[Objective] To analyze the loss rate of platelet donors and evaluate the strategies for establishing a platelet donor bank. [Methods] A total of 1 443 donors who joined the HLA and HPA gene donor bank for platelets in Henan Province from 2018 to 2020 were included in this study. Data on the total number of apheresis platelet donations, annual donation frequency, age at enrollment, donation habits (including the number of platelets donated per session and whether they had previously donated whole blood), and enrollment location were collected from the platelet donor information management system. Donor loss was determined based on the date of their last donation. The loss rates of different groups under various conditions were compared to assess the enrollment strategies. [Results] By the time the platelet bank was officially operational in 2022, 421 donors had been lost, resulting in an loss rate of 29% (421/1 443). By the end of 2023, the overall cumulative loss rate reached 52% (746/1 443). The loss rate was lower than the overall level in groups meeting any of the following conditions: total apheresis platelet donations exceeding 50, annual donation frequency of 10 or more, age at enrollment of 40 years or older, donation of more than a single therapeutic dose per session, or a history of whole blood donation two or more times. Additionally, loss rates varied across different enrollment locations, with higher enrollment numbers generally associated with higher loss rates. [Conclusion] Through a comprehensive analysis of donor loss, our center has adjusted its strategies for establishing the donor pool. These findings also provide valuable insights for other blood collection and supply institutions in building platelet donor banks.

Objective To construct a knowledge graph of healthcare-associated infection(HAI)prevention and control course,and evaluate its usability.Methods Based on the constructivist learning theory and the analyze-de-sign-develop-implement-evaluate(ADDIE)model,knowledge from various sources such as books,guidelines,and literature related to HAI prevention and control were integrated.The knowledge graph of HAI prevention and con-trol course were designed and constructed with the support of knowledge graph technology in Chaoxing Fanya plat-form.Thirty medical students were selected by convenience sampling method to try out the course knowledge graph.System usability scale and usage effect questionnaire were filled out to evaluate the usability of the knowledge graph.Results The knowledge graph of HAI prevention and control course contained 379 knowledge points asso-ciated with 520 test questions and 56 learning resources.After testing,the total score([70.50±12.20]points)was obtained for the usability of the knowledge graph.Among the four dimensions of the usage effect agreement ques-tionnaire,satisfaction,learning attitude,learning ability,and learning resource support accounted for 93.33％-96.67％,90.00％,93.33％-96.67％,and 83.33％-90.00％,respectively,with a high overall satisfaction rate.Conclusion The knowledge graph of HAI prevention and control course has good usability,which can realize students'personalized independent learning and improve their learning efficiency.

Objective:To develop a nomogram model for predicting the risk of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) and to validate the stability of the prediction performance of the model.Methods:The patients with MV admitted to the Department of Critical Care Medicine of General Hospital of Ningxia Medical University from January 2019 to December 2022 were retrospectively selected according to the order of admission. The patients with MV were divided into the non-VAP group and the VAP group according to whether VAP occurred. The clinical data of the two groups, including general information, disease, medication, condition, and operation-related indicators were collected as candidate predictors of the model for comparison. Multivariate logistic stepwise forward regression analysis was used to screen the predictors that finally entered the model, and a nomogram model was constructed. The model discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), the diagnostic test results of the model at the predicted threshold were calculated, the Hosmer-Lemeshow test was used to evaluate the model fit, and the Bootstrap resampling was used 1 000 times for internal validation, and model calibration and clinical applicability were evaluated by calibration curve and decision analysis curve, respectively.Results:A total of 1 250 patients with MV were included, including 1 102 patients in the non-VAP group and 148 patients in the VAP group, and the prevalence of VAP was 11.8%. The detection of multidrug-resistant organisms, chronic kidney disease, brain injury, oxygenation index, the place of tracheal intubation, reintubation, use of bronchoscopy, use of antibiotics, and MV duration were model predictors of VAP. The AUC of the nomogram model was 0.917 (95% CI: 0.895-0.939), the maximum Youden index of 0.697 corresponded to a prediction threshold of 0.096. The model accuracy, sensitivity and specificity were 0.836, 0.865, and 0.832, respectively. The positive predictive value and the negative predictive value were 0.409 and 0.979, respectively. The Hosmer- Lemeshow test indicated that the model fit well ( P=0.938). The results of the internal validation of the model showed that the predicted risk of the calibration curve was generally consistent with the actual risk, and the decision threshold probability of the decision analysis curve ranged from 2% to 90%. Conclusions:The nomogram model developed in this study is simple, convenient and has relatively stable prediction performance, which can be externally validated to evaluate the extrapolation of the model, and provide a basis for individualized clinical prediction of the risk of VAP in patients with MV.

Probiotics have shown excellent application prospects in preventing and treating many diseases. However, their sensitivity to the harsh environment in vivo always leads to a massive loss of viability and insufficient therapeutic effect. Fortunately, modified probiotics have emerged and provide multiple possibilities for their use in various diseases. Modification not only endows probiotics with extra capacity to resist severe environments but also gives them exogenous characteristics, such as prolonged retention time and improved therapeutic effects. Modified probiotics could combine with other therapies, which has opened up new avenues to enhance the efficacy of probiotic-based therapy. In this review, we have summarized the current physicochemical and biological modification strategies of probiotics. In addition, the progress of research on probiotic-based combination therapy has also been extensively reviewed, which contributes to the enhanced delivery of probiotics or other active constituents and provides new ideas for disease treatment, bioimaging, and diagnosis.

Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

OBJECTIVE To explore the risk factors for central line-associated bloodstream infection(CLABSI)in the maintenance hemodialysis(MHD)patients based on the informatization surveillance system and establish and verify the risk prediction model so as to provide bases for early identification and prevention of CLABSI.METHODS A total of 300 MHD patients who were treated in hemodialysis center of the Affiliated Hospital of Xuzhou Medical University from Jan.2020 to Dec.2023 were recruited as the research subjects and were randomly divided into the training set group with 210 cases and the validation set group with 90 cases in a 7∶3 ratio.The risk factors for the CLABSI were analyzed,the prediction model was established and verified.The performance of the model was evaluated by the area under the curve(AUC)of receiver operating characteristic(ROC)curves and Hosmer-Lemeshow goodness of fit test.RESULTS Among the 300 MHD patients who were treated with central venous catheters,32 were diagnosed with CLABSI,and the incidence was 0.65 per 1,000 catheter days.Multivari-ate analysis showed that catheter indwelling time,repeated catheterization,previous history of catheter-related in-fection and diabetes mellitus were the risk factors for the CLABSI in the MHD patients(P＜0.05).The model based on the logistic regression equation was established as follows:logit(P)=-5.661+0.024 × catheter in-dwelling duration(week)+2.037 × repeated catheterization+1.546 × previous history of catheter-related infec-tion+3.391× diabetes mellitus.ROC curve analysis showed that the AUC of the training set was 0.916(95％CI:0.837 to 0.994),with the sensitivity 87.00％,the specificity 86.63％,Youden index 0.736;the AUC of the vali-dation set was 0.797(95％CI:0.632 to 0.962),with the sensitivity 77.78％,the specificity 82.72％,the Youden index 0.605.The model showed excellent discrimination and calibration degree.CONCLUSION The logistic regres-sion equation that is established based on the 4 risk factors,catheter indwelling duration,repeated catheterization,previous history of catheter-related infection and diabetes mellitus,shows remarkable predictive efficiency,and it can provide evidence for clinical screening and prevention of CLABSI.

To address the common clinical problems associated with warm needling moxibustion, such as burns, bending of needle handles, and the inability to perform moxibustion during oblique needling, an adjustable warm needling moxibustion device is designed and has been granted a national patent. This device consists of five components: a moxa cylinder, an adjustable arm, a supporting tube, a temperature alarm, and a fixing strap. It allows infrared heat radiation from the moxa to pass through while blocking falling ash, thereby ensuring therapeutic efficacy and preventing burns. The device accommodates both perpendicular and oblique needling angles and adapts to various body positions, effectively avoiding deformation of the needle handle. It is easy to operate and offers high safety.
Moxibustion/methods* ; Humans ; Equipment Design ; Needles

This study aims to develop a fully automated method for tooth segmentation and root canal measurement based on cone beam computed tomography (CBCT) images, providing objective, efficient, and accurate measurement results to guide and assist clinicians in root canal diagnosis grading, instrument selection, and preoperative planning. The method utilized Attention U-Net to recognize tooth descriptors, cropped regions of interest (ROIs) based on the center of mass of these descriptors, and applied an integrated deep learning method for segmentation. The segmentation results were mapped back to the original coordinates and position-corrected, followed by automatic measurement and visualization of root canal lengths and angles. The results indicated that the Dice coefficient for segmentation was 96.42%, the Jaccard coefficient was 93.11%, the Hausdorff Distance was 2.07 mm, and the average surface distance was 0.23 mm, all of which surpassed existing methods. The relative error of the root canal working length measurement was 3.15% (< 5%), the curvature angle error was 2.85 °, and the correct classification rate of the treatment difficulty coefficient was 90.48%. The proposed methods all achieved favorable results, which can provide an important reference for clinical application.
Cone-Beam Computed Tomography/methods* ; Deep Learning ; Humans ; Dental Pulp Cavity/diagnostic imaging* ; Image Processing, Computer-Assisted/methods*

Standardised emergency management protocols for hand injury in microsurgery is critical, as it directly determines ultimate clinical outcomes. This consensus consolidates expert insights regarding diagnostic and treatment procedure for hand injury in microsurgery, emergency support protocols and key points of emergency workflow optimisation. It summarises the opinions of experts and puts forward standardised recommendations to guide clinical practice in microsurgical treatment process, so as to further improve the quality of treatment for hand injury in microsurgery and maximise the protection of limb function and quality of life of patients.

Objective:To investigate the drug resistance gene characteristics, plasmid characteristics and genome tracing of Shigella sonnei causing a bacillary dysentery outbreak in Shandong Province. Methods:Sixty-five Shigella sonnei strains isolated from a 2021 outbreak in a county of Shandong Province were analyzed using antimicrobial susceptibility testing, whole genome sequencing (WGS), characterization of resistance and virulence genes, plasmid profiling, core genome multilocus sequence typing (cgMLST), and single nucleotide polymorphism (SNP) analysis. Results:All isolates had the same resistance phenotype and genotypes and were multidrug-resistant ESBL-producing Shigella sonnei, carrying important virulence genes. Plasmid analysis revealed a conserved genetic arrangement, pil( M/ N/ O2/ P)-tra( F/ H/ J/ K/ N/ O/ P/ Q)-IS Ecp1- blaCTX-M-14-Tn 903- yub( J/ I/ F/ G/ E/ D), and shared across strains from diverse regions and bacterial species. The cgMLST and SNP analyses demonstrated concordant clustering, with all 65 outbreak-related strains forming a single cluster alongside human-derived strains from Guangxi. Conclusion:The ESBL-producing Shigella sonnei responsible for the outbreak shares a homologous relationship with Guangxi human-derived strains, and the detected resistance plasmids and virulence genes underscore the need to strengthen drug resistance surveillance and genome tracing.