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.

Objective To analyze the clinical characteristics of measles cases in the measles elimination stage and to provide a scientific basis for the prevention, control, diagnosis and treatment of measles. Methods The descriptive epidemiological method was used to analyze the clinical characteristics of 442 confirmed measles cases in Hebei Province from 2018 to 2020. Results Among the 442 measles cases, the main symptoms were rash (96.61%), fever (90.50%), cough (56.11%), and Koplik spots (30.09%). Complications were mainly pneumonia (12.22%). There were significant differences in symptoms among different age groups (P < 0.05). The incidence of symptoms in children under 5 years old (except cough) was higher than that in other age groups. Immunization history had no significant impact on the symptoms of fever and rash (P > 0.05), but the incidence of symptoms such as cough, conjunctivitis, Koplik's spots and catarrhal rhinitis in the immunized group was lower than that in the non-immunized group (P < 0.05). The group with an interval of 0 days from fever to rash was the largest, and the proportion of people with an immunization history in the 0-day group (68.06%) was significantly higher than that in the 3-4-day group (49.44%) (P < 0.05). Pneumonia complications were mainly concentrated in children under 5 years old (87.03%), and most of the cases had a 0-dose immunization history (81.48%). Conclusion In the measles elimination stage, the incidence of fever and rash in cases is relatively high, while the incidence of Koplik spots is relatively low. The symptoms are more obvious in the younger age group. Vaccination can reduce the incidence of specific symptoms. The change in the time of rash appearance suggests that the diagnosis and treatment plan need to be adjusted. This study provides key data support for the formulation of measles prevention, control and treatment strategies.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

BACKGROUND:Spinal cord injury is a neurological disorder caused by traumatic or non-traumatic events,often leading to severe functional impairment below the injured segment.In recent years,neural stem cell transplantation has been considered to have significant therapeutic potential in regulating the inflammatory response after spinal cord injury,inhibiting excessive proliferation of glial scars,and promoting nerve regeneration. OBJECTIVE:To review and discuss the potential mechanism of action of acupuncture and neural stem cell transplantation therapy in inhibiting spinal cord injury-induced secondary injury,and to delve into the scientific basis for its treatment of spinal cord injury. METHODS:PubMed,Elsevier,WanFang,and CNKI databases were searched using"spinal cord injury,acupuncture,neural stem cells,SDF-1α/CXCR4 axis"as Chinese and English search terms.Totally 96 articles were finally included.The research findings of acupuncture combined with neural stem cells in the treatment of spinal cord injury were summarized and analyzed,and the mechanism of this combination therapy in the treatment of secondary injury after spinal cord injury was summarized. RESULTS AND CONCLUSION:(1)The stromal-derived factor 1α(SDF-1α)/chemokine receptor 4(CXCR4)axis plays a crucial role in neural stem cell transplantation for spinal cord injury.This signaling mechanism not only affects neural stem cell migration,proliferation,and differentiation,but is also a key factor in determining the efficiency of stem cell homing to the injury site.Therefore,the regulation of targeting this axis is of great significance in enhancing the therapeutic effect of spinal cord injury.(2)Acupuncture,as a traditional Chinese medicine therapy,shows unique advantages in the regulation of secondary injury in spinal cord injury.It can effectively reduce secondary injury after spinal cord injury by regulating inflammatory response,inhibiting apoptosis,improving microcirculation,reducing glial scar formation,and counteracting oxidative stress.(3)Acupuncture was also able to influence the expression and function of the SDF-1α/CXCR4 axis,thereby enhancing the homing and survival ability of neural stem cells and promoting nerve regeneration and functional recovery.(4)The therapy combining acupuncture and stem cell transplantation is an innovative treatment strategy for spinal cord injury and suitable for repairing neural circuits.It combines the wisdom of traditional Chinese medicine with the advantages of modern biotechnology,providing a new treatment option for spinal cord injury patients.However,this combination therapy is still in the research and exploration stage,and its long-term efficacy and safety need to be further verified.(5)Taken together,acupuncture and neural stem cell transplantation for the treatment of spinal cord injury has great potential for clinical application,but in-depth research and optimization of treatment options are still needed.In the future,we look forward to further revealing the efficacy mechanism and optimal indications of this therapy through more clinical trials and mechanism studies,so as to bring better hope of recovery and more efficient therapeutic effects to spinal cord injury patients.

Objective To analyze the operation of Measles Surveillance System (MSS) in Hebei Province, and to provide evidence for measles elimination. Methods Measles surveillance data was collected from the MSS from 2020 to 2023, and a modified weighted technology for order preference by similarity to an ideal solution (TOPSIS) method was used to evaluate the surveillance indexes of measles in Hebei Province. Results The operation quality of the measles surveillance system in Hebei Province was improved year by year, with the highest quality in 2023, and all the indicators reached the monitoring program standards. The quality of measles surveillance system was not balanced among cities, and the main influencing factor was the substandard sensitivity indicators. The quality of measles surveillance system was the highest in Baoding City and the lowest in Zhangjiakou City. Conclusion The measles surveillance system in Hebei province is running well, and the sensitivity of the surveillance system should be improved to keep the high-quality operation of the surveillance system.

Pathological interaction between CD4 + T cells and B cells is one of the important mechanisms of systemic autoimmune diseases. Follicular helper T cells (Tfh) and peripheral helper T cells (Tph) are key cells for assisting B cells. Tph cell is a newly discovered helper T cell subset, and their phenotype is PD-1 highCXCR5 -CD4 +. Tph cell and Tfh cell have certain differences in phenotype, function, and site of action. It interacts with B cells, promoting the differentiation of B cells into plasma cells and the production of autoantibodies, as well as promoting the formation of ELS to maintain local inflammation and antibody responses. Tph cells have recently been reported in various autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, Sjogren′s syndrome, and IgG4-related diseases. This review summarizes the progress in peripheral immune response of Tph cells in different systemic autoimmune diseases, aiming to explore the new mechanism of autoantibody production and help to develop new diagnostic and therapeutic targets in the future.

Objective:To develop radiomics score (RS) based on 18F-FDG PET/CT, and construct the machine learning model combining clinical and other relevant factors for personalized prediction of 2-year event-free survival (2-EFS) in patients with diffuse large B-cell lymphoma (DLBCL), and to perform interpretability analysis of the model. Methods:A total of 91 patients (49 males, 42 females; age (57.8±12.8) years) with pathologically confirmed DLBCL from December 2017 to December 2020 at the First Hospital of Shanxi Medical University were retrospectively analyzed. According to the ratio of 7∶3, patients were randomly divided into training set ( n=63) and test set ( n=28), and divided into non-progression group and progression group according to the follow-up results. The whole-body PET semi-quantitative parameters were calculated from the PET/CT images before treatment, and 328 radiomics features were extracted from the largest target lesions of patients. The least absolute shrinkage and selection operator (LASSO) was used to develop the RS. Clinical and PET characteristic difference analysis was performed through χ2 test and Mann-Whitney U test. Extreme gradient boosting (XGBoost) models were constructed based on clinical, PET radiomics features and RS, and the prediction efficiency of each model was evaluated by ROC AUC. The model interpretability was analyzed by using shapely additive explanation (SHAP). Results:Of all patients, 32 had disease progression and 59 did not. There were no significant differences in baseline characteristics between the training set and the test set ( χ2 values: 0.06-1.84, U values: 665.00-763.00, all P>0.05). The comparison between the progression group and non-progression group in the training set showed statistical differences in the international prognostic index (IPI) score ( χ2=4.87, P=0.027), myelocytomatosis viral oncogene (MYC) protein expression ( χ2=4.29, P=0.038), and metabolic tumor volume (MTV; U=307.00, P=0.038). Seven radiomics features were screened by LASSO. Among XGBoost models with different feature combinations, IPI score, MYC protein expression, MTV combined with RS had the highest predictive efficiency (training set: AUC=0.73; test set: AUC=0.70). Through SHAP analysis, RS was the most predictive feature in the optimal model. Conclusion:The machine learning integrated model of IPI score, MYC protein expression and MTV combined with RS can effectively predict the prognosis of DLBCL patients, and baseline 18F-FDG PET/CT radiomics can be used as a potential means to evaluate the prognosis of DLBCL patients.

Objective:To investigate the current status and related factors of antiviral treatment for chronic hepatitis B virus (HBV) infection in rural communities in China.Methods:In 2023, 866 chronic HBV-infected individuals from rural communities in Zhangqiu District, Jinan City, were included in the study. Basic information, disease status and antiviral treatment conditions of the infected individuals were collected through questionnaires, specimen collection and laboratory tests. Univariate and multivariate logistic regression were used to analyze the related factors of the antiviral treatment rate of those who met the indications for hepatitis B antiviral treatment.Results:The median age ( Q1, Q3) of subjects was 56 (48, 66) years old, among which 436 (50.4%) were males. There were 712 (82.2%) individuals who met the indications for hepatitis B antiviral treatment, and 110 individuals received antiviral treatment with a rate of 15.5%. Multivariate logistic regression analysis showed that compared with males, families with an average monthly income per capita of <1 000 yuan, no alcohol consumption, no smoking, and a family history of HBV infection, females ( OR=4.66, 95% CI: 2.88-7.53), families with an average monthly income per capita of 1 000-1 999 yuan ( OR=1.64, 95% CI: 1.00-2.68) and ≥2 000 yuan ( OR=2.78, 95% CI: 1.54-5.03), alcohol consumption ( OR=6.42, 95% CI: 2.80-14.7), smoking ( OR=1.98, 95% CI: 1.04-3.77), and no family history of HBV infection ( OR=1.90, 95% CI: 1.16-3.09) had a lower antiviral treatment rate for chronic HBV infection. Conclusion:The antiviral treatment rate of chronic HBV-infected individuals in rural communities of Zhangqiu District, Jinan City is low, and the related factors are female, high monthly income per capita, alcohol consumption, smoking, and no family history of HBV infection.

Objective:To investigate the association between frailty and prognosis of elderly patients in the emergency department, and to validate frailty screening tools suitable for the emergency department.Methods:This was a prospective cohort study. Clinical data of elderly patients over 60 years old treated in the emergency department of Beijing Bo'Ai Hospital from January to December 2021 were collected. The Frailty Screening Questionnaire (FSQ), FRAIL Scale (FRAIL) and Clinical Frailty Scale (CFS) were used to score patients, and patients were divided into frail or non-frail group according to the criteria of the above three scales. Twelve-month all-cause mortality was the primary endpoint, dependence and re-admission to the emergency department within 12 months were secondary outcomes. Receiver operating characteristic curves were used to evaluate the ability of the FSQ, FRAIL and CFS scores to predict the primary and secondary endpoints, and the areas under the curve (AUC) were calculated and compared. Survival analysis was performed using Cox hazard proportional regression model, and relative risk was expressed as hazard ratio ( HR) and 95% CI. Results:A total of 406 patients were included in the study. The AUCs (95% CI) of FSQ, FRAIL and CFS scores for predicting 12-month all-cause mortality were 0.879 (0.844-0.909), 0.838 (0.798-0.872), 0.906 (0.873-0.933), respectively (all P<0.001). The AUCs of 3 scores for predicting secondary endpoints ranged from 0.820 to 0.889 (all P<0.001). Pairwise comparisons of the AUCs showed that the CFS was superior to one or both of the other frailty screening scales in predicting 12-month all-cause mortality and dependence except for re-admission to emergency room within 12 months after discharge (all P<0.05). Cox regression analysis revealed that, after adjusting for sex, age, body mass index and comorbidities, frailty as defined by the FSQ, FRAIL, and CFS scales was independently associated with 12-month all-cause mortality, with the HRadj of 3.267 (95% CI: 2.406-4.435), 2.465 (95% CI: 1.819-3.341), 3.523 (95% CI: 2.648-4.687), respectively (all P<0.001). Conclusions:FSQ, FRAIL and CFS scores can predict adverse outcomes, the CFS is a practical frailty screening tool in the emergency department, and frailty screening can improve the risk stratification of older patients.