10-year ASCVD risk for each patient was estimated using the China-PAR model,classifying patients into low-to-moderate and high-risk groups.Uni-variate analysis was employed to identify variables correlated with cardiovascular risk,followed by multivariate Logistic regression analysis to evaluate the independent impact of AIP,CIMT and baPWV on ASCVD risk.The Hosmer-Lemeshow goodness-of-fit test was used to assess the suitability of the combined variables(AIP,CIMT and baPWV).Lastly,the predictive efficacy of the combined variables and individual indicators was assessed using receiver operating characteristic(ROC)curves and the DeLong test.Results Multivariate Logis-tic regression analysis demonstrated that AIP,CIMT and baPWV were independent risk factors for ASCVD in T2DM patients(OR＞1,P＜0.05).The Hosmer-Lemeshow goodness-of-fit test indicated satisfactory model fit(x2=2.725,P=0.950).The combined variable of AIP,CIMT and baPWV exhibited superior discriminative ability in predicting ASCVD risk among T2DM patients(AUC=0.834),sig-nificantly outperforming individual variables.Conclusion AIP,CIMT and baPWV have significant clinical value in assessing ASCVD risk in T2DM patients.Integrating these indicators enhances predictive performance,offering an effective tool for individualized cardiovascular risk assessment in T2DM patients.

Objective:To investigate the prevalence and influencing factors of depression,anxiety and comorbid depression-anxiety symptoms among college freshmen,providing a theoretical basis for promoting their mental health.Methods:From Jan to Feb 2022,an online questionnaire survey was conducted,involving 483 online questionnaires from college freshmen(184 males,299 females).The depression-anxiety-stress self-rating scale,smartphone dependence self-rating scale for adolescents,and Pittsburgh sleep quality index(PSQI)were used for online surveys.The influencing factors of depression,anxiety,and their comorbidity among college freshmen were analyzed by multivariable logistic regression analysis.Results:The detection rates of smartphone dependence,sleep disorders,depression,anxiety and comorbid depression-anxiety symptoms among college freshmen were 26.1%,12.8%,26.3%,32.1%,and 23.6%,respectively.The detection rates of depression,anxiety and comorbid depression-anxiety symptoms in male students were significantly higher than those in female students(P＜0.05).Multivariable logistic regression analysis showed that self-perceived poor mental health,smartphone dependence and sleep disorders were risk factors for depression,anxiety and comorbid depression-anxiety symptoms.Low satisfaction with college life was a risk factor for depression.Medical specialty was a risk factor for anxiety and comorbid depression-anxiety symptoms(P＜0.05).Conclusions:Male college freshmen show higher rates of depression,anxiety,and their comorbidity.Low satisfaction with college life,self-perceived poor mental health,high academic pressure,smartphone dependence,medical specialty,and sleep disorders may be risk factors for depression,anxiety and comorbid depression-anxiety symptoms among college freshmen.

Objective To investigate the relationship between the atherogenic index of plasma(AIP),carotid intima-media thick-ness(CIMT),and brachial-ankle pulse wave velocity(baPWV)with the 10-year risk of atherosclerotic cardiovascular disease(AS-CVD)in patients with type 2diabetes mellitus(T2DM).Methods This study retrospectively analyzed the clinical data of 131 T2DM pa-tients managed through the National Metabolism Management Center(MMC)at the Affiliated Central Hospital of Shandong First Medical University from January 2020 to December 2022,all of whom had undergone AIP,CIMT and baPWV assessments.The 10-year ASCVD risk for each patient was estimated using the China-PAR model,classifying patients into low-to-moderate and high-risk groups.Uni-variate analysis was employed to identify variables correlated with cardiovascular risk,followed by multivariate Logistic regression analysis to evaluate the independent impact of AIP,CIMT and baPWV on ASCVD risk.The Hosmer-Lemeshow goodness-of-fit test was used to assess the suitability of the combined variables(AIP,CIMT and baPWV).Lastly,the predictive efficacy of the combined variables and individual indicators was assessed using receiver operating characteristic(ROC)curves and the DeLong test.Results Multivariate Logis-tic regression analysis demonstrated that AIP,CIMT and baPWV were independent risk factors for ASCVD in T2DM patients(OR＞1,P＜0.05).The Hosmer-Lemeshow goodness-of-fit test indicated satisfactory model fit(x2=2.725,P=0.950).The combined variable of AIP,CIMT and baPWV exhibited superior discriminative ability in predicting ASCVD risk among T2DM patients(AUC=0.834),sig-nificantly outperforming individual variables.Conclusion AIP,CIMT and baPWV have significant clinical value in assessing ASCVD risk in T2DM patients.Integrating these indicators enhances predictive performance,offering an effective tool for individualized cardiovascular risk assessment in T2DM patients.

Purpose/Significance A prediction model is constructed based on real-world data to achieve prediction and early screening of type 2 diabetic microvascular complications.Method/Process Based on the real world data of Nanjing Drum Tower Hospital in the past 10 years,a particle swarm optimization based deep belief network(PSO-DBN)prediction model for microvascular complica-tions in type 2 diabetes mellitus is constructed by taking test results and medical record documents into consideration.Result/Conclusion The PSO-DBN model can predict diabetic microvascular complications,and the performance is better than that of random forest and sup-port vector machine(SVM)benchmark models,it provides references for the research of disease prediction model of real-world data.

Objective To investigate the effects and mechanisms of Zhenxin Anshen Prescription(composed of Os Draconis,Ostreae Concha,Lophatheri Herba,Drynariae Rhizoma,Poria)on mice with atopic dermatitis(AD)based on the calcium channel regulator 1(ORAI1)/nuclear factor of T-cells(NFAT)signalling axis.Methods Thirty-six BALB/c mice were randomly divided into a blank control group,a model group,a Cetirizine group(1.3 mg·kg-1)and a Zhenxin Anshen Prescription group(36.36 g·kg-1),with nine mice in each group.AD mouse model was established using 1-chloro-2,4-dinitrobenzene(DNCB)induction.The drug was administered by gavage once a day for 2 weeks.At the end of drug administration,the area of skin lesions was measured and the severity of skin lesions was scored;spleen mass was measured and spleen index was calculated;pathological changes of skin lesion tissues were observed by HE staining;interleukin 4(IL-4),IL-13 and thymic stromal lymphopoietin(TSLP)in serum were detected by ELISA;and the protein expression levels of ORAI1,calmodulin phosphatase A(CaN)and nuclear factor of T cells 2(NFAT2)were detected by Western Blot.Results Compared with the blank control group,the skin lesion score of mice in the model group was significantly increased(P＜0.01),the skin lesion area was significantly enlarged(P＜0.01);the thickness of the epidermis and dermis were significantly increased(P＜0.01),hyperkeratosis of the epidermis,hypertrophy of the stratum spinosum,and infiltration of inflammatory cells such as eosinophils and lymphocytes can be seen in the dermis;the splenic index and serum IL-4,IL-13,TSLP levels were significantly increased(P＜0.01);protein expression levels of CaN,NFAT2,ORAI1 were significantly increased in the skin lesion tissues(P＜0.01).Compared with the model group,the dermatitis score of mice in the Zhenxin Anshen Prescription group was significantly decreased(P＜0.01),the lesion area was significantly reduced(P＜0.01),the epidermal and dermal thicknesses(P＜0.01),the hyperkeratosis of epidermis was alleviated,the spinous layer was slightly hypertrophic,and there was a small amount of inflammatory cell infiltration in the dermis;the splenic index and the levels of serum IL-4,IL-13,and TSLP were significantly decreased(P＜0.01);the protein expressions levels of CaN,NFAT2,and ORAI1 in the skin lesion tissues were significantly decreased(P＜0.01).Conclusion Zhenxin Anshen Prescription can ameliorate dermatopathological injury in DNCB-induced AD mice,and the mechanism may be related to its ability to inhibit the protein expressions of ORAI1,CaN and NFAT2,reduce the levels of serum type 2 inflammatory factors TSLP,IL-4 and IL-13,and ameliorate cutaneous inflammation and itching through immunomodulation.

By studying the current situation of multi-agent collaborative innovation and clinical achievements transformation at home and abroad, it is clear that multi-agent collaborative innovation is the only way for clinical research achievements transformation under the current background. This paper proposes a set of transformation path of clinical research achievements based on the multi-agent collaborative innovation platform of "production, teaching, research and medicine", which is supported by policy guidance and innovation management, and explore the role of equipment management department in achievement transformation.