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 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.

[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.

【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.

【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: To evaluate curative effects of coronavirus disease 2019 (COVID-19) patients by the transfusion of other convalescent plasma. METHODS: Retrospective analysis of the clinical data of 18 patients with severe and critical COVID-19, who were hospitalized in the ICU of Xianghu Branch of the First Affiliated Hospital of Nanchang University from February 1 to March 15, 2020. Patients were subdivided into an experimental group (=6, who had transfused the plasma) and an observation group (=12, who had no plasma transfusion). Basic clinical data and prognosis indexes of these two groups were compared. Moreover, for the experimental group, the dynamic changes of blood oxygen saturation before and after the transfusion, the changes of lymphocyte absolute value 48 hours after the transfusion, and the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid were analyzed. RESULTS: There were no significant differences in age, gender, blood type and other basic clinical data between the two groups (all >0.05).There were no significant differences in ventilator machine weaning time, extracorporeal membrane oxygenation (ECMO) weaning time, body temperature recovery to normal time, and hospitalization days between these two groups (all >0.05). For the experimental group, before, during and after the convalescent plasma transfusion, the blood oxygen saturation of all 6 patients at all time (1, 6, 8, 12, 24, 36, and 48 h) was more than 90%, and there was no significant fluctuation. There were 3 patients whose absolute value of lymphocyte was increased 48 hours after the transfusion, and the remaining was decreased. There were 5 patients whose SARS-CoV-2 nucleic acid detection turned negative 48 hours after the transfusion, accounting for 83.3%. CONCLUSIONS Transfusion of convalescent plasma will not affect outcomesof COVID-19 patients, which can neutralize SARS-CoV-2 in patients and reduce the loading capacity of SARS-CoV-2.
Betacoronavirus ; Blood Component Transfusion ; China ; Coronavirus Infections ; therapy ; Humans ; Immunization, Passive ; Pandemics ; Plasma ; Pneumonia, Viral ; therapy ; Retrospective Studies

OBJECTIVES: To explore the influential factors and titer trend of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific IgG antibody in convalescent patients with coronavirus disease 2019 (COVID-19), and to provide theoretical basis for the feasibility of clinical treatment of convalescent plasma. METHODS: Colloidal gold immunochromatography assay was used to detect the SARS-CoV-2 specific IgG antibody and its titer in 113 convalescent patients with COVID-19 who were followed up from February 19, 2020 to April 6, 2020. The basic characteristics and treatment factors of patients in the high titer group (antibody titer≥1꞉160, RESULTS: The difference in the clinical type of COVID-19, onset time, first admission C-reactive protein, absolute value of lymphocyte, absolute value of CD19 CONCLUSIONS Male COVID-19 patients might be more likely to produce high titer SARS-CoV-2 specific IgG antibodies than female. The peak level of SARS-CoV-2 specific IgG antibody in convalescent patients is maintained for a short period. Using plasma from convalescent COVID-19 patients for treatment should be within 28 d after discharge.
Antibodies, Viral ; Betacoronavirus ; COVID-19/therapy* ; Female ; Humans ; Immunization, Passive ; Immunoglobulin G ; Male ; Pandemics ; Pneumonia, Viral/epidemiology* ; SARS-CoV-2

Objective To evaluate the clinical value of apheresis platelets throught heanalysisof case control on the clinical efficacy and safety of cryopreserved apheresis platelets and fresh apheresis platelets.Methods 2 035 clinical cases of platelet transfusion in August 2014 to December 2016 by Using the closed loop intelligent path management and evaluation information system,456 cases were selected as control cases.Platelets were divided into the cryopreserved apheresis platelets group (group A,n=199) and fresh apheresis platelets group (group B,n=257) according to the transfused platelet type.The clinical application value of cryopreserved single platelets was evaluated by comparing the basic data,the effective indexes and safety indexes of the two groups.Results 1) The cases were 43.6％ (199/456) in A groups,and 56.4％ (257/456) in B groups,there were no significant difference in gender,age and medical and surgical cases between A and B group (P＞0.05);2) 199 cases in group A were cryopreserved platelets of 2 275 U,including 121 medicine cases,the total amount of transfusion was about 60.9％ (1 385/2 275),78 surgical cases accounted for 39.1％ (890/2 275);In the distribution of diseases,the blood system diseases accounted for 49.2％ (1 120/2 275),the total amount of obstetrics and gynecology disease infusion accounted for 10.6％ (240/2 275),and the amount of tumor radiotherapy and chemotherapy accounted for 6.2％ (140/2 275);The proportion of ABO blood type distribution was O type 25.9％,A type 22.9％,Btype 20.7％,ABtype 30.5％,respectively;3) The Plt counts of group A and B were significantly different before and after transfusion (P ＜0.05).But there was no significant difference between the two groups of cases before transfusion and 24h Plt count after transfusion,the Plt counts difference,and 24 h CCI (P＞0.05);4) The effective rates of platelet transfusion in group A and B were 76.9％ and 76.7％,respectively.Which has no significant difference between the two groups (P＞0.05)).There was no significant difference between the two groups in medical and surgical cases (P＞0.05),but the effective rate of surgical cases in group A (84.6％) was higher than that in B group (75.3％).The difference effect of medicine and surgery cases in B group were not statistically significant (P＞0.05),but the difference effect of medicine and surgery cases in A group was statistically significant (P＜0.05),platelet transfusion inefficient in surgical cases (15.4％) was significantly lower than that of cases (28.1％);5) The incidence of adverse reactions of blood transfusion was 3.5％,4.7％ in group A and B,and the blood transfusion mortality rate was zero,the difference was not statistically significant (P＞ 0.05).Conclusion The clinical effectiveness and safety of cryopreserved apheresis platelets are similar to those of fresh apheresis platelets,and the former can be widely Used in clinic,in particular,it has certain advantages in the surgical hemostatic effect.but for repeated infusion cases or platelet transfusion ineffective cases should be given priority to fresh apheresis platelets.