[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

Abstract Background and aims Hepatic ischemia-reperfusion injury (HIRI) is a major contributor to liver dysfunction and failure, particularly in the context of liver transplantation. Its pathogenesis is primarily driven by ferroptosis, oxidative stress, and mitochondrial dysfunction. Given the interplay among these mechanisms through redox imbalance and disrupted energy metabolism, nicotinic acid (NA)—recognized for its antioxidative and metabolic regulatory properties—emerges as a promising therapeutic candidate. This study aims to investigate the protective effects of NA on HIRI and elucidate its underlying mechanisms. Methods An HIRI model in mice and a hypoxia/reoxygenation (H/R) model in primary hepatocytes were established to evaluate the effects of NA treatment on oxidative stress. NA was administered prior to model induction. N-acetylcysteine (NAC) was used as a comparator. Comprehensive assessments of ferroptosis, oxidative stress, mitophagy, and mitochondrial biogenesis markers were conducted using Western blotting, immunohistochemistry, immunofluorescence, and biochemical assays. Results NA pretreatment reduced serum alanine aminotransferase, aspartate aminotransferase, and lactate dehydrogenase (LDH) levels, suppressed inflammation by decreasing neutrophil infiltration and macrophage activation, and mitigated oxidative stress by lowering reactive oxygen species (ROS) and malondialdehyde (MDA) levels. It enhanced antioxidant defenses, inhibited ferroptosis, and improved mitochondrial health through increased mitophagy, mitochondrial biogenesis, and mitochondrial permeability transition pore (mPTP) stabilization, leading to enhanced ATP production and mitochondrial function in HIRI. Conclusions NA improves mitochondrial function by promoting mitophagy and mitochondrial biogenesis, which reduces ferroptosis and oxidative stress, thereby alleviating HIRI.

Objective To explore the risk factors for platelet transfusion refractoriness(PTR)in patients with hemato-logical disorders,construct a prediction model and validate the model efficacy.Methods Patients with hematological disor-ders who received platelet transfusion therapy in the Chengdu Second People's Hospital from December 2021 to December 2022 were retrospectively included to judge the effectiveness of platelet transfusion and screened for risk factors by univariate and multivariate logistic regression.A prediction model for PTR was constructed using receiver operating characteristic(ROC)curve,calibration curve and decision curve(DCA)to assess the differentiation,calibration and clinical value of the model,respectively.Results A total of 334 hematological patients were included,including 168 males and 176 females,with a PTR incidence of 40.4%.Univariate and multivariate logistic regression analysis showed that platelet transfusion vol-ume,erythrocyte transfusion volume,and neutrophil ratio were risk factors for PTR(P<0.05).A prediction model for PTR in hematological patients was established based on these risk factors.The area under the model's curve was 0.8377(95%CI:0.723-0.772),the sensitivity was 58.52%,and the specificity was 89.95%.The calibration curve showed that the S∶P was 0.964,the maximum absolute difference Emax was 0.032,and the average absolute difference Eavg was 0.009.The DCA a-nalysis showed that the model had clinical application value when the risk threshold ranged from 0.2 to 0.9.Conclusion The PTR prediction model based on platelet transfusion volume,erythrocyte transfusion volume and neutrophil ratio can pro-vide a basis for effective platelet transfusion in hematological patients.

Objective:This study analyzed the expression of CD24 antigen on bone marrow plasma cells (BMPC) of patients with multiple myeloma (MM) and the predictive value of induction therapy.Methods:This clinical observational study utilized 258 MM patients samples treated at the Hematology Department of Beijing Jishuitan Hospital who met the inclusion criteria in the Department of Hematology, Capital Medical University, from August 12th, 2022 to February 1st, 2024. According to the different stages of the disease, patients were divided into three groups: 78 cases of Newly Diagnosed Multiple Myeloma(NDMM) (42 males and 36 females, aged 62±11), 56 cases of the relapse refractory group (34 males and 22 females, aged 64±9), and 124 cases of the disease remission group (68 males and 56 females, aged 62±10). Multiparameter flow cytometry (MFC) was used to detect the expression level of CD24 antigen on BMPC and the relationship between CD24 and MM disease status. The clinical data and test results of 78 NDMM patients at initial diagnosis were retrospectively analyzed, including gender, age, MFC detection of the positive expression rate of antigens (CD19, CD20, CD24, CD27, CD56), the results of efficacy evaluation after induction therapy, ISS staging, R-ISS staging, blood hemoglobin, β2-microglobulin, human serum albumin, serum creatinine, lactate dehydrogenas, correction of calcium, BMPC ratio, and the results of FISH. The patients were divided into a deep remission group [including complete remission (CR) and very good partial remission (VGPR)] with 43 cases and a non-deep remission group (non CR and VGPR) with 17 cases according to the difference of antigen positive expression rate after induction therapy. The differences of antigen expression on BMPC between the two groups were compared. Binary logistic regression was used to analyze the relationship between the expression of each antigen and the efficacy after induction therapy in patients, and the results showed that CD24 was more correlated with the achievement of deep remission after induction therapy than other antigens. Therefore, taking the positive expression rate of CD24 in NDMM patients at the initial diagnosis and deep remission after induction therapy as the research objects, the predictive value of CD24 for NDMM patients reaching deep remission after induction therapy was analyzed by using receiver operating characteristic curve (ROC), and the optimal cutoff value was obtained. NDMM was divided into two groups according to the cut-off value, and the differences between the two groups in clinical baseline data and prognostic indicators were compared.Results:The positive rates of plasma cell CD24 expression in the NDMM group, the relapse refractory group and the disease remission group were 2.18 (95% CI 0.08-81.85)%, 3.81 (95% CI 0.10-64.56)%, 8.74 (95% CI 0.79-95.55)% respectively. Compared with the disease remission group, the NDMM and relapse refractory group was lower ( Z=-7.889, -5.282, respectively, P<0.001). Univariate analysis showed that there was a significant difference in the positive expression rate of CD24 at initial diagnosis between the deep remission group and the non-deep remission group ( Z=-3.265, P<0.001), while there was no significant difference in CD19 ( Z=-0.271, P=0.787), CD20 ( Z=-0.205, P=0.837), CD27 ( Z=-0.582, P=0.560), and CD56 ( Z=-0.328, P=0.743) between the two groups. Binary logistic regression analysis showed that compared with other antigens [CD19 ( OR=1.045, 95% CI 0.975-1.120, P=0.217), CD20 ( OR=1.000, 95% CI 0.971-1.030, P=0.976), CD27 ( OR=0.997, 95% CI 0.977-1.016, P=0.734), CD56 ( OR=1.006, 95% CI 0.990-1.006, P=0.449)], the expression of CD24 ( OR=0.423, 95% CI 0.990-1.006, P=0.449) on BMPC in NDMM patients was most closely related to the achievement of deep remission was achieved after induction therapy. The lower the proportion of CD24 at the initial diagnosis was, the lower the probability of achieving deep remission after induction therapy was. The area under the curve (AUC) of CD24 in predicting deep remission after induction therapy was 0.772 (95% CI 0.655-0.889, P=0.001), with a sensitivity of 60.50%, a specificity of 85.00%, and the optimal critical value was 2.21%. Compared with the group with plasma CD24 positive rate>2.21%, the group with plasma CD24 positive rate<2.21% had a higher proportion of male (39.47%vs 65.00%, χ2=5.092, P=0.024), ISS stagingⅢ (41.67% vs 58.33%, χ2=6.175, P=0.046), β2 microglobulin (3.19 mg/L vs 4.14 mg/L, Z=-2.257, P=0.024), and BMPC [(8.672±1.827)% vs (19.530±3.188)%, t=-2.963, P=0.004] detected by MFC, and the differences were statistically significant. Conclusions:The low positive rate of plasma cell CD24 is closely related to the higher tumor burden and the worse disease status of MM patients. In addition, the positive expression rate of CD24 is at initial diagnosis can predict the efficacy achieved after induction therapy, and the lower positive rate of CD24 is, the worse the efficacy achieved after induction therapy. At the same time, MFC detection of CD24 is convenient and efficient in the evaluation and prediction of MM.

Objective: To compare the predictive efficacy of the two thrombosis risk assessment scores (Padua and IMPEDE scores) in venous thromboembolism (VTE) within 6 months in patients with newly diagnosed multiple myeloma (NDMM) in China. Methods: This study reviewed the clinical data of 421 patients with NDMM hospitalized in Beijing Jishuitan Hospital from April 2014 to February 2022. The sensitivity, specificity, accuracy, and Youden index of the two scores were calculated to quantify the thrombus risk assessment of VTE by the Padua and IMPEDE scores. The receiver operating characteristics curves of the two evaluation scores were drawn. Results: The incidence of VTE was 14.73%. The sensitivity, specificity, accuracy, and Youden index of the Padua score were 100%, 0%, 14.7%, and 0% and that of the IMPEDE score was 79%, 44%, 49.2%, and 23%, respectively. The areas under the curve of Padua and IMPEDE risk assessment scores were 0.591 and 0.722, respectively. Conclusion: IMPEDE score is suitable for predicting VTE within 6 months in patients with NDMM.
Humans ; Venous Thromboembolism/etiology* ; Multiple Myeloma/diagnosis* ; Risk Assessment ; Risk Factors ; ROC Curve ; Retrospective Studies

Objective:This study aims to investigate the clinical features and prognostic factors of patients with diffuse large B-cell lymphoma (DLBCL) and assess the prognostic value of diabetes mellitus (DM) and hyperglycemia during DLBCL treatment in DLBCL.Methods:The clinical data of 481 newly diagnosed DLBCL patients from January 1, 2009 to December 31, 2019 at Tianjin Medical University Cancer Institute and Hospital and Sun Yat-sen University Cancer Center were retrospectively collected, focusing on their blood glucose levels before and during treatment. Cox regression method was used for univariate analysis to assess prognostic factors, and the Kaplan-Meier method was used to draw survival curves to assess the prognostic value of DM and hyperglycemia during DLBCL treatment in patients with DLBCL.Results:Eighty-two (17.0%) patients had DM before DLBCL diagnosis and treatment, and 88 (18.3%) patients had at least one blood glucose increase during DLBCL treatment. Cox univariate analysis showed that age, Ann Arbor stage, international prognostic index, and DM were associated with overall survival (OS) and progression-free survival (PFS) (all P<0.05) . The pairwise comparison between the two groups showed that the OS ( P=0.001) and PFS ( P<0.001) of patients with pre-existing DM were significantly worse than those of patients without abnormal blood glucose. Moreover, the OS ( P=0.003) and PFS ( P<0.001) of patients with hyperglycemia during DLBCL treatment were significantly worse than those of patients without abnormal blood glucose. No significant difference exists between patients with DM and patients with hyperglycemia during DLBCL treatment (OS, P=0.557; PFS, P=0.463) . Additionally, patients with adequate glycemic control during chemotherapy had a better prognosis compared with patients with poor glycemic control (OS, P=0.037; PFS, P=0.007) . Conclusion:DM is an important factor affecting the prognosis of patients with DLBCL. Moreover, hyperglycemia during treatment is related to the poor prognosis of patients with DLBCL.

AIM To investigate the influences of Astragalus and Hurido effective components on apoptosis of rat glomerular mesangial cells.METHODS The proliferation of rat mesangial cells was induced by LPS and then intervened with Astragalus (astragalus polysaccharide,astragaloside Ⅳ,calycosin) and Hurido (hirudin).The cells were collected after 24 h.4',6-Diamidino-2-phenylindole (DAPI) staining was used to observe cell nuclear changes.Quantitative and qualitative expressions of Bcl-2 were detected by streptavidin-biotin complex (SABC).RESULTS Astragalus and Hurido effective components could induce the apoptosis of rat glomerular mesangial cells,and decrease the expression of Bcl-2.CONCLUSION Astragalus and Hurido effective components can induce the mesangial cell apoptosis by down-regulating Bcl-2 expression,which can be used for the treatment of mesangial proliferative glomerulonephritis.