Hyperkalemia is one of the common ion metabolism disorders in clinical practice. Hyperkalemia is defined as serum potassium higher than 5.0 mmol/L according to the guidelines at home and abroad. Acute severe hyperkalemia can cause serious consequences, such as flaccid paralysis, fatal arrhythmia, and even cardiac arrest. The use of renin-angiotensin- aldosterone system inhibitors, β-blockers and diuretics, low-sodium and high-potassium diets, and the presence of related comorbidities increase the occurrence of hyperkalemia. Hyperkalemia risk exist in all clinical departments, but there is a lack of a standardization in the management of multi- department cooperation in hospital. Therefore, a number of domestic nephrology and cardiology department experts have discussed a management model for multi-department cooperation in hyperkalemia, formulating the management standard on hospital evaluation, early warning, diagnosis and treatment, and process. This can promote each department to more effectively participate in nosocomial hyperkalemia diagnosis and treatment, as well as the long-term management of chronic hyperkalemia, improving the quality of hyperkalemia management in hospital.

Objective To track and evaluate the implementation of the Radiation Shielding Requirements in Room of Radiotherapy Installations—Part 1: General Principle (GBZ/T 201.1–2007) among relevant personnel in medical radiation institutions, and to provide a scientific basis for revising the standard. Methods According to the Guidelines for Health Standards Tracking Evaluation (WS/T 536–2017) and the implementation protocol of standard evaluation, an online survey was conducted among 212 relevant workers from 146 medical radiation institutions across 18 provinces in China. The data were aggregated and analyzed with the use of Microsoft Excel 2010. Results A total of 215 questionnaires were returned, of which 212 were valid. Among the valid respondents, 77.8% believe that this standard is universally applied; 96.2% believe that this standard can meet work needs; 63.7% have participated in relevant training on this standard; 74.1% use this standard once or more per year; and 10.8% believe that this standard needs to be revised. Conclusion Medial radiation workers have a high rate of awareness of the basic information and content of the standard, but the understanding and application of the standard content need to be improved. We recommend that relevant departments further strengthen the promotion of and training on the standard, revise some content based on actual situation, and improve workers’ ability to use the standard.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To explore the latent classes of recurrence risk perception in ischemic stroke patients and their relationship with health behaviors.Methods:Convenience sampling was used to select 312 patients with ischemic stroke from two ClassⅢ Grade A hospitals of Guangzhou from December 2022 to June 2023 as the research subject. Before discharge, the General Information Questionnaire, Recurrence Risk Perception Scale for Patients with Stroke, and Health Behavior Scale for Stroke Patients were used for investigation. One month later, the Health Behavior Scale for Stroke Patients was used for follow-up. Latent class analysis and multiple Logistic regression analysis were used to explore the latent classes of recurrence risk perception and their influencing factors, while multiple linear regression was used to analyze the relationship between latent classes of recurrence risk perception and health behavior at 1-month follow-up.Results:A total of 312 questionnaires were distributed, and 302 valid questionnaires were collected, with an effective response rate of 96.79%. One month later, 261 study subjects completed follow-up. The recurrence risk perception in ischemic stroke patients were divided into four classes of overall low perceived accuracy, light consequence-heavy disease-moderate perceived accuracy, heavy self-care-light diet-upper moderate perceived accuracy, and overall high perceived accuracy. Age, educational level, place of residence and monthly average income were influencing factors for different latent classes ( P<0.05). Compared with patients with overall low perceived accuracy, patients with heavy self-care-light diet-upper moderate perceived accuracy, as well as those with overall high perceived accuracy, showed better health behavior after discharge, with a statistically significant difference ( P<0.05) . Conclusions:Medical and nursing staff should provide targeted nursing interventions based on the common characteristics and individual differences of different classes of patients, helping patients correctly perceive the recurrence risk, improve health behavior, and prevent stroke recurrence.

Objective To investigate the feasibility of granzyme B(GB)promoter-controlled ferritin heavy chain(FTH1)reporter gene expression for monitoring the activation status of chimeric antigen receptor T cells(CAR-T)by magnetic resonance imaging(MRI).Methods Cytotoxic T lymphocytes(CTLs)were screened by Ficoll density gradient centrifugation and flow sorting.The GB promoter and FTH1 gene were ligated together with disialoganglioside 2(GD2)CAR,and lentiviral vectors were transfected into CTLs to construct GD2-CAR-T/pGB-FTH1 cells.GD2-CAR-T/pCMV-FTH1,GD2-CAR-T,and T cells served as control cells.CytoTox96@non-radioactive cytotoxicity was used to detect the killing effect of each group of cells after co-culture with human neuroblastoma cells(SK-N-SH).ELISA was employed to detect the coincubation factor as well as the amount of GB secretion.Western blotting,Prussian blue staining and cellular MRI were applied to detect the expression of the FTH1 gene after co-culture.Results CTLs were successfully obtained,and then GD2-CAR-T/pGB-FTH1,GD2-CAR-T/pCMV-FTH1 and GD2-CAR-T cells were constructed.The killing effect,co-incubation factor and GB secretion of the above 3 groups of cells were significantly higher than those of the T cells,and the level of GB expression was highest at day 1,and then decreased in order at day 3 and day 7 after co-culturing with SK-N-SH cells.The relative expression of FTH1 and iron content of the GD2-CAR-T/pGB-FTH1 cells showed the same trend as GB expression,and the MRI signals were gradually increased.There were no significant differences in the relative expression of FTH1,iron content and MRI signals in the GD2-CAR-T/pCMV-FTH1 cells at all time points.No FTH1 expression or iron aggregation was observed in the GD2-CAR-T and T cells groups.Conclusion MRI based on the FTH1 reporter gene driven by the granzyme B promoter can reflect the GB expression level and tumor killing effect of CAR-T cells,which provides a potential real-time visual means to monitor the cell activation status for CAR-T therapy.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Adenoid cystic carcinoma usually occurs in the salivary glands of the head and neck. It is a malignant tumor with a high degree of malignancy, resistance to radiotherapy and chemotherapy and poor prognosis. The clinical course of adenoid cystic carcinoma is slow and easy to be misdiagnosed. The main diagnosis and treatment means are individualized and precise treatment under the multi-disciplinary consultation mode, that is, surgical treatment and radiotherapy and chemotherapy. Adenoid cystic carcinoma is prone to relapse and hematologic metastasis, and the traditional radiotherapy and chemotherapy based therapies have not achieved satisfactory efficacy in the past three decades. How to detect, diagnose and treat early is an urgent task faced by clinicians.
Humans ; Carcinoma, Adenoid Cystic/pathology* ; Neoplasm Recurrence, Local ; Neck/pathology* ; Oropharynx/pathology* ; Diagnostic Errors

The concept of benefit finding, the assessment tools and the status quo of benefit finding for family caregivers of stroke patients were elaborated, the influencing factors of benefit finding of family caregivers of stroke patients were summarized, the current problems and the development direction of future research were pointed out, aiming to provide a reference for clinical staff to conduct research on benefit finding of family caregivers of stroke patients in China.

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.