Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

Disease computable phenotype is a data model designed to identify specific clinical conditions or characteristics, which automatically extracts information from clinical databases such as electronic health records through algorithms. Phenotypic data for rare diseases often reside in unstructured text. Due to the scarcity of rare disease cases, atypical symptoms, and insufficient physician experience, misdiagnosis and underdiagnosis rates remain high. In this context, the application of computable phenotype technology holds promise for improving the accuracy and efficiency of rare disease diagnosis. This article reviews the current research status, challenges, and opportunities of computable phenotype technology in biomedicine, particularly in the field of rare diseases, and proposes a development and validation framework for rare disease computable phenotypes, aiming to provide research and development insights for computable phenotypes to empower the diagnosis and treatment of rare diseases.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Based on the Political Economic Social Technological(PEST)-Strengths Weakness Opportunity Threats(SWOT)model,by sorting out the macro-environmental factors such as politics,economy,society and technology,and combining the internal strengths and weaknesses of the hospital as well as the external opportunities and threats,it puts forward the strategies to optimize the comprehensive budget management.It is found that hospitals face problems in total budget management such as disconnection between budgeting and strategy,and low level of informatization,but they also have advantages such as resource optimization and support for decision-making.The external environment provides opportunities such as health insurance reform and financing channel expansion,while there are threats such as industry competition and data security.It is suggested to improve the budget management level and promote the high-quality development of hospitals by expanding funding sources,strengthening cost control,and promoting the integration of industry and finance.

Objective To investigate the correlation between the expression of serum microRNA-21-5p(miR-21-5p),microRNA-1224-5p(miR-1224-5p),and microRNA-181a-5p(miR-181a-5p)with postoperative delayed healing in patients with femoral neck fracture(FNF).Methods From October 2021 to April 2024,371 patients with FNF admitted to our hospital were included as subjects.The patients were assigned into a study group(delayed healing,68 cases)and a control group(normal healing,303 cases)based on whether the fracture ends healed 4 months after surgery.Real-time fluorescence quantitative PCR(qRT-PCR)was applied to detect the expression levels of serum miR-21-5p,miR-1224-5p,and miR-181a-5p.Multivariate Logistic regression was applied to analyze the influencing factors of postoperative healing delay in FNF patients.ROC curve was applied to analyze the predictive value of serum miR-21-5p,miR-1224-5p,and miR-181a-5p for postoperative healing delay in FNF patients.Results The levels of serum miR-21-5p,miR-1224-5p,and miR-181a-5p in the study group were lower than those in the control group(P＜0.05).Multivariate Logistic analysis showed that age ≥ 60 years old,diabetes,and smoking were risk factors for postoperative delayed healing in FNF patients(P＜0.05),and miR-21-5p,miR-1224-5p and miR-181a-5p were protective factors for postoperative delayed healing in FNF patients(P＜0.05).ROC curve showed that the AUC values of miR-21-5p,miR-1224-5p,and miR-181a-5p for predicting postoperative healing delay in FNF patients were 0.845,0.809,and 0.797,respectively.When the three were combined for prediction,the AUC increased to 0.933.The combined detection effect of the three indicators was better than that of any individual indicator(Zcombination vs.miR-21-5p=3.444,Zcombination vs.miR-1224-5p=4.401,Zcombination vs.miR-181a-5p=4.279,P＜0.05).Conclusion The levels of serum miR-21-5p,miR-1224-5p,and miR-181a-5p are reduced in FNF patients with postoperative delayed healing.The combined detection of the three may have a certain predictive value for postoperative delayed healing in FNF patients.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

Objective To evaluate the efficacy and safety of enteric-coated metformin hydrochloride capsules(Junlida?)in patients with T2DM and poor glycemic control under lifestyle interventions.Methods In this study,419 patients with T2DM were recruited from 15 research centers from July 2020 to March 2022,and randomly divided into observation(Obs)group(n=209)and control group(Con,n=210)using a multicenter,randomized,double-blind,non-inferiority trial design.Patients in the Obs group were treated with enteric-coated Metformin hydrochloride capsules(Junlida?),and patients in the Con group were treated with Metformin hydrochloride tablets(Glucophage?).The optimal effective dose of 2 g/d was achieved within 4 weeks,and the reasonable dose was maintained until the end of treatment.The treatment period was 24 weeks.HbA1c and its compliance rate,FPG,and body weight were compared between the two groups in full analysis set(FAS)and protocol set(PPS).Safety and adverse events(AE)were evaluated in safety set(SS).Results A total of 414 participants were randomized(207 cases in Obs group and 207 cases in Con group).414 cases in FAS population(207 cases in Obs group and 207 cases in Con group),and 328 cases in PPS population(164 cases in Obs group and 164 cases in Con group),and 414 cases in SS population(207 cases in Obs group and 207 cases in Con group).After treatment,HbA1c,FPG and body weight were lower in both groups(P<0.05)in FAS and PPS.HbA1c compliance rate was not significantly different between the two groups in FAS and PPS(P>0.05).The results of non-inferiority test showed that the lower limit was>-0.4%in both FAS(-0.154,95%CI-0.384～0.069)and PPS(-0.139,95%CI-0.390～0.112),and the Obs group reached non-inferiority end point.The achievement rate,compliance rate,safety index and incidence of AE were not significantly different between the two groups(P>0.05).Conclusions Junlida? demonstrated non-inferiority to Glucophage? in glycemic control and can be safely and effectively used in patients with diabetes.

Objective:To develop the Adolescent Mental Health Computerized Adaptive Test(AMH-CAT)for assessing psychological crises in adolescents using item response theory(IRT).Methods:A total of 8 679 students,aged 9 to 19 years,were sampled from 14 primary and secondary schools.The item bank was constructed by examining unidimensionality,independence,discrimination,and Differential Item Functioning(DIF).The AMH-CAT algorithm was developed using R software and validated for reliability and validity through real and simulated data.The School Psychological Interview Evaluation Form served as the criterion tool to assess the predictive validi-ty of AMH-CAT in evaluating psychological crises levels.Results:The item bank,consisting of 43 items,demon-strated unidimensionality and independence,with discrimination values＞0.80 and no DIF across genders.Under va-rious stopping rules,AMH-CAT showed ABS values＜0.40,RMSE values＜0.50,and a correlation(r)＞0.87(P＜0.001)between estimated and true psychological crises levels.Real participants answered an average of 10 items under the SE(θ)≤0.4 stopping rule,with a reliability of 0.89,and the scores were positively correlated with the complete item bank scores(r=0.95,P＜0.001).The predictive accuracy for Level 1 and Level 2 concerns was 0.89 and 0.90,respectively.Conclusion:The Adolescent Mental Health Computerized Adaptive Test(AMH-CAT)demonstrates excellent validity,reliability and assessment efficiency for evaluating adolescent psychological crises.