Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding developed a strategy for platelet and plasma infusion management in critically ill children based on systematic reviews and consensus meetings of international multidisciplinary experts. One good practice statement and six expert consensus statements were proposed for plasma and platelet transfusions in critically ill children following severe trauma, traumatic brain injury, and/or intracranial hemorrhage. This article introduces the specific methods and basis for the formation of recommendations in this part of the guide.

Objective: To investigate the current knowledge status of transfusion medicine among pediatricians/postgraduates and the reliability of large language models (LLMs) for assisted learning, and to assess changes in pediatricians' transfusion medicine knowledge before and after the implementation of the "Pediatric Transfusion Guideline" (hereafter referred to as the "Guideline"). Methods: In January 2022 (prior to the implementation of the "Guideline"), a questionnaire was developed based on the "Guideline" content and distributed to pediatricians. Subsequently, in July 2025 (after the implementation of the "Guideline"), the "Pediatric Transfusion Medicine Knowledge Questionnaire" was designed based on the content of the January 2022 questionnaire. This questionnaire survey was conducted on pediatricians/postgraduates and LLMs. We analyzed the level of transfusion medicine knowledge among pediatricians/postgraduates and the reliability of LLMs for assisted learning, and compared the accuracy of pediatricians' responses before and after "Guideline" implementation. Results: The survey results after the implementation of the "Guidelines" revealed that pediatricians/postgraduates achieved response accuracy rates exceeding 80% on the topic of "Patient Blood Management". However, response accuracy rates were below 30% for topics including "Types and Indications of Blood Components/Products" and "E-valuation of Transfusion Efficacy". The pediatricians' accuracy rates for related questions before and after the implementation of the "Guidelines" were 14.7%-68.9% and 3%-38%, respectively, and the comparison of accuracy rates for each question showed significant differences (P<0.001). The accuracy rates of the LLMs on the questionnaire were all below 90%. Among them, Doubao (81.1%) and Kimi (86.4%) achieved relatively higher accuracy rates, while Tencent Yuanbao (Hunyuan) had the lowest accuracy rate at only 59.5%. Conclusion: The implementation of the "Guideline" may have improved pediatricians' knowledge level of pediatric transfusion medicine. However, their knowledge level of pediatric transfusion remains low, and LLMs cannot yet provide absolutely reliable guidance. Systematic training in pediatric transfusion medicine is urgently needed.

Objective To develop and compare the predictive performance of five machine learning models for adverse postoperative outcomes in cardiac surgery patients, and to identify key decision factors through SHapley Additive exPlanations (SHAP) interpretability analysis. Methods A retrospective collection of perioperative data (including demographic information, preoperative, intraoperative, and postoperative indicators) with 88 variables was conducted from adult cardiac surgery patients at the First Affiliated Hospital of Xinjiang Medical University in 2023. Adverse postoperative outcomes were defined as the occurrence of acute kidney injury and/or in-hospital mortality during the postoperative hospitalization period following cardiac surgery. Patients were divided into an adverse outcome group and a favorable outcome group based on the presence of adverse postoperative outcomes. After screening feature variables using the least absolute shrinkage and selection operator (LASSO) regression method, five machine learning models were constructed: eXtreme gradient boosting (XGBoost), random forest (RF), gradient boosting machine (GBM), light gradient boosting machine (LightGBM), and generalized linear model (GLM). The dataset was randomly divided into a training set and a test set at a 7 : 3 ratio using stratified sampling, with postoperative outcome as the stratification factor. Model performance was evaluated using receiver operating characteristic curves, decision curve analysis, and F1 Score. The SHAP method was applied to analyze feature contribution. Results A total of 639 patients were included, comprising 395 males and 244 females, with a median age of 62 (55, 69) years. The adverse outcome group consisted of 191 patients, while the favorable outcome group included 448 patients, resulting in an adverse postoperative outcome incidence of 29.9%. Univariate analysis showed no significant differences between the two groups for any variables (P>0.05). Using LASSO regression, 16 feature variables were selected (including cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, systemic inflammatory response index, etc.), and five machine learning models (GLM, RF, GBM, LightGBM, XGBoost) were constructed. Evaluation results demonstrated that the XGBoost model exhibited the best predictive performance on both the training set (n=447) and test set (n=192), with area under the curve values of 0.761 [95%CI (0.719, 0.800) ] and 0.759 [95%CI (0.692, 0.818) ], respectively. It also significantly outperformed other models in positive predictive value, and balanced accuracy in the test set. Decision curve analysis further confirmed its clinical utility across various risk thresholds. SHAP analysis indicated that variables such as cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, and inflammatory markers (SIRI, NLR, CAR) had high contributions to the prediction. Conclusion The XGBoost model effectively predicts adverse postoperative outcomes in cardiac surgery patients. Clinically, attention should be focused on cardiopulmonary bypass support time, postoperative blood glucose control, and monitoring of inflammatory levels to improve patient prognosis.

Home rehabilitation is the main rehabilitation model for elderly patients with hip fractures in China, and the application of digital health technology shows great potential in improving the quality of home rehabilitation for this population. This paper describes the concept of digital health technology, the current application status of different types of digital health technology in home rehabilitation for elderly patients with hip fractures, and discusses existing issues and future prospects, aiming to provide a reference for digital home rehabilitation nursing for elderly hip fracture patients.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

The global incidence rate of cancer is increasing yearly,and chemotherapy-induced gastrointestinal mucosal injury has become a crucial factor affecting patients'therapeutic prognosis;however,there is currently a lack of effective therapeutic drugs to address this issue.There is thus an urgent need to establish more ideal animal models of chemotherapy-induced gastrointestinal mucosal injury,to support the exploration of its pathogenesis and the development of therapeutic drugs.This review considered relevant literature published during the period from 2019 to 2024,to provide a comprehensive summary and analysis from several perspectives,including the selection of experimental animals,chemotherapeutic drugs and modeling method,evaluation indicators,and practical applications.Furthermore,we highlight several existing issues with current models,including the lack of standardized modeling method,insufficient research on models with a tumor background,and inadequate exploration of novel cell death mechanisms.This collation of the literature also revealed the gradual emergence of traditional Chinese medicine as a research hotspot,with potential for the treatment of gastrointestinal mucosal injury.Further studies of effective medicines are warranted to identify interventional strategies for chemotherapy-induced gastrointestinal mucosal injury.

Home rehabilitation is the main rehabilitation model for elderly patients with hip fractures in China, and the application of digital health technology shows great potential in improving the quality of home rehabilitation for this population. This paper describes the concept of digital health technology, the current application status of different types of digital health technology in home rehabilitation for elderly patients with hip fractures, and discusses existing issues and future prospects, aiming to provide a reference for digital home rehabilitation nursing for elderly hip fracture patients.

The global incidence rate of cancer is increasing yearly,and chemotherapy-induced gastrointestinal mucosal injury has become a crucial factor affecting patients'therapeutic prognosis;however,there is currently a lack of effective therapeutic drugs to address this issue.There is thus an urgent need to establish more ideal animal models of chemotherapy-induced gastrointestinal mucosal injury,to support the exploration of its pathogenesis and the development of therapeutic drugs.This review considered relevant literature published during the period from 2019 to 2024,to provide a comprehensive summary and analysis from several perspectives,including the selection of experimental animals,chemotherapeutic drugs and modeling method,evaluation indicators,and practical applications.Furthermore,we highlight several existing issues with current models,including the lack of standardized modeling method,insufficient research on models with a tumor background,and inadequate exploration of novel cell death mechanisms.This collation of the literature also revealed the gradual emergence of traditional Chinese medicine as a research hotspot,with potential for the treatment of gastrointestinal mucosal injury.Further studies of effective medicines are warranted to identify interventional strategies for chemotherapy-induced gastrointestinal mucosal injury.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Objective To establish a human α-synuclein nuclear localization signal transgenic mouse model and investigate the effects of α-synuclein nuclear localization on the behavior of mice.Methods Human α-synuclein nuclear localization signal and EGFP lentiviral vectors were constructed.Transgenic mice were created with the microinjection method.Using PCR and Western Blot method to identify the genotypes and protein expression of the transgenic founder mice and their offsprings.The immunofluorescence was used to examine the localization of human α-synuclein in the mouse brain tissue.The behavioral changes of the transgenic mice were evaluated by the open field test,rotarod test,and O maze test.Results The h SNCA-NLS gene was successfully inserted into the mouse genome,the human α-syn was successfully expressed,and the human α-syn has localized with the nuclear.Further studies found that human α-synuclein nuclear localization signal transgenic mice had significant motor dysfunction,astrocyte proliferation and inflammatory response at 2 months of age and exhibited significant anxiety-like symptoms and reduced expression of the γ-aminobutyric acid(GABA)gene at 9 months of age,which persisted until 12 months of age.Conclusions A human α-synuclein nuclear localization signal transgenic mouse model has been successfully established.The mice exhibit significant motor dysfunction and anxiety-like symptoms.The successful establishment of this model provides a foundation for studying the role of α-syn nuclear localization in Parkinson's disease.