Platelet transfusion refractoriness (PTR) is one of the common problems in platelet transfusion, significantly impacting patient clinical outcomes and increasing the demand for allogeneic platelet transfusion. Both immune and non-immune factors contribute to PTR, among which the occurrence mechanism of immune platelet transfusion refractoriness (IPTR) involves humoral and cellular immune processes and is influenced by platelet storage, processing, and the patient's disease, therapy and immune status. This review comprehensively discusses the research related to the factors for alloimmune of IPTR, the mechanism of platelet clearance and its influencing factors. Furthermore, it explores feasible prevention and treatment measures such as platelet compatibility transfusion and clinical treatments. The aim is to provide a systematic cognition for a deeper understanding of the pathological process of platelet alloimmunization and clearance, and to provide a theoretical basis for the construction of precise clinical prevention and treatment strategies for IPTR, as well as to explore feasible research directions in this field in the future.

Objective: To investigate the efficacy of therapeutic plasma exchange and rituximab in the treatment of passenger lymphocyte syndrome (PLS) after ABO incompatible liver transplantation. Methods: PLS diagnosis was performed on the transplant patient using immunohematology testing techniques such as direct anti human globulin test (DAT), red blood cell elution test, and blood type antibody titer detection, combined with changes in hemolysis laboratory indicators; Severe immune hemolysis caused by PLS treated with red blood cell transfusion, therapeutic plasma exchange, and rituximab. Results: The patient was diagnosed with PLS 9 days after transplantation, and hemolysis caused by PLS continued until 20 days after transplantation; After three rounds of therapeutic plasma exchange and treatment with 100 mg rituximab, the titer of the patient's immune blood type antibody (IgG anti-B) decreased from 128 to 8 and was maintained until 27 days after transplantation. The patient's hemolytic symptoms improved and were discharged 32 days after transplantation. Conclusion: This case explores the application of therapeutic plasma exchange and rituximab in the treatment of severe hemolysis in PLS after transplantation, providing a reference for establishing standardized management of PLS after solid organ transplantation.

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 evaluate the efficacy and safety of plasma exchange (PE) in thymoma-associated myasthenia gravis (MG), thereby to provide theoretical support for its application in the treatment of thymoma-associated MG. Methods: A total of 133 patients with thymoma-associated MG admitted from January 2018 to September 2024 were retrospectively analyzed. Patients were matched using propensity score to reduce selection bias, yielding 22 matched pairs for both PE group (n=22) and non-PE group (n=22). Patient characteristics including gender, age of disease onset, course of disease, history of thymoma resection, clinical absolute scores [clinical absolute scores (CAS) and clinical relative scores (CRS)], and synchronized immunotherapy regimen of the two groups were analyzed. The CAS scores before and after treatment were compared between the two groups, and the CRS was used to assess the treatment efficiency. Safety of the two treatment regimens were also compared. Continuous variables were compared using the t-test or ANOVA, while categorical data were compared by the chi-square test. Results: A total of 133 patients were included and divided into two groups according to whether they underwent plasma exchange treatment: the PE group (n=22) and the non-PE group (n=111). To exclude bias caused by large difference in the number of cases between the two groups, we performed propensity score matching. After matching, the number of cases in both groups was 22. There was no significant difference in baseline clinical characteristics between the two groups (P>0.05), including gender, age of onset, duration of disease course, history of thymectomy and baseline CAS score before treatment. Compared to the non-PE group, patients in the PE group showed more significant improvement in CAS score (5.09±1.95 vs 3.59±1.50, P<0.05) and a higher CRS score (75.00% vs 50.00%, P<0.001). Compared to the non-PE group, PE group had significantly longer ICU stay, longer hospital stay and higher hospitalization cost (P<0.05). There was no statistically significant difference in adverse events between the two groups during treatment (P>0.05). During long-term follow-up, both the PE and non-PE groups showed relatively low 1-, 3-, and 5-year recurrence rate, with no significant difference between the two groups (P>0.05). Conclusion: This study indicates that plasma exchange has clear value in the treatment of patients with thymoma-associated myasthenia gravis. It can not only significantly improve patients' muscle strength to alleviate motor dysfunction and enhance quality of life, but also does not significantly increase the incidence of adverse reactions. Therefore, it can be regarded as one of the preferred treatment options that achieve a "balance between efficacy and safety" for such patients, and provides an important basis for optimizing treatment strategies, improving prognosis, and promoting the application of subsequent treatment regimens.

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 investigate the effect of double plasma molecular adsorption system and sequential half-dose plasma exchange (DPMAS+HPE) on the short-term survival rate of patients with hepatitis B associated acute-on-chronic liver failure (HBV-ACLF). 【Methods】 Data on HBV-ACLF cases hospitalized in our hospital from January 1, 2015 to December 31, 2022 were retrospectively collected, and were divided into standard comprehensive medical treatment group and DPMAS+HPE group according to different treatment methods. Propensity score matching (PSM) was used to eliminate inter group confounding bias. The baseline data and improvement of laboratory indicators after treatment between two groups were compared. Death related risk factors in HBV-ACLF patients were screened by logistic regression analysis, and cumulative survival rates at 30 and 90 days between the two groups were compared by Kaplan-Meier survival analysis. 【Results】 A total of 373 cases of HBV-ACLF were included in this study. Among them, 136 cases in the treatment group received DPMAS+HPE once on the basis of comprehensive internal medicine treatment, and 237 cases only received comprehensive internal medicine treatment. After PSM, 136 patients were included as the control group. The decrease in alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total protein (TP) in the treatment group before and after treatment was significantly greater than that in the control group (446.5 vs 159.0, 317.0 vs 92.0,5.2 vs 0.3), with statistically significant difference (P<0.05). DPMAS+HPE treatment is an independent protective factor for mortality in HBV-ACLF patients at 30 and 90 days (30 days: OR=0.497, P<0.05; 90 days: OR= 0.436, P<0.05). The cumulative survival rates at 30 and 90 days in the treatment group were significantly higher than those in the control group (30 days: 50.71% vs 44.12%, P<0.05; 90 days: 30.15% vs 22.79%, P<0.05). 【Conclusion】 DPMAS+HPE improves the short-term prognosis of HBV-ACLF patients and can serve as an effective artificial liver model for the treatment of HBV-ACLF patients.

[Abstract] [Objective] To explore the risk factors of blood transfusion in patients with isolated traumatic brain injury (iTBI) based on multiple machine learning methods, so as to establish a predictive model to provide reasonable guidance for blood transfusion in patients with iTBI. [Methods] A total of 2 273 patients with iTBI from the First Affiliated Hospital of Nanchang University from January 1, 2015 to June 30, 2021 were included to compare and analyze the differences in variables such as vital signs, clinical indicators and laboratory testing indicators between transfusion and non transfusion patients. Furthermore, six machine learning models were established to compare the performance of different models through cross validation, accuracy, specificity, recall, f1 value and area under the ROC curve. The SHAP plot was used to explain the influencing factors of blood transfusion in iTBI patients. [Results] This study included 2 273 iTBI patients, with a total of 301 patients receiving blood transfusions. There were significant differences (P<0.05) in gender, age, HR, clinical diagnosis, skull fracture, treatment methods, hemorrhagic shock, GCS, K, Ca, PT, APTT, INR, RBC, Hct, Hb and Plt between transfusion and non transfusion patients; Moreover, the LOS, incidence of complications, mechanical ventilation rate, ICU admission rate, readmission rate within 90 days and in-hospital mortality rate of transfusion patients were all higher than those of the non transfusion group (P<0.05). Six machine learning algorithms were used for model construction, and the validation results on the test set showed that the CatBoost model performed the best with an AUC of 0.911. Furthermore, the SHAP framework was used to explain and visualize the optimal model CatBoost, showing that surgical treatment, lower GCS, higher INR, lower Hct, lower K, lower Ca, age ≥60 years, skull fractures and hemorrhagic shock increase the risk of blood transfusion in patients. [Conclusion] This study established a machine learning model for predicting blood transfusion in iTBI patients, and the CatBoost model performed the best. This model may be useful and beneficial for identifying transfusion risks in this population, making clinical transfusion decisions and monitoring progress.

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 construct a blood transfusion prediction model for patients with severe traumatic brain injury (TBI), in order to predict the risk of blood transfusion and guide blood transfusion decision-making. 【Methods】 The clinical data of 756 patients with severe TBI admitted to the hospital from January 1, 2015 to June 30, 2021 were retrospectively analyzed. According to whether the patients were transfused with red blood cells after admission, the patients were divided into blood transfusion group (n=354) and non-blood transfusion group (n=402). The basic clinical data and prognostic indicators of the two groups were compared. Logistic regression algorithm was used to screen the risk factors related to blood transfusion in hospital to establish a nomogram prediction model, and the performance of the model was evaluated. 【Results】 No significant differences were noticed in gender, age, body temperature, cause of injury, ABO blood group, Rh blood group, serum Na and K concentrations between the two groups (P>0.05). Significant differences were found in Glasgow coma score (GCS), heart rate (HR), systolic blood pressure (SP), diastolic blood pressure (DP), shock index (SI), respiratory rate (RR), clinical diagnosis, treatment, hemoglobin concentration (Hb), hematocrit (Hct), platelet count (Plt) and coagulation function between the two groups (P<0.05). The length of stay, complication rate, ventilator utilization rate, ICU admission rate and 90-day readmission rate in the blood transfusion group were significantly higher than those in the non-blood transfusion group (P<0.05). However, there was no significant difference in in-hospital mortality between the two groups (P>0.05). Multivariate logistic regression analysis showed that surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR were independent risk factors for blood transfusion. A nomogram prediction model was constructed and the area under the ROC curve of the training set and the test set was 0.819(95% CI: 0.784-0.854) and 0.866(95% CI: 0.818-0.910), respectively, which had good predictive performance. 【Conclusion】 Surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR are independent risk factors for blood transfusion in adult patients with severe traumatic brain injury. The nomogram prediction model can better predict the blood transfusion demand of TBI patients and has high application value.

OBJECTIVES: In recent years, it has been reported that the anti-shock effect of plasma substitutes in adult patients with major burn in shock stage is not good. However, due to the shortage of clinical frozen plasma supply, it is impossible to guarantee that frozen plasma is used as colloidal solution for anti-shock treatment. The purpose of this study is to explore the effect of the infusion ration between frozen plasma and plasma substitutes on the prognosis of adult patients with major burn in shock stage. METHODS: This study enrolled 586 adult patients with major burn by selecting the hospitalization burn patients, who had been hospitalized at the Jiangxi province burn center from September 2014 to April 2019. The patients with the infusion ratio of frozen plasma to plasma substitutes ≥2꞉1 at 48 hours after admission were included in the experimental group, otherwise they were included in the control group. The basic clinical data and clinical prognosis indicator in the 2 groups were compared. Logistic univariate regression analysis was used to screen the influential factors of 30-day mortality in adult patients with major burn, and logistic multivariate regression analysis was used to obtain independent risk and protective factors; Kaplan-Meier method was used to draw the survival curve of the 2 groups, and log-rank test was used to compare the 30-day survival rate of the 2 groups. RESULTS: There were significant differences in the infusion volume of frozen plasma and plasma substitutes between the 2 groups at 48 hours after admission (both CONCLUSIONS Infusion ration between frozen plasma to plasma substitutes at 48 hours after admission is an independent protective factor for 30-day mortality of adult patients with major burn. In the early stage of adult patients with major burn, frozen plasma should be used as the anti-shock therapy as far as possible (frozen plasma꞉plasma substitute ≥2꞉1) to improve the prognosis and reduce the of 30-day mortality.
Adult ; Hospitalization ; Humans ; Plasma Substitutes ; Prognosis ; Retrospective Studies ; Shock